Championship · England

West Ham UnitedvCharlton Athletic

Saturday 22 August at 15:00London Stadiumlineups not announced

Referee

Andrew Kitchen

58 matches on record

Fouls per game

23.0

-1% vs league

League average

23.2

fouls per match, both teams

Angles

every priced line builder

formGreg Docherty over 0.5 shots: 7/10 of his last 10, 5 in a row
Last 20: 10/20 · 2/4 away · strip 2 1 1 2 2 0 1 0 0 1 · market 61% · best 1.85 (Coral) · bet365 1.67
opponentCharlton Athletic concede 5.3 shots on target a game — 3rd most of 27 in the Championship
Over their last 10. Good news for West Ham United's shooters.
opponentWest Ham United concede 9.0 fouls a game — 18th most of 20 in the Championship
Over their last 9. 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 — 4 live calls

Konstantinos Mavropanosover 0.50 Shots on target3.25 at bet365 · fair 2.80+16.1%
Greg Dochertyover 0.50 Shots on target3.75 at bet365 · fair 3.30+13.6%
Greg Dochertyover 1.50 Shots4.00 at bet365 · fair 3.65+9.6%
Taty Castellanosover 2.50 Shots1.33 at bet365 · fair 1.25+6.6%

Published at the price shown and scored against the closing line whatever happens next — the same rows, with staking context, are on the value board and in the track record.

