Serie A · Italy

AC MilanvVenezia

Friday 28 August at 19:45Stadio Giuseppe Meazzalineups not announced

Referee

Not appointed

0 matches on record

Fouls per game

—

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 v20260815-1512 · Tackles v20260815-1512 · Shots v20260815-1512 · Fouls won v20260815-1512 · Cards v20260815-1512 · Saves v20260815-1512

Model projections

Fouls48 playersHighest: Alessio Zerbin, 1.63 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
Alessio ZerbinMID	Venezianow at Frosinone	1.74	84provisional	1.63	48%	17	022% 130% 225% 314% 46% 52% 6+1%
Kike PérezMID	Venezia	2.08	70provisional	1.62	47%	13	024% 130% 223% 314% 46% 52% 6+1%
Hans Nicolussi CavigliaMID	Venezianow at Parma	1.50	82provisional	1.37	39%	33	027% 134% 223% 311% 44% 51% 6+0%
Jay IdzesDEF	Venezia	1.36	89provisional	1.35	39%	35	026% 135% 223% 311% 44% 51% 6+0%
Gaetano OristanioMID	Venezianow at Torino	1.89	63provisional	1.32	38%	32	029% 133% 222% 310% 44% 51% 6+0%
Fali CandéDEF	Venezia	1.30	90provisional	1.30	37%	17	028% 135% 223% 310% 43% 51% 6+0%
Yunus MusahMID	AC Milan	2.03	56provisional	1.26	35%	21	034% 131% 219% 310% 44% 51% 6+1%
Alfred DuncanMID	Venezia	1.89	60provisional	1.26	36%	12	036% 128% 219% 310% 44% 51% 6+1%
Adrien RabiotMID	AC Milan	1.27	88provisional	1.24	35%	29	030% 135% 222% 39% 43% 51% 6+0%
Daniel FilaFWD	Venezia	2.08	50provisional	1.14	31%	7	037% 131% 218% 39% 43% 51% 6+0%
Ruben Loftus-CheekMID	AC Milan	2.10	46provisional	1.07	29%	26	042% 129% 216% 38% 43% 51% 6+1%
Francesco ZampanoMID	Venezia	1.35	68provisional	1.02	28%	19	040% 132% 217% 37% 42% 51% 6+0%
Koni De WinterDEF	AC Milan	1.33	69provisional	1.02	28%	21	041% 131% 217% 37% 42% 51% 6+0%
Antonio CandelaDEF	Venezia	1.27	72provisional	1.02	27%	13	038% 134% 218% 37% 42% 50% 6+0%
Gianluca BusioMID	Venezia	1.07	77provisional	0.91	23%	31	042% 134% 216% 35% 41% 5+0%
Strahinja PavlovićDEF	AC Milan	0.96	82provisional	0.87	22%	54	043% 135% 216% 35% 41% 5+0%
Pervis EstupiñánDEF	AC Milan	1.44	55provisional	0.87	23%	14	048% 129% 215% 36% 42% 50% 6+0%
Fikayo TomoriDEF	AC Milan	1.02	76provisional	0.86	22%	48	044% 134% 216% 35% 41% 5+0%
Matteo GabbiaDEF	AC Milan	0.93	84provisional	0.86	22%	53	043% 135% 216% 35% 41% 5+0%
Luka ModrićMID	AC Milan	0.92	83provisional	0.84	21%	32	044% 135% 215% 35% 41% 5+0%
Giorgio AltareDEF	Venezia	1.21	63provisional	0.84	21%	9	046% 133% 215% 35% 41% 5+0%
Joel PohjanpaloFWD	Venezia	0.92	81provisional	0.83	20%	19	044% 135% 215% 34% 41% 5+0%
Youssouf FofanaMID	AC Milan	1.05	70provisional	0.81	20%	61	046% 134% 214% 34% 41% 5+0%
Alexis SaelemaekersMID	AC Milan	0.90	80provisional	0.80	19%	35	046% 135% 214% 34% 41% 5+0%
Issa DoumbiaMID	Venezia	1.79	39provisional	0.78	20%	11	052% 128% 212% 35% 42% 51% 6+0%
Santiago GimenezFWD	AC Milan	1.28	52provisional	0.74	18%	21	050% 132% 213% 34% 41% 5+0%
Mikael Egill EllertssonMID	Venezia	0.97	69provisional	0.74	18%	30	049% 133% 213% 34% 41% 5+0%
Ardon JashariMID	AC Milan	1.33	50provisional	0.74	18%	8	052% 130% 212% 34% 41% 5+0%
Filippo TerraccianoDEF	AC Milan	1.60	41provisional	0.73	20%	6	060% 120% 211% 36% 42% 51% 6+0%
Magnus Kofod AndersenMID	Venezia	1.32	49provisional	0.72	18%	7	053% 129% 212% 34% 41% 5+0%
Marin ŠverkoDEF	Venezia	0.93	70provisional	0.72	17%	13	051% 132% 213% 34% 41% 5+0%
Michael SvobodaDEF	Venezianow at Brighton & Hove Albion	0.75	82provisional	0.68	15%	15	051% 133% 212% 33% 4+1%
Joël SchingtienneDEF	Venezia	0.86	70provisional	0.67	15%	14	053% 131% 211% 33% 41% 5+0%
Zachary AthekameDEF	AC Milan	1.94	30provisional	0.66	15%	12	057% 128% 210% 33% 41% 50% 6+0%
Rafael LeãoFWD	AC Milan	0.88	67provisional	0.65	14%	54	053% 132% 211% 33% 41% 5+0%
Davide BartesaghiDEF	AC Milan	0.79	73provisional	0.64	14%	32	054% 132% 211% 33% 4+1%
Ridgeciano HapsDEF	Venezia	1.05	55provisional	0.64	15%	17	056% 130% 211% 33% 41% 5+0%
Christian PulisicFWD	AC Milan	0.85	64provisional	0.61	13%	50	056% 130% 210% 33% 4+1%
Francesco CamardaFWD	AC Milan	2.42	21provisional	0.57	12%	2	060% 128% 28% 32% 41% 50% 6+0%
Mirko MaricFWD	Venezia	1.44	35provisional	0.57	13%	5	062% 125% 29% 33% 41% 5+0%
Christian GytkjaerFWD	Venezia	1.71	26provisional	0.50	11%	7	065% 124% 27% 32% 41% 5+0%
Samuele RicciMID	AC Milan	1.06	42provisional	0.49	10%	12	064% 125% 28% 32% 40% 5+0%
John YeboahFWD	Venezia	1.12	37provisional	0.46	9%	12	066% 125% 27% 32% 4+0%
Christopher NkunkuFWD	AC Milan	0.97	42provisional	0.46	9%	17	066% 125% 27% 32% 4+0%
Samuel ChukwuezeFWD	AC Milan	0.81	35provisional	0.32	5%	12	075% 120% 24% 31% 4+0%
Mike MaignanGK	AC Milan	0.02	89provisional	0.02	—	74	098% 1+2%
Ionuț RaduGK	Venezianow at Celta de Vigo	0.01	90provisional	0.01	—	15	099% 1+1%
Filip StankovićGK	Venezia	0.01	86provisional	0.01	—	15	099% 1+1%

