La Liga · Spain

Atlético de MadridvVillarreal

Sunday 23 August at 16:00Riyadh Air Metropolitanolineups not announced

Referee

Not appointed

0 matches on record

Fouls per game

—

League average

23.2

fouls per match, both teams

Angles

every priced line builder

opponentAtlético de Madrid concede 10.1 fouls a game — 22nd most of 23 in La Liga
Over their last 10. A hard place to get fouls.

Facts with sample sizes, not predictions. The market % beside a line is the books’ median price with margin in, and the over market runs hot.

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

Fouls51 playersHighest: Santiago Mouriño, 1.41 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
Santiago MouriñoDEF	Villarreal	1.52	82provisional	1.41	41%	54	026% 133% 223% 311% 44% 51% 6+0%
Carlos MartínFWD	Atlético de Madrid	1.93	57provisional	1.37	39%	38	028% 133% 222% 311% 44% 51% 6+0%
Johnny CardosoMID	Atlético de Madrid	1.71	62provisional	1.29	36%	43	031% 133% 221% 310% 44% 51% 6+0%
Rodrigo MendozaMID	Atlético de Madrid	1.68	59provisional	1.23	35%	25	031% 134% 221% 39% 43% 51% 6+0%
Cristian RomeroDEF	—	1.31	80provisional	1.21	34%	41	030% 136% 221% 39% 43% 51% 6+0%
Santi ComesañaMID	Villarreal	1.31	76provisional	1.14	32%	70	033% 135% 220% 38% 43% 51% 6+0%
Robin Le NormandDEF	Atlético de Madrid	1.13	76provisional	1.00	27%	56	038% 135% 218% 36% 42% 5+1%
Pape GueyeMID	Villarreal	1.16	73provisional	0.99	26%	65	038% 135% 218% 36% 42% 5+0%
Carlos RomeroDEF	Villarreal	1.03	83provisional	0.97	26%	71	038% 136% 218% 36% 42% 5+0%
Pau NavarroDEF	Villarreal	1.13	74provisional	0.97	26%	40	039% 136% 218% 36% 42% 5+0%

10 of 51 players shown, ranked by projection. Show all 51 →

Shots51 playersHighest: Ademola Lookman, 2.44 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
Ademola LookmanFWD	Atlético de Madrid	2.99	71provisional	2.44	67%	56	011% 122% 224% 319% 412% 57% 6+5%
Giacomo RaspadoriFWD	Atlético de Madrid	3.02	57provisional	2.04	54%	51	021% 125% 220% 315% 49% 55% 6+5%
Julián AlvarezFWD	Atlético de Madrid	2.72	61provisional	1.97	55%	66	018% 127% 223% 316% 49% 54% 6+3%
Antoine GriezmannFWD	Atlético de Madrid	2.49	63provisional	1.85	52%	72	020% 128% 223% 315% 48% 54% 6+2%
Alexander SørlothFWD	Atlético de Madrid	3.50	41provisional	1.83	50%	70	021% 129% 222% 313% 47% 54% 6+3%
Alejandro GrimaldoDEF	—	1.89	84provisional	1.79	52%	61	018% 129% 225% 315% 47% 53% 6+1%
Georges MikautadzeFWD	Villarreal	2.09	72provisional	1.73	50%	33	021% 129% 224% 314% 47% 53% 6+2%
Álex BaenaFWD	Atlético de Madrid	2.10	62provisional	1.54	44%	60	026% 130% 222% 312% 46% 52% 6+1%
Ayoze PérezFWD	Villarreal	1.94	64provisional	1.46	42%	56	027% 131% 222% 312% 45% 52% 6+1%
Carlos MartínFWD	Atlético de Madrid	2.05	57provisional	1.40	40%	38	028% 132% 222% 311% 45% 52% 6+1%

