EVERTON vs CHELSEA

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 15:30 | XG-database only

Executive assessment: Chelsea lead the recorded squad attacking xG per 90 player-minutes (0.165 versus 0.207, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Everton; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Everton approach: Emphasise chance generation from the forward group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Chelsea approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 37% to Everton, 27% to a draw and 36% to Chelsea. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

BRENTFORD vs LIVERPOOL

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 18:00 | XG-database only

Executive assessment: Liverpool lead the recorded squad attacking xG per 90 player-minutes (0.206 versus 0.212, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Brentford; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Brentford approach: Emphasise chance generation from the defense group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Liverpool approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 39% to Brentford, 27% to a draw and 34% to Liverpool. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

FULHAM vs HULL CITY

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 18:00 | XG-database only

Executive assessment: Fulham lead the recorded squad attacking xG per 90 player-minutes (0.175 versus 0.131, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Fulham; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Fulham approach: Emphasise chance generation from the forward group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Hull City approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 40% to Fulham, 27% to a draw and 33% to Hull City. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

MANCHESTER CITY vs IPSWICH TOWN

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 18:00 | XG-database only

Executive assessment: Manchester City lead the recorded squad attacking xG per 90 player-minutes (0.237 versus 0.166, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Manchester City; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Manchester City approach: Emphasise chance generation from the forward group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Ipswich Town approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 45% to Manchester City, 27% to a draw and 28% to Ipswich Town. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

NEWCASTLE UNITED vs ASTON VILLA

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 20:30 | XG-database only

Executive assessment: Newcastle United lead the recorded squad attacking xG per 90 player-minutes (0.145 versus 0.120, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Newcastle United; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Newcastle United approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Aston Villa approach: Use the midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 42% to Newcastle United, 27% to a draw and 31% to Aston Villa. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

BOURNEMOUTH vs SUNDERLAND

PRE-MATCH ANALYTICAL INTELLIGENCE | 18 OCT 2026 | 17:00 | XG-database only

Executive assessment: Sunderland lead the recorded squad attacking xG per 90 player-minutes (0.218 versus 0.245, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Bournemouth; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Bournemouth approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Sunderland approach: Use the midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 38% to Bournemouth, 27% to a draw and 35% to Sunderland. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

BRIGHTON & HOVE ALBION vs CRYSTAL PALACE

PRE-MATCH ANALYTICAL INTELLIGENCE | 18 OCT 2026 | 17:00 | XG-database only

Executive assessment: Brighton & Hove Albion lead the recorded squad attacking xG per 90 player-minutes (0.255 versus 0.180, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Brighton & Hove Albion; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Brighton & Hove Albion approach: Emphasise chance generation from the defense group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Crystal Palace approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 44% to Brighton & Hove Albion, 27% to a draw and 29% to Crystal Palace. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

LEEDS UNITED vs MANCHESTER UNITED

PRE-MATCH ANALYTICAL INTELLIGENCE | 18 OCT 2026 | 17:00 | XG-database only

Executive assessment: Manchester United lead the recorded squad attacking xG per 90 player-minutes (0.161 versus 0.222, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Leeds United; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Leeds United approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Manchester United approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 38% to Leeds United, 27% to a draw and 35% to Manchester United. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

NOTTINGHAM FOREST vs ARSENAL

PRE-MATCH ANALYTICAL INTELLIGENCE | 18 OCT 2026 | 19:30 | XG-database only

Executive assessment: Arsenal lead the recorded squad attacking xG per 90 player-minutes (0.177 versus 0.194, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Nottingham Forest; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Nottingham Forest approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Arsenal approach: Use the defense group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 37% to Nottingham Forest, 27% to a draw and 36% to Arsenal. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

TOTTENHAM vs COVENTRY CITY

PRE-MATCH ANALYTICAL INTELLIGENCE | 19 OCT 2026 | 23:00 | XG-database only

Executive assessment: Tottenham lead the recorded squad attacking xG per 90 player-minutes (0.126 versus 0.117, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Tottenham; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Tottenham approach: Emphasise chance generation from the defense group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Coventry City approach: Use the forward group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 40% to Tottenham, 27% to a draw and 33% to Coventry City. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