All 48 players shown, ranked by projection. Show fewer ↥ 5 of the 48 have since left the club — the squad is built from who has played for these teams, not from who is registered today, so they are shown rather than quietly dropped.

Tackles48 playersHighest: Alessio Zerbin, 1.25 expectedshow

What drives it — Possession share. A tackle count depends far more on how much of the match is played at your own end than on a player’s own form. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 1.5	n	Distribution
Alessio ZerbinMID	Venezianow at Frosinone	1.34	84provisional	1.25	35%	17	033% 132% 220% 39% 44% 51% 6+1%
Kike PérezMID	Venezia	1.53	70provisional	1.19	33%	13	035% 132% 219% 39% 43% 51% 6+1%
Antonio CandelaDEF	Venezia	1.39	72provisional	1.11	30%	13	037% 132% 218% 38% 43% 51% 6+0%
Fikayo TomoriDEF	AC Milan	1.32	76provisional	1.11	30%	48	037% 132% 218% 38% 43% 51% 6+0%
Fali CandéDEF	Venezia	1.01	90provisional	1.01	27%	17	039% 135% 218% 37% 42% 51% 6+0%
Alexis SaelemaekersMID	AC Milan	1.13	80provisional	1.00	27%	35	039% 134% 217% 37% 42% 51% 6+0%
Davide BartesaghiDEF	AC Milan	1.22	73provisional	1.00	26%	32	042% 132% 216% 37% 42% 51% 6+0%
Strahinja PavlovićDEF	AC Milan	1.09	82provisional	0.99	26%	54	041% 133% 217% 36% 42% 51% 6+0%
Adrien RabiotMID	AC Milan	1.00	88provisional	0.98	26%	29	040% 134% 217% 36% 42% 51% 6+0%
Joël SchingtienneDEF	Venezia	1.20	70provisional	0.94	25%	14	044% 131% 215% 36% 42% 51% 6+0%

10 of 48 players shown, ranked by projection. Show all 48 → 5 of the 48 have since left the club — the squad is built from who has played for these teams, not from who is registered today, so they are shown rather than quietly dropped.

