Championship · England

Birmingham CityvBristol City

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

Referee

Not appointed

0 matches on record

Fouls per game

—

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

Fouls46 playersHighest: Jay Stansfield, 1.43 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	1.71	75provisional	1.43	42%	42	025% 133% 224% 312% 44% 51% 6+0%
Ross McCrorieDEF	Bristol City	1.80	71provisional	1.41	41%	59	027% 133% 223% 311% 44% 51% 6+1%
August PriskeFWD	Birmingham City	2.05	54provisional	1.22	33%	12	037% 130% 218% 39% 44% 52% 6+1%
Tomoki IwataMID	Birmingham City	1.29	84provisional	1.21	34%	45	031% 135% 221% 39% 43% 51% 6+0%
Jhon Elmer Solis RomeroMID	Birmingham City	1.45	65provisional	1.05	29%	15	038% 134% 218% 37% 42% 51% 6+0%
Seung-Ho PaikMID	Birmingham City	1.15	78provisional	1.00	27%	39	038% 135% 218% 36% 42% 5+1%
Phil NeumannDEF	Birmingham City	0.96	88provisional	0.94	24%	32	039% 136% 217% 35% 41% 5+0%
Sinclair ArmstrongFWD	Bristol City	2.05	41provisional	0.93	24%	49	044% 132% 215% 36% 42% 51% 6+0%
Joe WilliamsMID	Bristol City	1.48	55provisional	0.91	24%	20	045% 131% 216% 36% 42% 50% 6+0%
Sam MorsyMID	Bristol City	1.26	65provisional	0.91	23%	16	042% 134% 216% 35% 41% 5+0%

10 of 46 players shown, ranked by projection. Show all 46 →

Tackles46 playersHighest: George Tanner, 1.93 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
George TannerDEF	Bristol City	2.49	70provisional	1.93	52%	57	023% 125% 221% 314% 49% 55% 6+4%
Ross McCrorieDEF	Bristol City	2.38	71provisional	1.86	52%	59	020% 128% 223% 315% 48% 54% 6+3%
Kai WagnerDEF	Birmingham City	1.84	87provisional	1.79	51%	16	020% 129% 224% 315% 47% 53% 6+2%
Marc LeonardMID	Birmingham City	3.41	46provisional	1.73	44%	10	027% 129% 219% 311% 46% 54% 6+4%
Vivaldo Borges dos Santos NetoDEF	Bristol City	2.11	72provisional	1.68	47%	32	025% 128% 221% 313% 47% 53% 6+2%
Cameron PringDEF	Bristol City	2.25	66provisional	1.65	46%	47	027% 128% 221% 313% 47% 53% 6+2%
Tomoki IwataMID	Birmingham City	1.66	84provisional	1.56	44%	45	025% 131% 223% 312% 46% 52% 6+1%
Max BirdMID	Bristol City	2.10	67provisional	1.55	43%	55	027% 129% 221% 312% 46% 53% 6+2%
Seung-Ho PaikMID	Birmingham City	1.60	78provisional	1.39	39%	39	029% 132% 221% 311% 45% 52% 6+1%
Sam MorsyMID	Bristol City	1.92	65provisional	1.39	39%	16	030% 132% 221% 311% 45% 52% 6+1%

10 of 46 players shown, ranked by projection. Show all 46 →

Shots46 playersHighest: Jay Stansfield, 2.34 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	2.80	75provisional	2.34	65%	42	012% 123% 224% 319% 412% 56% 6+5%
Marvin DuckschFWD	Birmingham City	2.95	60provisional	1.95	54%	26	022% 125% 221% 315% 49% 55% 6+3%
Demarai GrayFWD	Birmingham City	2.73	62provisional	1.88	53%	29	020% 127% 223% 315% 48% 54% 6+3%
Scott TwineMID	Bristol City	2.33	68provisional	1.76	50%	72	021% 128% 223% 315% 47% 53% 6+2%
Patrick RobertsFWD	Birmingham City	2.23	63provisional	1.57	44%	28	028% 128% 221% 313% 46% 53% 6+1%
August PriskeFWD	Birmingham City	2.50	54provisional	1.49	40%	12	032% 128% 218% 311% 46% 53% 6+2%
Emil Riis JakobsenFWD	Bristol City	1.90	66provisional	1.40	40%	40	028% 132% 222% 311% 45% 52% 6+1%
Carlos Vicente RoblesFWD	Birmingham City	2.02	58provisional	1.31	36%	13	034% 130% 218% 310% 45% 52% 6+1%
Kyogo FuruhashiFWD	Birmingham City	2.98	36provisional	1.19	30%	14	039% 130% 216% 38% 44% 52% 6+1%
Tomoki IwataMID	Birmingham City	1.27	84provisional	1.19	33%	45	032% 135% 220% 39% 43% 51% 6+0%