EINTRACHT FRANKFURT vs 1. FC KOLN

PRE-MATCH ANALYTICAL INTELLIGENCE | 16 OCT 2026 | 22:30 | XG-database only

Executive assessment: Eintracht Frankfurt lead the recorded squad attacking xG per 90 player-minutes (0.239 versus 0.120, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Eintracht Frankfurt; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Eintracht Frankfurt approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

1. FC Koln approach: Use the forward group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 49% to Eintracht Frankfurt, 27% to a draw and 24% to 1. FC Koln. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

SV ELVERSBERG vs FC AUGSBURG

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 17:30 | XG-database only

Executive assessment: FC Augsburg lead the recorded squad attacking xG per 90 player-minutes (0.185 versus 0.216, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is FC Augsburg; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

SV Elversberg approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

FC Augsburg approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 35% to SV Elversberg, 27% to a draw and 38% to FC Augsburg. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

HAMBURGER SV vs VFB STUTTGART

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 17:30 | XG-database only

Executive assessment: VfB Stuttgart lead the recorded squad attacking xG per 90 player-minutes (0.051 versus 0.141, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is VfB Stuttgart; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Hamburger SV approach: Emphasise chance generation from the defense group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

VfB Stuttgart approach: Use the defense group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 27% to Hamburger SV, 27% to a draw and 46% to VfB Stuttgart. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

WERDER BREMEN vs SC PADERBORN 07

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 17:30 | XG-database only

Executive assessment: Werder Bremen lead the recorded squad attacking xG per 90 player-minutes (0.167 versus 0.070, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Werder Bremen; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Werder Bremen approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

SC Paderborn 07 approach: Use the forward group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 43% to Werder Bremen, 27% to a draw and 30% to SC Paderborn 07. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

FC SCHALKE 04 vs 1. FSV MAINZ 05

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 17:30 | XG-database only

Executive assessment: 1. FSV Mainz 05 lead the recorded squad attacking xG per 90 player-minutes (0.074 versus 0.235, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is 1. FSV Mainz 05; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

FC Schalke 04 approach: Emphasise chance generation from the defense group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

1. FSV Mainz 05 approach: Use the forward group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 28% to FC Schalke 04, 27% to a draw and 45% to 1. FSV Mainz 05. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

UNION BERLIN vs BORUSSIA DORTMUND

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 17:30 | XG-database only

Executive assessment: Borussia Dortmund lead the recorded squad attacking xG per 90 player-minutes (0.095 versus 0.175, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Borussia Dortmund; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Union Berlin approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Borussia Dortmund approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 36% to Union Berlin, 27% to a draw and 37% to Borussia Dortmund. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

BAYERN MUNICH vs RB LEIPZIG

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 20:30 | XG-database only

Executive assessment: Bayern Munich lead the recorded squad attacking xG per 90 player-minutes (0.318 versus 0.183, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Bayern Munich; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Bayern Munich approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

RB Leipzig approach: Use the defense group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 44% to Bayern Munich, 27% to a draw and 29% to RB Leipzig. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

BAYER LEVERKUSEN vs SC FREIBURG

PRE-MATCH ANALYTICAL INTELLIGENCE | 18 OCT 2026 | 17:30 | XG-database only

Executive assessment: SC Freiburg lead the recorded squad attacking xG per 90 player-minutes (0.238 versus 0.278, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is SC Freiburg; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Bayer Leverkusen approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

SC Freiburg approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 31% to Bayer Leverkusen, 27% to a draw and 42% to SC Freiburg. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

BORUSSIA MONCHENGLADBACH vs TSG HOFFENHEIM

PRE-MATCH ANALYTICAL INTELLIGENCE | 18 OCT 2026 | 19:30 | XG-database only

Executive assessment: TSG Hoffenheim lead the recorded squad attacking xG per 90 player-minutes (0.100 versus 0.171, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is TSG Hoffenheim; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Borussia Monchengladbach approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

TSG Hoffenheim approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 31% to Borussia Monchengladbach, 27% to a draw and 42% to TSG Hoffenheim. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

DEPORTIVO DE LA CORUNA vs LEVANTE

PRE-MATCH ANALYTICAL INTELLIGENCE | 16 OCT 2026 | 23:00 | XG-database only

Executive assessment: Levante lead the recorded squad attacking xG per 90 player-minutes (0.137 versus 0.153, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Deportivo de La Coruna; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Deportivo de La Coruna approach: Emphasise chance generation from the midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Levante approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 37% to Deportivo de La Coruna, 27% to a draw and 36% to Levante. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

