Championship · England

Birmingham CityvBristol City

Saturday 22 August at 12:30St. Andrew's Stadiumlineups not announced

Referee

Will Finnie

23 matches on record

Fouls per game

21.3

-8% vs league

League average

23.2

fouls per match, both teams

Angles

every priced line builder

formSam Greenwood over 1.5 shots: 8/10 of his last 10
Last 20: 11/20 · 3/4 away · strip 1 2 2 2 2 2 5 3 5 0 · market 71% · best 1.85 (Ladbrokes) · bet365 1.61
opponentBristol City concede 16.2 shots a game — 2nd most of 27 in the Championship
Over their last 10. Good news for Birmingham City's shooters.

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

Fouls48 playersHighest: Jay Stansfield, 1.37 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
Jay StansfieldFWD	Birmingham City	1.56	76provisional	1.37	40%	46	026% 134% 223% 311% 44% 51% 6+0%
August PriskeFWD	Birmingham City	1.76	65provisional	1.36	39%	18	029% 132% 222% 311% 44% 51% 6+1%
Sam GreenwoodMID	Bristol City	1.72	58provisional	1.23	35%	39	033% 133% 220% 39% 44% 51% 6+0%
Ross McCrorieDEF	Bristol City	1.40	73provisional	1.20	34%	64	031% 135% 221% 39% 43% 51% 6+0%
Tomoki IwataMID	Birmingham City	1.18	84provisional	1.12	31%	46	033% 136% 220% 38% 42% 51% 6+0%
Luis VázquezFWD	Birmingham City	1.32	60provisional	0.97	26%	18	040% 134% 217% 36% 42% 50% 6+0%
Cameron PringDEF	Bristol City	1.14	71provisional	0.96	25%	58	040% 135% 217% 36% 42% 5+0%
Phil NeumannDEF	Birmingham City	0.90	87provisional	0.88	22%	33	042% 136% 216% 35% 41% 5+0%
Fally MayuluFWD	Bristol City	2.50	21provisional	0.87	21%	25	044% 134% 214% 35% 41% 50% 6+0%
Seung-ho PaikMID	Birmingham City	1.06	68provisional	0.86	21%	44	044% 134% 215% 35% 41% 5+0%

10 of 48 players shown, ranked by projection. Show all 48 →

Shots48 playersHighest: Jay Stansfield, 2.23 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
Jay StansfieldFWD	Birmingham City	2.57	76provisional	2.23	63%	46	013% 124% 225% 318% 411% 55% 6+4%
Demarai GrayFWD	Birmingham City	2.67	56provisional	1.80	50%	38	022% 128% 222% 314% 48% 54% 6+2%
Scott TwineMID	Bristol City	1.92	71provisional	1.59	46%	81	023% 131% 224% 313% 46% 52% 6+1%
August PriskeFWD	Birmingham City	2.10	65provisional	1.58	45%	18	026% 129% 222% 313% 46% 53% 6+1%
Marvin DuckschFWD	Birmingham City	2.63	48provisional	1.55	42%	65	030% 129% 219% 311% 46% 53% 6+2%
Luis VázquezFWD	Birmingham City	2.17	60provisional	1.54	43%	18	027% 130% 221% 312% 46% 52% 6+1%
Patrick RobertsFWD	Birmingham City	2.11	61provisional	1.52	43%	84	028% 130% 221% 312% 46% 52% 6+1%
Sam GreenwoodMID	Bristol City	2.03	58provisional	1.41	39%	39	030% 131% 221% 311% 45% 52% 6+1%
Carlos VicenteFWD	Birmingham City	1.54	76provisional	1.34	38%	76	029% 133% 222% 310% 44% 51% 6+1%
Tomoki IwataMID	Birmingham City	1.37	84provisional	1.30	37%	46	029% 134% 222% 310% 44% 51% 6+0%

10 of 48 players shown, ranked by projection. Show all 48 →

Shots on target48 playersHighest: Jay Stansfield, 0.77 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
Jay StansfieldFWD	Birmingham City	0.89	76provisional	0.77	53%	46	047% 134% 214% 34% 41% 5+0%
Marvin DuckschFWD	Birmingham City	1.18	48provisional	0.70	46%	65	054% 130% 211% 34% 41% 5+0%
Luis VázquezFWD	Birmingham City	0.85	60provisional	0.61	43%	18	057% 130% 210% 33% 41% 5+0%
August PriskeFWD	Birmingham City	0.78	65provisional	0.59	43%	18	057% 130% 210% 32% 4+1%
Demarai GrayFWD	Birmingham City	0.82	56provisional	0.56	41%	38	059% 129% 29% 32% 4+0%
Carlos VicenteFWD	Birmingham City	0.62	76provisional	0.54	41%	76	059% 130% 29% 32% 4+0%
Scott TwineMID	Bristol City	0.63	71provisional	0.52	40%	81	060% 130% 28% 32% 4+0%
Sam GreenwoodMID	Bristol City	0.68	58provisional	0.47	36%	39	064% 127% 27% 31% 4+0%
Tomi HorvatMID	Bristol City	0.56	66provisional	0.43	34%	15	066% 127% 26% 31% 4+0%
Patrick RobertsFWD	Birmingham City	0.60	61provisional	0.43	34%	84	066% 126% 26% 31% 4+0%

10 of 48 players shown, ranked by projection. Show all 48 →

Fouls won48 playersHighest: Carlos Vicente, 1.41 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
Carlos VicenteFWD	Birmingham City	1.64	76provisional	1.41	40%	76	027% 133% 222% 311% 45% 52% 6+1%
Jason KnightMID	Bristol City	1.40	87provisional	1.35	39%	83	027% 134% 223% 311% 44% 51% 6+0%
Scott TwineMID	Bristol City	1.51	71provisional	1.23	35%	81	031% 134% 221% 39% 43% 51% 6+0%
Adam RandellMID	Bristol City	1.29	84provisional	1.22	34%	84	031% 135% 221% 39% 43% 51% 6+0%
Sam GreenwoodMID	Bristol City	1.71	58provisional	1.16	32%	39	036% 132% 219% 39% 43% 51% 6+0%
Luis VázquezFWD	Birmingham City	1.63	60provisional	1.14	31%	18	036% 132% 219% 38% 43% 51% 6+0%
Rob AtkinsonDEF	Bristol City	1.19	77provisional	1.05	28%	40	036% 135% 219% 37% 42% 50% 6+0%
Kristoffer LundDEF	—	1.21	74provisional	1.02	27%	33	038% 134% 218% 37% 42% 51% 6+0%
Keshi AndersonFWD	Birmingham City	1.92	41provisional	0.98	25%	26	043% 132% 216% 36% 42% 51% 6+0%
Rob DickieDEF	Bristol City	1.00	85provisional	0.95	25%	71	040% 135% 217% 36% 42% 5+0%

10 of 48 players shown, ranked by projection. Show all 48 →

Saves3 playersHighest: Brad Collins, 2.77 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
Brad CollinsGK	—	2.92	84provisional	2.77	50%	15	09% 119% 222% 320% 414% 58% 6+8%
James BeadleGK	Birmingham City	2.25	89provisional	2.24	38%	74	013% 124% 225% 318% 411% 55% 6+4%
Ryan AllsopGK	Birmingham City	2.25	86provisional	2.17	37%	11	013% 125% 225% 318% 410% 55% 6+3%

2 of 7 markets have no projection for this fixture.