Pythia projects passes from how much of the ball each team is expected to have. Probabilities are model estimates, not guarantees. Not betting advice · 21+ · Gambling problem? Call 1-800-GAMBLER.

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1. Team form

   For every team, across every competition, an exponentially weighted read of passes made, passes conceded, possession, field tilt (share of opposition-half passes) and a PPDA proxy (opponent passes per defensive action). Recent matches count most.

2. Matchup → team passes & possession

   A log-linear model projects how many passes each side attempts in this fixture: my volume, what the opponent concedes, the opponent's own volume, what I concede, and home advantage. The two projections give expected possession.

3. Player share — and how the matchup shifts it

   Each player's share of his team's passes per 90, shrunk toward his position's typical share when the sample is small. The share then moves with the matchup, learned from past matches by position: centre-backs take a bigger slice when their team dominates the ball, keepers when the opponent presses high, forwards a smaller one in high-volume games.

4. Projection

   team passes × player share × expected minutes ÷ 90

5. Probability & edge

   P(More) comes from the real distribution of actual ÷ projected passes in past starts — so early subs, red cards and blowouts are priced in, not assumed away. Edge = projection vs line.