10 of 51 players shown, ranked by projection. Show all 51 →

Shots on target51 playersHighest: Julián Alvarez, 0.99 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
Julián AlvarezFWD	Atlético de Madrid	1.36	61provisional	0.99	60%	66	040% 134% 217% 36% 42% 51% 6+0%
Alexander SørlothFWD	Atlético de Madrid	1.75	41provisional	0.91	56%	70	044% 133% 215% 36% 42% 51% 6+0%
Ademola LookmanFWD	Atlético de Madrid	1.03	71provisional	0.84	55%	56	045% 134% 215% 35% 41% 5+0%
Georges MikautadzeFWD	Villarreal	0.97	72provisional	0.80	53%	33	047% 134% 214% 34% 41% 5+0%
Antoine GriezmannFWD	Atlético de Madrid	1.03	63provisional	0.76	51%	72	049% 133% 213% 34% 41% 5+0%
Giacomo RaspadoriFWD	Atlético de Madrid	1.06	57provisional	0.71	48%	51	052% 131% 212% 34% 41% 5+0%
Ayoze PérezFWD	Villarreal	0.82	64provisional	0.62	44%	56	056% 131% 210% 33% 4+1%
Nicolas PépéFWD	Villarreal	0.66	69provisional	0.53	40%	65	060% 129% 28% 32% 4+0%
Álex BaenaFWD	Atlético de Madrid	0.68	62provisional	0.50	38%	60	062% 128% 28% 32% 4+0%
Carlos MartínFWD	Atlético de Madrid	0.72	57provisional	0.49	38%	38	062% 128% 28% 31% 4+0%

10 of 51 players shown, ranked by projection. Show all 51 →

Fouls won51 playersHighest: Pape Gueye, 1.54 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
Pape GueyeMID	Villarreal	1.85	73provisional	1.54	45%	65	024% 131% 223% 313% 46% 52% 6+1%
Ilias AkhomachFWD	Villarreal	2.61	47provisional	1.49	41%	32	029% 130% 220% 311% 46% 53% 6+2%
Georges MikautadzeFWD	Villarreal	1.49	72provisional	1.22	34%	33	032% 134% 220% 39% 43% 51% 6+0%
Ayoze PérezFWD	Villarreal	1.58	64provisional	1.18	33%	56	034% 133% 220% 39% 43% 51% 6+0%
Nicolas PépéFWD	Villarreal	1.45	69provisional	1.14	32%	65	035% 133% 219% 38% 43% 51% 6+0%
Álex BaenaFWD	Atlético de Madrid	1.55	62provisional	1.12	31%	60	036% 133% 219% 38% 43% 51% 6+0%
Santiago MouriñoDEF	Villarreal	1.17	82provisional	1.08	29%	54	036% 135% 219% 37% 42% 51% 6+0%
Giuliano SimeoneFWD	Atlético de Madrid	1.52	58provisional	1.04	28%	65	039% 134% 218% 37% 42% 51% 6+0%
Rodrigo MendozaMID	Atlético de Madrid	1.42	59provisional	0.99	26%	25	039% 134% 217% 36% 42% 51% 6+0%
Pablo BarriosMID	Atlético de Madrid	1.12	76provisional	0.97	25%	55	039% 135% 217% 36% 42% 5+0%

10 of 51 players shown, ranked by projection. Show all 51 →

Saves5 playersHighest: Luiz Júnior, 3.15 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
Luiz JúniorGK	Villarreal	3.21	88provisional	3.15	58%	46	06% 115% 220% 320% 416% 510% 6+12%
Péter GulácsiGK	—	3.16	87provisional	3.07	57%	53	06% 116% 221% 320% 415% 510% 6+11%
Arnau TenasGK	Villarreal	3.03	86provisional	2.92	54%	10	07% 117% 222% 320% 415% 59% 6+10%
Jan OblakGK	Atlético de Madrid	2.38	89provisional	2.37	41%	67	011% 123% 225% 319% 412% 56% 6+5%
Juan MussoGK	Atlético de Madrid	2.24	86provisional	2.17	37%	11	013% 125% 225% 318% 410% 55% 6+3%

2 of 7 markets have no projection for this fixture.