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

Fouls54 playersHighest: Conor Coventry, 1.42 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
Conor CoventryMID	Charlton Athletic	1.61	76provisional	1.42	41%	41	026% 133% 223% 312% 44% 51% 6+0%
Greg DochertyMID	Charlton Athletic	1.36	78provisional	1.22	34%	39	031% 135% 221% 39% 43% 51% 6+0%
Karoy AndersonMID	Charlton Athletic	1.56	63provisional	1.19	33%	10	033% 134% 220% 39% 43% 51% 6+0%
Harvey KnibbsMID	Charlton Athletic	2.06	43provisional	1.18	33%	26	035% 132% 219% 39% 43% 51% 6+0%
Nathaniel ChalobahMID	Charlton Athletic	1.79	50provisional	1.15	32%	30	035% 134% 219% 38% 43% 51% 6+0%
Lucas PaquetáMID	West Ham United	1.26	79provisional	1.13	31%	51	033% 135% 220% 38% 42% 51% 6+0%
Taty CastellanosFWD	West Ham United	1.25	79provisional	1.13	31%	59	033% 136% 220% 38% 42% 51% 6+0%
Edson ÁlvarezMID	West Ham United	1.54	58provisional	1.11	30%	28	035% 134% 219% 38% 43% 51% 6+0%
Kayne RamsayDEF	Charlton Athletic	1.19	83provisional	1.11	31%	37	034% 136% 220% 38% 42% 51% 6+0%
PabloFWD	West Ham United	1.40	65provisional	1.10	30%	15	035% 135% 219% 38% 42% 51% 6+0%
Crysencio SummervilleFWD	West Ham United	1.24	71provisional	1.03	28%	50	037% 135% 218% 37% 42% 50% 6+0%
Lloyd JonesDEF	Charlton Athletic	1.06	86provisional	1.03	27%	47	036% 136% 219% 37% 42% 5+0%
Tomáš SoučekMID	West Ham United	1.10	73provisional	0.95	25%	70	040% 135% 217% 36% 42% 5+0%
Millenic AlliFWD	Charlton Athletic	1.31	58provisional	0.93	24%	38	043% 133% 216% 36% 42% 50% 6+0%
Matty GoddenFWD	Charlton Athletic	1.74	38provisional	0.90	23%	12	045% 132% 215% 36% 42% 51% 6+0%
Miles LeaburnFWD	Charlton Athletic	1.57	42provisional	0.89	22%	39	044% 134% 215% 35% 42% 50% 6+0%
Luke BerryMID	Charlton Athletic	2.20	26provisional	0.86	21%	16	048% 131% 213% 35% 42% 51% 6+0%
Reece BurkeDEF	Charlton Athletic	1.30	51provisional	0.85	21%	34	045% 134% 215% 35% 41% 5+0%
Danny McNamaraDEF	Charlton Athletic	1.38	47provisional	0.81	21%	30	049% 130% 213% 35% 42% 50% 6+0%
Macaulay GillespheyDEF	Charlton Athletic	0.99	69provisional	0.80	20%	35	047% 133% 214% 34% 41% 5+0%
Aaron Wan-BissakaDEF	West Ham United	0.73	86provisional	0.70	16%	61	050% 134% 212% 33% 4+1%
Onel Lázaro Hernández MayeaFWD	Charlton Athletic	1.38	36provisional	0.69	16%	29	053% 131% 211% 34% 41% 5+0%
Tyreece CampbellFWD	Charlton Athletic	0.90	61provisional	0.67	15%	46	053% 132% 211% 33% 41% 5+0%
Amari'i BellDEF	Charlton Athletic	0.69	84provisional	0.65	14%	66	052% 134% 211% 32% 4+0%
El Hadji Malick DioufDEF	West Ham United	0.79	70provisional	0.64	14%	33	054% 132% 211% 33% 41% 5+0%
Luke ChambersDEF	Charlton Athletic	0.84	61provisional	0.63	14%	18	054% 132% 211% 32% 4+1%
Freddie PottsMID	West Ham United	0.96	52provisional	0.63	14%	59	056% 131% 210% 33% 41% 5+0%
Mohamadou KantéMID	West Ham United	1.53	28provisional	0.62	14%	12	059% 127% 29% 33% 41% 5+0%
Charlie KelmanFWD	Charlton Athletic	0.98	47provisional	0.60	13%	33	057% 130% 210% 32% 41% 5+0%
Kyle Walker-PetersDEF	West Ham United	0.63	81provisional	0.58	12%	57	057% 132% 210% 32% 4+0%
Joël VeltmanDEF	West Ham United	0.83	56provisional	0.57	12%	46	058% 129% 29% 32% 4+1%
Andrew IrvingMID	West Ham United	1.26	31provisional	0.54	12%	17	062% 127% 28% 32% 41% 5+0%
Sonny CareyMID	Charlton Athletic	0.70	65provisional	0.54	11%	47	059% 130% 29% 32% 4+0%
Joe Rankin-CostelloDEF	Charlton Athletic	1.24	30provisional	0.54	11%	53	061% 128% 28% 32% 41% 5+0%
Maximilian KilmanDEF	West Ham United	0.65	70provisional	0.53	11%	60	061% 129% 28% 32% 4+0%
Soungoutou MagassaMID	West Ham United	1.10	34provisional	0.52	11%	22	062% 127% 28% 32% 40% 5+0%
Karlan GrantFWD	Charlton Athletic	0.72	60provisional	0.52	10%	71	061% 129% 28% 32% 4+0%
Jarrod BowenFWD	West Ham United	0.53	88provisional	0.52	10%	73	060% 131% 28% 31% 4+0%
Maxwel CornetFWD	—	1.35	24provisional	0.52	10%	17	061% 129% 28% 32% 4+0%
Konstantinos MavropanosDEF	West Ham United	0.58	77provisional	0.52	10%	65	060% 130% 28% 32% 4+0%
Ibrahim FullahMID	Charlton Athletic	1.13	29provisional	0.49	9%	11	062% 129% 27% 31% 4+0%
George EarthyMID	West Ham United	1.07	31provisional	0.49	9%	50	062% 128% 27% 32% 4+0%
Nayef AguerdDEF	West Ham United	0.51	83provisional	0.48	8%	23	062% 129% 27% 31% 4+0%
Jean-Clair TodiboDEF	West Ham United	0.49	76provisional	0.43	7%	50	065% 127% 26% 31% 4+0%
Adama TraoréFWD	West Ham United	1.00	29provisional	0.43	8%	60	067% 125% 26% 31% 4+0%
Oliver ScarlesDEF	West Ham United	0.69	48provisional	0.42	8%	29	067% 126% 26% 31% 4+0%
Joël PiroeFWD	—	0.78	38provisional	0.39	7%	62	070% 123% 26% 31% 4+0%
James Ward-ProwseMID	West Ham United	0.68	43provisional	0.38	7%	43	070% 124% 25% 31% 4+0%
Rob ApterFWD	Charlton Athletic	0.75	36provisional	0.37	6%	13	071% 123% 25% 31% 4+0%
Manor SolomonFWD	West Ham United	0.43	56provisional	0.30	4%	62	075% 121% 24% 3+0%
Alphonse AreolaGK	West Ham United	0.06	87provisional	0.06	0%	46	094% 16% 2+0%
Thomas KaminskiGK	Charlton Athletic	0.03	89provisional	0.03	—	82	097% 1+3%
Will MannionGK	Charlton Athletic	0.01	86provisional	0.01	—	10	099% 1+1%
Mads HermansenGK	West Ham United	0.00	88provisional	0.00	—	46	0100% 1+0%

