Championship · England

BurnleyvWest Ham United

Sunday 16 August at 16:00Turf Moorlineups not announced

Referee

Joshua Smith

51 matches on record

Fouls per game

21.0

-7% vs league

League average

22.6

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 v20260813-1451 · Tackles v20260813-1451 · Shots v20260813-1451 · Fouls won v20260813-1451 · Cards v20260813-1451 · Saves v20260813-1451

Model projections

Fouls39 playersHighest: Valentín Mariano José Castellanos Giménez, 1.59 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
Valentín Mariano José Castellanos GiménezFWD	West Ham United	1.84	78provisional	1.59	47%	18	021% 132% 225% 313% 46% 52% 6+1%
Zian FlemmingFWD	Burnley	2.06	66provisional	1.51	43%	49	028% 128% 221% 313% 46% 52% 6+1%
Lucas Tolentino Coelho de LimaMID	West Ham United	1.76	77provisional	1.49	43%	47	025% 132% 223% 312% 45% 52% 6+1%
Luca KoleoshoFWD	Burnley	2.04	60provisional	1.36	39%	20	034% 127% 219% 311% 45% 52% 6+1%
Edson Omar Álvarez VelázquezMID	West Ham United	1.89	64provisional	1.34	38%	24	030% 133% 221% 311% 44% 51% 6+1%
Pablo Felipe Pereira de JesusFWD	West Ham United	1.97	59provisional	1.29	37%	10	032% 131% 220% 310% 44% 51% 6+1%
Tomáš SoučekMID	West Ham United	1.61	68provisional	1.22	34%	58	034% 132% 220% 39% 44% 51% 6+0%
Crysencio SummervilleFWD	West Ham United	1.62	65provisional	1.17	33%	41	035% 132% 219% 39% 43% 51% 6+0%
Hannibal MejbriMID	Burnley	2.06	50provisional	1.13	31%	40	040% 128% 217% 39% 44% 51% 6+1%
Josh CullenMID	Burnley	1.17	86provisional	1.12	31%	61	034% 136% 220% 38% 42% 51% 6+0%

10 of 39 players shown, ranked by projection. Show all 39 →

Tackles39 playersHighest: Lucas Tolentino Coelho de Lima, 2.03 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
Lucas Tolentino Coelho de LimaMID	West Ham United	2.38	77provisional	2.03	56%	47	018% 126% 223% 316% 49% 55% 6+4%
Kyle Walker-PetersDEF	West Ham United	2.91	60provisional	1.95	50%	16	028% 122% 217% 313% 49% 55% 6+6%
Lucas Pires SilvaDEF	Burnley	2.24	78provisional	1.93	53%	48	021% 126% 222% 315% 49% 54% 6+3%
Edson Omar Álvarez VelázquezMID	West Ham United	2.60	64provisional	1.84	50%	24	022% 127% 222% 314% 48% 54% 6+3%
Aaron Wan-BissakaDEF	West Ham United	1.85	86provisional	1.77	50%	59	021% 129% 224% 314% 47% 53% 6+2%
Oliver ScarlesDEF	West Ham United	3.34	47provisional	1.76	45%	17	030% 125% 217% 312% 47% 54% 6+4%
Jean-Clair TodiboDEF	West Ham United	2.09	73provisional	1.69	47%	45	024% 129% 222% 313% 47% 53% 6+2%
Kyle Andrew WalkerDEF	Burnley	1.74	86provisional	1.67	48%	35	023% 130% 223% 314% 47% 53% 6+2%
Soungoutou MagassaMID	West Ham United	3.36	45provisional	1.66	41%	12	034% 124% 215% 310% 47% 54% 6+4%
Josh CullenMID	Burnley	1.72	86provisional	1.65	47%	61	023% 130% 223% 313% 46% 53% 6+1%

