Serie A · Italy

TorinovAC Milan

Sunday 23 August at 19:45Stadio Olimpico Grande Torinolineups not announced

Referee

Luca Zufferli

33 matches on record

Fouls per game

23.8

+3% vs league

League average

23.2

fouls per match, both teams

Value

No edges published on this fixture. An edge is published only when a bookmaker's price beats the model's fair price by that market's full bar — most fixtures never produce one. The value board explains every gate a candidate has to clear.

What these numbers are

Not tips and not prices. Each row is the model's expected count for one player in this match — how many fouls, tackles or shots it thinks he records — plus the full spread of outcomes around it. Nothing here has been compared to a bookmaker.

Step 1
His own record
Every completed match in the dataset, as a rate per 90 minutes. The n column is how many matches that rests on.
Step 2
Pulled toward his position
A thin record gets pulled hard toward other players in his position, in his league — a goalkeeper toward goalkeepers, not toward the outfielders around him. How hard is fitted per market, not chosen: tackles pull about four times harder than shots on target.
Step 3
This fixture's conditions
How much of the stat the opponent concedes, what the referee's matches look like, and home or away. This is where a projection stops being a season average.
Step 4
Scaled to expected minutes
A rate becomes a count only once you say how long he plays. 60 minutes carries two-thirds the exposure of 90, and the distribution is built at that exposure.

How to read each column

Model /90: The model's rate for this match with the minutes taken back out — steps 1 to 3 already applied. It moves with the opponent and the referee, so it is not his raw career rate; the builder shows career and model rates side by side.
Exp. mins: Minutes the model expects. Confirmed means the lineup is out; provisional means it is guessing from his start rate, and is the widest of the three.
Projected: The expected count in this match, at those minutes. This is the number a line is set against.
Over 1.5, etc.: Read straight off the distribution beside it, not off how often he has beaten that line before. It answers what the model thinks, not what has happened.
n: Matches behind his own rate. Under 30 it turns amber: the projection is mostly his position group speaking, and §6.3 will not publish an edge on it.
Distribution: The whole spread, not just the average. The dashed amber cut is the line; jade bars beat it. An expected 1.8 fouls made of 2 every week and an expected 1.8 made of a 0 and a 5 are different bets, and this is where you see which one you have.

Counts are modelled as negative binomial rather than Poisson, because fouls and tackles are overdispersed and a Poisson would systematically underprice the tails — which is exactly where over bets live. Every market on this page cleared its calibration gate before it was allowed to produce a projection: when the model says 60%, it lands within a point or so of 60% out of sample.

Fouls v20260816-1555 · Shots v20260816-1555 · Shots on target v20260816-1555 · Fouls won v20260816-1555 · Saves v20260816-1229

Model projections

Fouls52 playersHighest: Saúl Coco, 1.21 expectedshow

What drives it — Who referees the match. A strict official lifts every player on the pitch, which is the part most books price off a season average. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 1.5	n	Distribution
Saúl CocoDEF	Torino	1.23	88provisional	1.21	34%	67	030% 136% 221% 39% 43% 51% 6+0%
Gvidas GineitisMID	Torino	1.57	61provisional	1.18	33%	59	033% 134% 220% 39% 43% 51% 6+0%
Warren BondoMID	AC Milan	1.53	62provisional	1.15	32%	51	034% 134% 220% 38% 43% 51% 6+0%
Adrien RabiotMID	AC Milan	1.12	87provisional	1.09	30%	29	034% 136% 220% 37% 42% 50% 6+0%
Valentino LazaroMID	Torino	1.23	75provisional	1.07	29%	64	035% 135% 219% 37% 42% 51% 6+0%
Cesare CasadeiMID	Torino	1.70	47provisional	1.04	28%	48	039% 134% 217% 37% 42% 51% 6+0%
Nikola VlašićMID	Torino	1.14	79provisional	1.03	28%	67	036% 136% 219% 37% 42% 5+1%
Pietro PellegriFWD	—	1.52	53provisional	1.02	27%	11	039% 134% 218% 37% 42% 51% 6+0%
Koni De WinterDEF	AC Milan	1.22	67provisional	0.97	26%	51	041% 133% 217% 36% 42% 50% 6+0%
Fikayo TomoriDEF	AC Milan	1.07	78provisional	0.96	25%	55	039% 136% 217% 36% 42% 5+0%