All 54 players shown, ranked by projection. Show fewer ↥

Shots54 playersHighest: Taty Castellanos, 3.33 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
Taty CastellanosFWD	West Ham United	3.72	79provisional	3.33	81%	59	05% 114% 219% 320% 416% 511% 6+14%
Jarrod BowenFWD	West Ham United	2.62	88provisional	2.57	71%	73	09% 120% 224% 320% 413% 57% 6+6%
Crysencio SummervilleFWD	West Ham United	2.44	71provisional	2.00	56%	50	018% 126% 224% 316% 49% 54% 6+3%
Joël PiroeFWD	—	3.94	38provisional	1.86	45%	62	029% 127% 216% 310% 47% 55% 6+6%
PabloFWD	West Ham United	2.08	65provisional	1.59	46%	15	024% 130% 223% 313% 46% 52% 6+1%
Lucas PaquetáMID	West Ham United	1.77	79provisional	1.58	46%	51	023% 131% 224% 313% 46% 52% 6+1%
Manor SolomonFWD	West Ham United	2.08	56provisional	1.39	38%	62	032% 130% 220% 311% 45% 52% 6+1%
Tomáš SoučekMID	West Ham United	1.59	73provisional	1.33	38%	70	030% 133% 221% 310% 44% 51% 6+1%
Karlan GrantFWD	Charlton Athletic	1.75	60provisional	1.23	34%	71	034% 132% 219% 39% 44% 51% 6+1%
Sonny CareyMID	Charlton Athletic	1.56	65provisional	1.18	33%	47	035% 133% 219% 39% 43% 51% 6+0%

10 of 54 players shown, ranked by projection. Show all 54 →

Shots on target54 playersHighest: Taty Castellanos, 1.38 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
Taty CastellanosFWD	West Ham United	1.54	79provisional	1.38	73%	59	027% 133% 223% 311% 44% 51% 6+1%
Jarrod BowenFWD	West Ham United	0.98	88provisional	0.97	61%	73	039% 136% 217% 36% 42% 5+0%
Joël PiroeFWD	—	1.55	38provisional	0.73	45%	62	055% 127% 211% 34% 42% 51% 6+0%
Crysencio SummervilleFWD	West Ham United	0.75	71provisional	0.61	44%	50	056% 131% 210% 32% 4+1%
PabloFWD	West Ham United	0.74	65provisional	0.56	42%	15	058% 130% 29% 32% 4+0%
Karlan GrantFWD	Charlton Athletic	0.68	60provisional	0.48	36%	71	064% 127% 27% 32% 4+0%
Lucas PaquetáMID	West Ham United	0.52	79provisional	0.47	37%	51	063% 128% 27% 31% 4+0%
Tomáš SoučekMID	West Ham United	0.55	73provisional	0.46	36%	70	064% 128% 27% 31% 4+0%
Manor SolomonFWD	West Ham United	0.68	56provisional	0.45	35%	62	065% 126% 27% 31% 4+0%
Charlie KelmanFWD	Charlton Athletic	0.69	47provisional	0.40	31%	33	069% 124% 26% 31% 4+0%

10 of 54 players shown, ranked by projection. Show all 54 →

Fouls won54 playersHighest: Crysencio Summerville, 1.83 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
Crysencio SummervilleFWD	West Ham United	2.25	71provisional	1.83	52%	50	020% 128% 224% 315% 48% 54% 6+2%
Lucas PaquetáMID	West Ham United	1.83	79provisional	1.63	47%	51	022% 131% 224% 314% 46% 52% 6+1%
Taty CastellanosFWD	West Ham United	1.53	79provisional	1.36	39%	59	027% 134% 223% 311% 44% 51% 6+0%
Jarrod BowenFWD	West Ham United	1.31	88provisional	1.28	36%	73	029% 135% 222% 310% 43% 51% 6+0%
Kyle Walker-PetersDEF	West Ham United	1.37	81provisional	1.24	35%	57	031% 134% 221% 39% 43% 51% 6+0%
Amari'i BellDEF	Charlton Athletic	1.31	84provisional	1.23	35%	66	030% 135% 221% 39% 43% 51% 6+0%
Joël VeltmanDEF	West Ham United	1.71	56provisional	1.12	30%	46	039% 131% 217% 38% 43% 51% 6+0%
Manor SolomonFWD	West Ham United	1.49	56provisional	0.98	26%	62	042% 132% 216% 37% 42% 51% 6+0%
Millenic AlliFWD	Charlton Athletic	1.41	58provisional	0.95	25%	38	043% 132% 216% 36% 42% 51% 6+0%
Karlan GrantFWD	Charlton Athletic	1.11	60provisional	0.77	19%	71	049% 132% 213% 34% 41% 5+0%

10 of 54 players shown, ranked by projection. Show all 54 →

Saves4 playersHighest: Thomas Kaminski, 3.01 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
Thomas KaminskiGK	Charlton Athletic	3.05	89provisional	3.01	56%	82	07% 116% 221% 320% 415% 510% 6+11%
Will MannionGK	Charlton Athletic	3.06	86provisional	2.95	54%	10	07% 117% 222% 320% 415% 59% 6+10%
Alphonse AreolaGK	West Ham United	2.80	87provisional	2.73	50%	46	09% 119% 223% 320% 414% 58% 6+8%
Mads HermansenGK	West Ham United	2.59	88provisional	2.54	45%	46	010% 121% 224% 320% 413% 57% 6+6%

2 of 7 markets have no projection for this fixture.