10 of 39 players shown, ranked by projection. Show all 39 →

Shots39 playersHighest: Zian Flemming, 2.50 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
Zian FlemmingFWD	Burnley	3.42	66provisional	2.50	64%	49	017% 120% 219% 316% 412% 58% 6+8%
Valentín Mariano José Castellanos GiménezFWD	West Ham United	2.57	78provisional	2.22	63%	18	012% 124% 225% 319% 411% 55% 6+3%
Jarrod BowenFWD	West Ham United	2.03	89provisional	2.00	58%	72	015% 127% 226% 317% 49% 54% 6+2%
Lyle FosterFWD	Burnley	2.41	55provisional	1.47	40%	33	033% 127% 218% 311% 46% 53% 6+2%
Luca KoleoshoFWD	Burnley	2.15	60provisional	1.44	40%	20	034% 126% 219% 312% 46% 52% 6+1%
Marcus EdwardsFWD	Burnley	2.37	54provisional	1.43	39%	25	034% 127% 218% 311% 46% 53% 6+2%
Crysencio SummervilleFWD	West Ham United	1.78	65provisional	1.29	36%	41	033% 131% 220% 310% 44% 52% 6+1%
Lucas Tolentino Coelho de LimaMID	West Ham United	1.41	77provisional	1.20	33%	47	033% 134% 220% 39% 43% 51% 6+0%
Pablo Felipe Pereira de JesusFWD	West Ham United	1.71	59provisional	1.12	31%	10	037% 132% 218% 38% 43% 51% 6+0%
Hannibal MejbriMID	Burnley	2.02	50provisional	1.11	30%	40	041% 128% 216% 38% 44% 51% 6+1%

10 of 39 players shown, ranked by projection. Show all 39 →

Fouls won39 playersHighest: Lucas Tolentino Coelho de Lima, 1.70 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
Lucas Tolentino Coelho de LimaMID	West Ham United	1.99	77provisional	1.70	49%	47	022% 129% 224% 314% 47% 53% 6+1%
Crysencio SummervilleFWD	West Ham United	2.34	65provisional	1.69	47%	41	025% 128% 221% 314% 47% 53% 6+2%
Hannibal MejbriMID	Burnley	2.97	50provisional	1.64	44%	40	031% 125% 218% 312% 47% 54% 6+3%
Josh CullenMID	Burnley	1.60	86provisional	1.53	44%	61	023% 132% 224% 313% 45% 52% 6+1%
Jarrod BowenFWD	West Ham United	1.39	89provisional	1.37	39%	72	027% 134% 223% 311% 44% 51% 6+0%
Marcus EdwardsFWD	Burnley	2.00	54provisional	1.21	33%	25	039% 128% 217% 39% 44% 52% 6+1%
Zian FlemmingFWD	Burnley	1.60	66provisional	1.17	33%	49	037% 131% 219% 39% 43% 51% 6+0%
Kyle Walker-PetersDEF	West Ham United	1.39	60provisional	0.93	25%	16	046% 128% 215% 37% 42% 51% 6+0%
Valentín Mariano José Castellanos GiménezFWD	West Ham United	1.03	78provisional	0.89	22%	18	042% 135% 216% 35% 41% 5+0%
Chimuanya UgochukwuMID	Burnley	1.14	67provisional	0.85	22%	30	045% 133% 215% 35% 41% 5+0%

10 of 39 players shown, ranked by projection. Show all 39 →

Cards39 playersHighest: Lucas Tolentino Coelho de Lima, 0.22 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
Lucas Tolentino Coelho de LimaMID	West Ham United	0.26	77provisional	0.22	19%	47	081% 117% 22% 3+0%
Edson Omar Álvarez VelázquezMID	West Ham United	0.27	64provisional	0.19	17%	24	083% 116% 22% 3+0%
Hannibal MejbriMID	Burnley	0.32	50provisional	0.18	16%	40	084% 114% 22% 3+0%
Valentín Mariano José Castellanos GiménezFWD	West Ham United	0.20	78provisional	0.17	15%	18	085% 114% 2+1%
Tomáš SoučekMID	West Ham United	0.21	68provisional	0.16	15%	58	085% 113% 2+1%
Kyle Andrew WalkerDEF	Burnley	0.16	86provisional	0.16	15%	35	085% 113% 2+1%
Josh CullenMID	Burnley	0.16	86provisional	0.15	14%	61	086% 113% 2+1%
Alphonse AreolaGK	West Ham United	0.14	88provisional	0.14	13%	46	087% 112% 2+1%
Josh LaurentMID	Burnley	0.22	56provisional	0.13	12%	46	088% 111% 2+1%
Axel TuanzebeDEF	Burnley	0.14	86provisional	0.13	13%	14	087% 112% 2+1%

10 of 39 players shown, ranked by projection. Show all 39 →

Saves2 playersHighest: Alphonse Areola, 3.32 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
Alphonse AreolaGK	West Ham United	3.38	88provisional	3.32	61%	46	05% 114% 220% 320% 416% 511% 6+14%
Mads HermansenGK	West Ham United	2.98	90provisional	2.98	55%	18	07% 117% 222% 320% 415% 510% 6+10%

1 of 7 markets have no projection for this fixture.