10 of 52 players shown, ranked by projection. Show all 52 →

Shots52 playersHighest: Giovanni Simeone, 1.90 expectedshow

What drives it — The player’s own shot rate, shrunk toward others in his position, then adjusted for how many shots the opponent concedes. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 1.5	n	Distribution
Giovanni SimeoneFWD	Torino	2.82	57provisional	1.90	51%	62	023% 125% 220% 314% 49% 55% 6+4%
Duván ZapataFWD	Torino	2.50	59provisional	1.76	49%	35	023% 128% 222% 314% 48% 53% 6+2%
Rafael LeãoFWD	AC Milan	2.43	61provisional	1.75	49%	63	022% 129% 223% 314% 47% 53% 6+2%
Santiago GimenezFWD	AC Milan	2.24	60provisional	1.61	46%	30	024% 130% 223% 313% 46% 53% 6+1%
Ché AdamsFWD	Torino	2.15	51provisional	1.34	37%	69	031% 132% 220% 310% 44% 52% 6+1%
Adrien RabiotMID	AC Milan	1.37	87provisional	1.33	38%	29	028% 134% 222% 310% 44% 51% 6+0%
Nikola VlašićMID	Torino	1.47	79provisional	1.32	38%	67	029% 134% 222% 310% 44% 51% 6+0%
Pietro PellegriFWD	—	2.05	53provisional	1.31	37%	11	032% 131% 220% 310% 44% 52% 6+1%
Christian PulisicFWD	AC Milan	2.22	47provisional	1.29	35%	64	034% 131% 218% 39% 44% 52% 6+1%
Christopher NkunkuFWD	AC Milan	1.85	53provisional	1.17	32%	59	037% 131% 218% 39% 44% 51% 6+1%

10 of 52 players shown, ranked by projection. Show all 52 →

Shots on target50 playersHighest: Duván Zapata, 0.73 expectedshow

What drives it — Shot volume first, conversion second — literally: the projection is the shots model thinned by the player’s own on-target rate, so a high-volume low-accuracy shooter and a sniper price differently at the same shot count. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 0.5	n	Distribution
Duván ZapataFWD	Torino	1.04	59provisional	0.73	49%	35	051% 132% 213% 34% 41% 5+0%
Rafael LeãoFWD	AC Milan	0.99	61provisional	0.71	49%	63	051% 132% 212% 33% 41% 5+0%
Giovanni SimeoneFWD	Torino	1.01	57provisional	0.68	46%	62	054% 130% 212% 33% 41% 5+0%
Santiago GimenezFWD	AC Milan	0.84	60provisional	0.60	44%	30	056% 131% 210% 32% 4+1%
Christian PulisicFWD	AC Milan	0.93	47provisional	0.54	39%	64	061% 128% 29% 32% 40% 5+0%
Christopher NkunkuFWD	AC Milan	0.82	53provisional	0.52	38%	59	062% 128% 28% 32% 4+0%
Ché AdamsFWD	Torino	0.81	51provisional	0.50	38%	69	062% 128% 28% 32% 4+0%
Pietro PellegriFWD	—	0.75	53provisional	0.48	37%	11	063% 127% 27% 32% 4+0%
Nikola VlašićMID	Torino	0.52	79provisional	0.47	37%	67	063% 128% 27% 31% 4+0%
Gaetano OristanioMID	—	0.70	44provisional	0.39	31%	57	069% 125% 25% 31% 4+0%
Adrien RabiotMID	AC Milan	0.38	87provisional	0.37	30%	29	070% 125% 25% 3+1%
Cesare CasadeiMID	Torino	0.57	47provisional	0.33	27%	48	073% 122% 24% 31% 4+0%
Youssouf FofanaMID	AC Milan	0.39	73provisional	0.33	27%	68	073% 123% 24% 3+1%
Samuel ChukwuezeFWD	AC Milan	0.60	43provisional	0.32	26%	50	074% 121% 24% 31% 4+0%
Alexis SaelemaekersMID	AC Milan	0.34	76provisional	0.29	25%	58	075% 121% 23% 3+0%
Gvidas GineitisMID	Torino	0.38	61provisional	0.28	24%	59	076% 120% 23% 3+0%
Zakaria AboukhlalFWD	Torino	0.52	40provisional	0.27	22%	15	078% 119% 23% 3+0%
Alieu NjieFWD	Torino	0.78	22provisional	0.25	22%	31	078% 119% 23% 3+0%
Emirhan İlkhanMID	Torino	0.33	61provisional	0.24	21%	19	079% 118% 22% 3+0%
Francesco CamardaFWD	AC Milan	0.65	26provisional	0.23	20%	31	080% 117% 22% 3+0%
Sandro KulenovićFWD	Torino	0.70	22provisional	0.22	19%	13	081% 116% 22% 3+0%
Ruben Loftus-CheekMID	AC Milan	0.37	47provisional	0.21	19%	47	081% 116% 22% 3+0%
Strahinja PavlovićDEF	AC Milan	0.23	83provisional	0.21	19%	58	081% 117% 22% 3+0%
Davide BartesaghiDEF	AC Milan	0.23	77provisional	0.20	18%	35	082% 116% 22% 3+0%
Samuele RicciMID	AC Milan	0.26	58provisional	0.18	16%	65	084% 114% 22% 3+0%
Luka ModrićMID	AC Milan	0.25	61provisional	0.18	16%	69	084% 114% 22% 3+0%
Guillermo MaripánDEF	Torino	0.22	70provisional	0.18	16%	55	084% 114% 21% 3+0%
Eray CömertDEF	—	0.19	78provisional	0.17	15%	42	085% 114% 2+1%
Tino AnjorinMID	Torino	0.41	30provisional	0.17	15%	37	085% 113% 21% 3+0%
Ardon JashariMID	AC Milan	0.23	61provisional	0.17	15%	14	085% 114% 21% 3+0%
Zachary AthekameDEF	AC Milan	0.35	37provisional	0.17	15%	27	085% 113% 21% 3+0%
Yunus MusahMID	AC Milan	0.27	46provisional	0.15	14%	49	086% 113% 21% 3+0%
Pervis EstupiñánDEF	AC Milan	0.20	62provisional	0.15	13%	49	087% 112% 2+1%
Marcus PedersenDEF	Torino	0.18	68provisional	0.14	13%	58	087% 112% 2+1%
Warren BondoMID	AC Milan	0.18	62provisional	0.13	12%	51	088% 111% 2+1%
Saúl CocoDEF	Torino	0.13	88provisional	0.13	12%	67	088% 111% 2+1%
Matteo GabbiaDEF	AC Milan	0.13	85provisional	0.13	12%	56	088% 111% 2+1%
Valentino LazaroMID	Torino	0.14	75provisional	0.12	11%	64	089% 111% 2+1%
Ali DembéléDEF	Torino	0.36	23provisional	0.12	11%	17	089% 110% 2+1%
Mario GilaDEF	—	0.11	83provisional	0.11	10%	63	090% 110% 2+1%
Niels NkounkouDEF	Torino	0.28	27provisional	0.10	9%	23	091% 19% 2+1%
Filippo TerraccianoDEF	AC Milan	0.11	78provisional	0.09	9%	49	091% 18% 2+0%
Ivan IlićMID	Torino	0.18	39provisional	0.09	8%	27	092% 18% 2+0%
Pietro ComuzzoDEF	—	0.13	59provisional	0.09	8%	60	092% 18% 2+0%
Ardian IsmajliDEF	Torino	0.09	83provisional	0.09	8%	54	092% 18% 2+0%
Koni De WinterDEF	AC Milan	0.10	67provisional	0.08	7%	51	093% 17% 2+0%
Cristiano BiraghiDEF	Torino	0.15	40provisional	0.07	7%	37	093% 16% 2+0%
Adrien TamèzeMID	Torino	0.16	31provisional	0.07	6%	44	094% 16% 2+0%
Fikayo TomoriDEF	AC Milan	0.07	78provisional	0.06	6%	55	094% 16% 2+0%
Adam MasinaDEF	Torino	0.11	46provisional	0.06	6%	33	094% 16% 2+0%