RCD ESPANYOL vs ATLETICO MADRID

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 16:00 | XG-database only

Executive assessment: Atletico Madrid lead the recorded squad attacking xG per 90 player-minutes (0.166 versus 0.199, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Atletico Madrid; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

RCD Espanyol approach: Emphasise chance generation from the forward group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Atletico Madrid approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 35% to RCD Espanyol, 27% to a draw and 38% to Atletico Madrid. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

VILLARREAL CF vs ELCHE

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 18:15 | XG-database only

Executive assessment: Villarreal CF lead the recorded squad attacking xG per 90 player-minutes (0.260 versus 0.137, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Villarreal CF; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Villarreal CF approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Elche approach: Use the forward group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 45% to Villarreal CF, 27% to a draw and 28% to Elche. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

REAL BETIS vs FC BARCELONA

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 20:30 | XG-database only

Executive assessment: FC Barcelona lead the recorded squad attacking xG per 90 player-minutes (0.214 versus 0.429, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is FC Barcelona; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Real Betis approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

FC Barcelona approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 28% to Real Betis, 27% to a draw and 45% to FC Barcelona. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

VALENCIA CF vs ATHLETIC BILBAO

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 23:00 | XG-database only

Executive assessment: Athletic Bilbao lead the recorded squad attacking xG per 90 player-minutes (0.110 versus 0.182, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Athletic Bilbao; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Valencia CF approach: Emphasise chance generation from the midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Athletic Bilbao approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 33% to Valencia CF, 27% to a draw and 40% to Athletic Bilbao. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

OSASUNA vs RACING SANTANDER

PRE-MATCH ANALYTICAL INTELLIGENCE | 18 OCT 2026 | 16:00 | XG-database only

Executive assessment: Racing Santander lead the recorded squad attacking xG per 90 player-minutes (0.171 versus 0.176, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Osasuna; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Osasuna approach: Emphasise chance generation from the forward group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Racing Santander approach: Use the forward group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 37% to Osasuna, 27% to a draw and 36% to Racing Santander. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

CELTA DE VIGO vs DEPORTIVO ALAVES

PRE-MATCH ANALYTICAL INTELLIGENCE | 18 OCT 2026 | 18:15 | XG-database only

Executive assessment: Deportivo Alaves lead the recorded squad attacking xG per 90 player-minutes (0.113 versus 0.157, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Deportivo Alaves; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Celta de Vigo approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Deportivo Alaves approach: Use the forward group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 35% to Celta de Vigo, 27% to a draw and 38% to Deportivo Alaves. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

MALAGA CF vs REAL SOCIEDAD

PRE-MATCH ANALYTICAL INTELLIGENCE | 18 OCT 2026 | 20:30 | XG-database only

Executive assessment: Real Sociedad lead the recorded squad attacking xG per 90 player-minutes (0.086 versus 0.167, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Real Sociedad; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Malaga CF approach: Emphasise chance generation from the forward group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Real Sociedad approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 33% to Malaga CF, 27% to a draw and 40% to Real Sociedad. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

REAL MADRID vs SEVILLA FC

PRE-MATCH ANALYTICAL INTELLIGENCE | 18 OCT 2026 | 23:00 | XG-database only

Executive assessment: Real Madrid lead the recorded squad attacking xG per 90 player-minutes (0.303 versus 0.111, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Real Madrid; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Real Madrid approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Sevilla FC approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 49% to Real Madrid, 27% to a draw and 24% to Sevilla FC. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

GETAFE vs RAYO VALLECANO

PRE-MATCH ANALYTICAL INTELLIGENCE | 19 OCT 2026 | 23:00 | XG-database only

Executive assessment: Rayo Vallecano lead the recorded squad attacking xG per 90 player-minutes (0.113 versus 0.170, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Rayo Vallecano; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Getafe approach: Emphasise chance generation from the midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Rayo Vallecano approach: Use the forward group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 35% to Getafe, 27% to a draw and 38% to Rayo Vallecano. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

FROSINONE vs SASSUOLO

PRE-MATCH ANALYTICAL INTELLIGENCE | 16 OCT 2026 | 22:45 | XG-database only

Executive assessment: Sassuolo lead the recorded squad attacking xG per 90 player-minutes (0.180 versus 0.229, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Frosinone; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Frosinone approach: Emphasise chance generation from the forward group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Sassuolo approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 38% to Frosinone, 27% to a draw and 35% to Sassuolo. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