Shots48 playersHighest: Rafael Leão, 2.42 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
Rafael LeãoFWD	AC Milan	3.27	67provisional	2.42	64%	54	014% 122% 222% 318% 412% 57% 6+6%
Santiago GimenezFWD	AC Milan	3.64	52provisional	2.11	56%	21	019% 125% 221% 315% 410% 55% 6+5%
Christian PulisicFWD	AC Milan	2.95	64provisional	2.10	57%	50	019% 124% 221% 316% 410% 55% 6+5%
Adrien RabiotMID	AC Milan	1.79	88provisional	1.75	51%	29	019% 130% 225% 315% 47% 53% 6+1%
Joel PohjanpaloFWD	Venezia	1.92	81provisional	1.73	50%	19	021% 129% 224% 315% 47% 53% 6+1%
Youssouf FofanaMID	AC Milan	1.87	70provisional	1.44	41%	61	027% 132% 222% 312% 45% 52% 6+1%
Samuel ChukwuezeFWD	AC Milan	3.64	35provisional	1.43	35%	12	037% 128% 215% 39% 45% 53% 6+3%
Christopher NkunkuFWD	AC Milan	2.99	42provisional	1.40	37%	17	036% 127% 216% 310% 46% 53% 6+2%
Alexis SaelemaekersMID	AC Milan	1.48	80provisional	1.32	38%	35	029% 134% 222% 310% 44% 51% 6+0%
Hans Nicolussi CavigliaMID	Venezianow at Parma	1.24	82provisional	1.13	31%	33	034% 135% 220% 38% 43% 51% 6+0%

Fouls won48 playersHighest: Adrien Rabiot, 1.89 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	1.93	88provisional	1.89	55%	29	017% 128% 225% 316% 48% 53% 6+2%
Alexis SaelemaekersMID	AC Milan	2.04	80provisional	1.82	53%	35	019% 129% 225% 315% 48% 53% 6+2%
Gaetano OristanioMID	Venezianow at Torino	2.50	63provisional	1.75	50%	32	021% 129% 223% 314% 47% 53% 6+2%
Rafael LeãoFWD	AC Milan	2.10	67provisional	1.55	44%	54	025% 130% 222% 313% 46% 52% 6+1%
Alessio ZerbinMID	Venezianow at Frosinone	1.56	84provisional	1.47	42%	17	026% 132% 223% 312% 45% 52% 6+1%
Gianluca BusioMID	Venezia	1.42	77provisional	1.21	34%	31	033% 133% 220% 39% 43% 51% 6+0%
Mikael Egill EllertssonMID	Venezia	1.43	69provisional	1.10	30%	30	037% 133% 218% 38% 43% 51% 6+0%
Luka ModrićMID	AC Milan	1.16	83provisional	1.07	29%	32	037% 134% 219% 37% 42% 51% 6+0%
Christian PulisicFWD	AC Milan	1.44	64provisional	1.03	28%	50	040% 132% 217% 37% 42% 51% 6+0%
Ruben Loftus-CheekMID	AC Milan	2.00	46provisional	1.02	27%	26	044% 129% 215% 37% 43% 51% 6+1%

Cards48 playersHighest: Kike Pérez, 0.21 expectedshow

Known defect — Prices ANY card — yellow, second yellow or straight red — matching how books settle "to be shown a card". The trends column counts the same thing.

What drives it — Fouls first, then how readily the referee reaches for a card. Two officials averaging four cards a match can do it for opposite reasons. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 0.5	n	Distribution
Kike PérezMID	Venezia	0.28	70provisional	0.21	19%	13	081% 117% 22% 3+0%
Alessio ZerbinMID	Venezianow at Frosinone	0.23	84provisional	0.21	19%	17	081% 117% 22% 3+0%
Fali CandéDEF	Venezia	0.21	90provisional	0.21	19%	17	081% 117% 22% 3+0%
Jay IdzesDEF	Venezia	0.18	89provisional	0.18	17%	35	083% 115% 2+1%
Adrien RabiotMID	AC Milan	0.18	88provisional	0.18	16%	29	084% 115% 2+1%
Hans Nicolussi CavigliaMID	Venezianow at Parma	0.19	82provisional	0.18	16%	33	084% 115% 2+1%
Yunus MusahMID	AC Milan	0.27	56provisional	0.17	15%	21	085% 114% 21% 3+0%
Pervis EstupiñánDEF	AC Milan	0.26	55provisional	0.16	14%	14	086% 113% 21% 3+0%
Antonio CandelaDEF	Venezia	0.19	72provisional	0.15	14%	13	086% 113% 2+1%
Fikayo TomoriDEF	AC Milan	0.18	76provisional	0.15	14%	48	086% 113% 2+1%

Saves3 playersHighest: Filip Stanković, 3.43 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
Filip StankovićGK	Venezia	3.60	86provisional	3.43	63%	15	05% 113% 219% 320% 417% 512% 6+15%
Ionuț RaduGK	Venezianow at Celta de Vigo	3.23	90provisional	3.23	60%	15	06% 114% 220% 320% 416% 511% 6+13%
Mike MaignanGK	AC Milan	2.43	89provisional	2.41	42%	74	011% 122% 224% 319% 412% 56% 6+5%

1 of the 3 have since left the club — the squad is built from who has played for these teams, not from who is registered today, so they are shown rather than quietly dropped.

1 of 7 markets have no projection for this fixture.