All 50 players shown, ranked by projection. Show fewer ↥

Fouls won52 playersHighest: Adrien Rabiot, 1.81 expectedshow

What drives it — How much a player runs at defenders. Dribble volume drives this far more than the referee does. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 1.5	n	Distribution
Adrien RabiotMID	AC Milan	1.87	87provisional	1.81	53%	29	018% 129% 225% 316% 47% 53% 6+1%
Alexis SaelemaekersMID	AC Milan	1.84	76provisional	1.59	46%	58	023% 131% 224% 313% 46% 52% 6+1%
Samuele RicciMID	AC Milan	2.19	58provisional	1.49	41%	65	029% 129% 220% 312% 46% 53% 6+1%
Warren BondoMID	AC Milan	1.73	62provisional	1.24	35%	51	033% 132% 220% 39% 44% 51% 6+0%
Rafael LeãoFWD	AC Milan	1.68	61provisional	1.20	33%	63	034% 133% 219% 39% 43% 51% 6+0%
Duván ZapataFWD	Torino	1.50	59provisional	1.04	28%	35	039% 133% 218% 37% 42% 51% 6+0%
Nikola VlašićMID	Torino	1.14	79provisional	1.03	27%	67	037% 135% 218% 37% 42% 50% 6+0%
Gaetano OristanioMID	—	1.85	44provisional	1.01	26%	57	040% 133% 216% 37% 42% 51% 6+0%
Yunus MusahMID	AC Milan	1.79	46provisional	1.00	26%	49	042% 131% 216% 37% 43% 51% 6+0%
Santiago GimenezFWD	AC Milan	1.38	60provisional	0.97	26%	30	040% 134% 217% 36% 42% 50% 6+0%

10 of 52 players shown, ranked by projection. Show all 52 →

Saves2 playersHighest: Mike Maignan, 3.03 expectedshow

What drives it — Opponent shot volume. A keeper’s own record carries so little that this market shrinks harder than any other on the board. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 2.5	n	Distribution
Mike MaignanGK	AC Milan	3.07	88provisional	3.03	56%	74	07% 116% 221% 320% 415% 510% 6+11%
Alberto PaleariGK	Torino	2.61	88provisional	2.58	46%	30	010% 120% 224% 320% 413% 57% 6+6%

2 of 7 markets have no projection for this fixture.