Head to head
J. Neves vs K. Kvaratskhelia
Two transparent 100-point cases. The same methodology, compared component by component.
Real-data provisional ranking
Every displayed component is computed from current API-Football fixture, event, player-stat, standings, and pre-match Elo evidence. The ranking remains provisional—not illustrative—until the locked 2024–2025 historical holdout gate is complete.
Rank #12
João Neves
Paris Saint Germain · Midfielder
Rank #1
Khvicha Kvaratskhelia
Paris Saint Germain · Forward
Compare the evidence
J. Neves
Role output is the 72nd role-cohort percentile from 4 disclosed metric families (100% weight coverage).
weighted mean of position-specific metric percentiles; raw action rates use frozen pre-match field-strength adjustment and ratios use empirical-Bayes shrinkage
K. Kvaratskhelia
Role output is the 95th role-cohort percentile from 4 disclosed metric families (100% weight coverage).
weighted mean of position-specific metric percentiles; raw action rates use frozen pre-match field-strength adjustment and ratios use empirical-Bayes shrinkage
Compare the evidence
J. Neves
Creation & progression is the 66th role-cohort percentile from 4 disclosed metric families (100% weight coverage).
weighted mean of position-specific metric percentiles; raw action rates use frozen pre-match field-strength adjustment and ratios use empirical-Bayes shrinkage
K. Kvaratskhelia
Creation & progression is the 95th role-cohort percentile from 4 disclosed metric families (100% weight coverage).
weighted mean of position-specific metric percentiles; raw action rates use frozen pre-match field-strength adjustment and ratios use empirical-Bayes shrinkage
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J. Neves
All-round role contribution is the 78th role-cohort percentile from 4 disclosed metric families (100% weight coverage).
weighted mean of position-specific metric percentiles; raw action rates use frozen pre-match field-strength adjustment and ratios use empirical-Bayes shrinkage
K. Kvaratskhelia
All-round role contribution is the 84th role-cohort percentile from 4 disclosed metric families (100% weight coverage).
weighted mean of position-specific metric percentiles; raw action rates use frozen pre-match field-strength adjustment and ratios use empirical-Bayes shrinkage
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J. Neves
Efficiency & execution is the 78th role-cohort percentile from 4 disclosed metric families (100% weight coverage).
weighted mean of position-specific metric percentiles; raw action rates use frozen pre-match field-strength adjustment and ratios use empirical-Bayes shrinkage
K. Kvaratskhelia
Efficiency & execution is the 83rd role-cohort percentile from 4 disclosed metric families (100% weight coverage).
weighted mean of position-specific metric percentiles; raw action rates use frozen pre-match field-strength adjustment and ratios use empirical-Bayes shrinkage
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J. Neves
Availability combines 2883 minutes (55% of team opportunity), 41 appearances, and 65% smooth consistency credit.
60% minutes share + 15% appearance share + 10% start share + 15% smooth 30+ minute match-impact consistency
K. Kvaratskhelia
Availability combines 2687 minutes (56% of team opportunity), 45 appearances, and 62% smooth consistency credit.
60% minutes share + 15% appearance share + 10% start share + 15% smooth 30+ minute match-impact consistency
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J. Neves
Against opponents at or above the 75th pre-match Elo percentile: 17 appearances, 1355 minutes, and 57th role-impact percentile.
80% minutes-weighted role impact + 20% capped 900-minute volume
K. Kvaratskhelia
Against opponents at or above the 75th pre-match Elo percentile: 20 appearances, 1325 minutes, and 57th role-impact percentile.
80% minutes-weighted role impact + 20% capped 900-minute volume
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J. Neves
Knockout credit uses 11 appearances and 975 minutes, weighted by both stage and competition prestige.
75% stage-, prestige-, and minutes-weighted role impact + 25% capped 900-minute prestige volume
K. Kvaratskhelia
Knockout credit uses 10 appearances and 761 minutes, weighted by both stage and competition prestige.
75% stage-, prestige-, and minutes-weighted role impact + 25% capped 900-minute prestige volume
Compare the evidence
J. Neves
Match-state events produce 6.21 leverage units from 12 goal/assist/penalty events; untimed role actions in high-uncertainty fixtures add a 84th-percentile proxy.
80% expected-points-added goal/assist leverage (60% volume, 40% rate) + 20% position-specific high-uncertainty action proxy
K. Kvaratskhelia
Match-state events produce 14.81 leverage units from 28 goal/assist/penalty events; untimed role actions in high-uncertainty fixtures add a 94th-percentile proxy.
80% expected-points-added goal/assist leverage (60% volume, 40% rate) + 20% position-specific high-uncertainty action proxy
Compare the evidence
J. Neves
Team credit: UEFA Champions League winner (1.30 credit); Ligue 1 winner (0.43 credit); FIFA World Cup round of 16 (0.09 credit). Diminishing-return evidence is 1.59 against the disclosed 2.00 ceiling.
finish × prestige × route × participation × importance; credits then receive 1.0/0.6/0.3/0.1 diminishing weights
K. Kvaratskhelia
Team credit: UEFA Champions League winner (1.27 credit); Ligue 1 winner (0.46 credit). Diminishing-return evidence is 1.54 against the disclosed 2.00 ceiling.
finish × prestige × route × participation × importance; credits then receive 1.0/0.6/0.3/0.1 diminishing weights