VENEZIA vs NAPOLI

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 17:00 | XG-database only

Executive assessment: Venezia lead the recorded squad attacking xG per 90 player-minutes (0.230 versus 0.148, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Venezia; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Venezia approach: Emphasise chance generation from the defense group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Napoli approach: Use the midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 41% to Venezia, 27% to a draw and 32% to Napoli. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

BOLOGNA vs INTER MILAN

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 20:00 | XG-database only

Executive assessment: Inter Milan lead the recorded squad attacking xG per 90 player-minutes (0.158 versus 0.332, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Inter Milan; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

Bologna approach: Emphasise chance generation from the forward group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Inter Milan approach: Use the forward group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 30% to Bologna, 27% to a draw and 43% to Inter Milan. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

AS ROMA vs GENOA

PRE-MATCH ANALYTICAL INTELLIGENCE | 17 OCT 2026 | 22:45 | XG-database only

Executive assessment: AS Roma lead the recorded squad attacking xG per 90 player-minutes (0.322 versus 0.123, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is AS Roma; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution

ANALYTICAL FINDING | Goals minus xG describes recorded finishing relative to chance quality, not a reliable forecast of future conversion. The sheet does not identify starters or substitutes.

05 | Match-phase dynamics and data availability

The XG-database worksheet contains no match dates, half-time results, first-half/second-half shots, starter changes or substitute-minute classifications. These components of the reference template cannot be calculated from the authorised sheet and are therefore intentionally not inferred.

06 | Shooting efficiency and attacking output

ANALYTICAL FINDING | Shots on target and key passes are not columns in the XG-database worksheet. Shot quality (xG per shot) is available, but cannot establish shot accuracy.

07 | Players to watch by tactical line

ANALYTICAL FINDING | Candidates are selected using attacking xG and rating among the listed players, not confirmed match selection or fitness.

08 | Potential match strategies: strengths and vulnerabilities

AS Roma approach: Emphasise chance generation from the attacking midfield group, which contributes the largest share of the home team’s recorded positional attacking xG. Prioritise good shot locations and guard against turnovers when committing attacking players.

Genoa approach: Use the attacking midfield group’s recorded xG contribution as a reference for attacking combinations. Limit the opponent’s highest-xG unit’s access to central shooting areas, while seeking efficient counterattacks.

ANALYTICAL FINDING | These are scenario-based tactical suggestions drawn from player xG distributions, not observed formations, pressing metrics or verified coaching instructions.

Overall analytical judgment

The model allocates 51% to AS Roma, 27% to a draw and 22% to Genoa. The comparison is informed by the available player-level attacking xG, xG per 90 player-minutes, shot quality and player ratings. Confidence is limited: there are no venue-specific statistics, defensive xGA, match-phase measures or confirmed lineups in the authorised worksheet. No projected score is provided.

DATA SOURCE | Supplied POWER V15(4) workbook, XG-database worksheet only. No other worksheet or external data used.

UDINESE vs LECCE

PRE-MATCH ANALYTICAL INTELLIGENCE | 18 OCT 2026 | 14:30 | XG-database only

Executive assessment: Lecce lead the recorded squad attacking xG per 90 player-minutes (0.143 versus 0.149, home then away). This is an exposure-normalised comparison of listed player contributions, not a home/away match split or a defensive xGA assessment. Player availability and match lineups are not confirmed.

01 | Outcome probability assessment

Directional heuristic estimates use squad attacking xG per 90 player-minutes, minutes-weighted player ratings, shot quality and a small assumed home adjustment. They are not calibrated match probabilities.

ANALYTICAL FINDING | The indicative preference is Udinese; the model is limited by absent defensive xGA, venue splits and confirmed lineups.

02 | Functional strength: player-rating comparison

ANALYTICAL FINDING | Ratings are minutes-weighted averages within the workbook’s Position Group labels; they do not measure expected goals conceded or guarantee that players will start.

03 | Overall attacking xG: player-squad comparison

ANALYTICAL FINDING | Totals reflect different numbers of players and minutes; per-90 player-minute rates offer an exposure check, but are not team xG per match or venue-specific xG.

03A | Positional xG contribution — XG-database

Values in parentheses are player counts. Defender xG is attacking xG contributed by players classified as defenders; it is not defensive xGA.

04 | Exposure and finishing contribution