10 of 46 players shown, ranked by projection. Show all 46 →

Fouls won46 playersHighest: Jason Knight, 1.51 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
Jason KnightMID	Bristol City	1.57	87provisional	1.51	44%	80	024% 132% 224% 312% 45% 52% 6+1%
Scott TwineMID	Bristol City	1.74	68provisional	1.32	37%	72	030% 132% 221% 310% 44% 51% 6+1%
Adam RandellMID	Bristol City	1.36	83provisional	1.25	35%	43	030% 134% 221% 39% 43% 51% 6+0%
Demarai GrayFWD	Birmingham City	1.56	62provisional	1.07	29%	29	038% 133% 218% 38% 43% 51% 6+0%
Cameron PringDEF	Bristol City	1.44	66provisional	1.06	29%	47	039% 132% 218% 37% 43% 51% 6+0%
Patrick RobertsFWD	Birmingham City	1.46	63provisional	1.02	28%	28	041% 132% 217% 37% 42% 51% 6+0%
Keshi AndersonFWD	Birmingham City	2.37	38provisional	1.00	26%	11	044% 131% 215% 37% 43% 51% 6+1%
Bright Osayi-SamuelDEF	Birmingham City	1.55	58provisional	0.99	27%	20	043% 130% 216% 37% 42% 51% 6+0%
Ethan LairdDEF	Birmingham City	2.02	43provisional	0.97	25%	12	045% 130% 215% 37% 43% 51% 6+0%
Carlos Vicente RoblesFWD	Birmingham City	1.43	58provisional	0.92	24%	13	045% 131% 215% 36% 42% 51% 6+0%

10 of 46 players shown, ranked by projection. Show all 46 →

Cards46 playersHighest: Ross McCrorie, 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
Ross McCrorieDEF	Bristol City	0.28	71provisional	0.22	19%	59	081% 117% 22% 3+0%
Cameron PringDEF	Bristol City	0.25	66provisional	0.18	16%	47	084% 115% 22% 3+0%
Christoph KlarerDEF	Birmingham City	0.18	90provisional	0.18	16%	43	084% 115% 2+1%
James BeadleGK	Birmingham City	0.17	90provisional	0.17	16%	35	084% 114% 2+1%
Jhon Elmer Solis RomeroMID	Birmingham City	0.23	65provisional	0.17	15%	15	085% 114% 2+1%
Noah EileDEF	Bristol City	0.18	84provisional	0.17	15%	14	085% 114% 2+1%
Phil NeumannDEF	Birmingham City	0.17	88provisional	0.17	15%	32	085% 114% 2+1%
Tomoki IwataMID	Birmingham City	0.18	84provisional	0.16	15%	45	085% 114% 2+1%
Sam MorsyMID	Bristol City	0.23	65provisional	0.16	15%	16	085% 114% 2+1%
Jay StansfieldFWD	Birmingham City	0.19	75provisional	0.16	15%	42	085% 113% 2+1%

10 of 46 players shown, ranked by projection. Show all 46 →

Saves3 playersHighest: Max O’Leary, 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
Max O’LearyGK	Bristol City	2.77	90provisional	2.77	51%	53	08% 119% 223% 320% 414% 58% 6+8%
James BeadleGK	Birmingham City	2.36	90provisional	2.36	41%	35	011% 123% 225% 319% 412% 56% 6+5%
Ryan AllsopGK	Birmingham City	2.21	90provisional	2.21	38%	11	013% 125% 225% 318% 411% 55% 6+4%

1 of 7 markets have no projection for this fixture.