Championship · England

Birmingham CityvSouthampton

Tuesday 1 September at 19:45St. 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

Fouls52 playersHighest: Flynn Downes, 1.53 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
Flynn DownesMID	Southampton	1.82	76provisional	1.53	45%	59	025% 131% 224% 313% 45% 52% 6+1%
Jay StansfieldFWD	Birmingham City	1.74	75provisional	1.46	42%	42	025% 133% 224% 312% 45% 51% 6+1%
Caspar JanderMID	Southampton	1.45	78provisional	1.25	36%	34	031% 133% 221% 310% 43% 51% 6+0%
August PriskeFWD	Birmingham City	2.08	54provisional	1.24	34%	12	036% 130% 218% 39% 44% 52% 6+1%
Tomoki IwataMID	Birmingham City	1.31	84provisional	1.23	35%	45	030% 135% 221% 39% 43% 51% 6+0%
Cyle LarinFWD	Southampton	1.89	53provisional	1.11	30%	12	038% 132% 218% 38% 43% 51% 6+0%
Jhon Elmer Solis RomeroMID	Birmingham City	1.48	65provisional	1.07	29%	15	037% 134% 218% 38% 42% 51% 6+0%
Seung-Ho PaikMID	Birmingham City	1.17	78provisional	1.02	27%	39	037% 135% 218% 37% 42% 50% 6+0%
Phil NeumannDEF	Birmingham City	0.98	88provisional	0.96	25%	32	039% 136% 217% 36% 41% 5+0%
Christoph KlarerDEF	Birmingham City	0.89	90provisional	0.89	22%	43	042% 136% 216% 35% 41% 5+0%

10 of 52 players shown, ranked by projection. Show all 52 →

Tackles52 playersHighest: Caspar Jander, 2.64 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
Caspar JanderMID	Southampton	3.07	78provisional	2.64	67%	34	014% 119% 220% 317% 413% 58% 6+9%
Kai WagnerDEF	Birmingham City	1.94	87provisional	1.88	54%	16	018% 128% 224% 315% 48% 54% 6+2%
Marc LeonardMID	Birmingham City	3.59	46provisional	1.82	46%	10	026% 128% 219% 311% 47% 54% 6+5%
Welington Damascena SantosDEF	Southampton	2.88	51provisional	1.64	43%	17	032% 125% 217% 312% 47% 54% 6+3%
Tomoki IwataMID	Birmingham City	1.75	84provisional	1.64	47%	45	023% 130% 223% 313% 46% 53% 6+1%
Flynn DownesMID	Southampton	1.94	76provisional	1.62	46%	59	025% 129% 222% 313% 46% 53% 6+2%
Seung-Ho PaikMID	Birmingham City	1.68	78provisional	1.47	41%	39	027% 131% 222% 312% 45% 52% 6+1%
Finn AzazMID	Southampton	1.74	74provisional	1.44	41%	39	029% 131% 221% 311% 45% 52% 6+1%
Jhon Elmer Solis RomeroMID	Birmingham City	1.93	65provisional	1.40	39%	15	030% 131% 220% 311% 45% 52% 6+1%
James BreeDEF	Southampton	1.68	74provisional	1.38	39%	32	031% 130% 221% 311% 45% 52% 6+1%
Ryan ManningDEF	Southampton	1.74	71provisional	1.38	38%	59	032% 130% 220% 311% 45% 52% 6+1%
Joe AriboMID	Southampton	2.20	55provisional	1.34	36%	27	035% 129% 218% 310% 45% 52% 6+1%
Jack StephensDEF	Southampton	1.41	80provisional	1.26	35%	47	033% 132% 220% 310% 44% 51% 6+1%
Bright Osayi-SamuelDEF	Birmingham City	1.95	58provisional	1.25	34%	20	037% 129% 218% 310% 44% 52% 6+1%
Alexander CochraneDEF	Birmingham City	1.49	73provisional	1.22	34%	19	035% 131% 219% 39% 44% 51% 6+1%
Phil NeumannDEF	Birmingham City	1.21	88provisional	1.19	33%	32	033% 134% 220% 39% 43% 51% 6+0%
Patrick RobertsFWD	Birmingham City	1.65	63provisional	1.16	32%	28	038% 130% 218% 39% 44% 51% 6+1%
Thomas DoyleMID	Birmingham City	2.03	50provisional	1.13	30%	23	041% 129% 216% 38% 44% 52% 6+1%
Cameron BraggMID	Southampton	2.45	40provisional	1.10	28%	7	046% 126% 213% 37% 44% 52% 6+1%
Christoph KlarerDEF	Birmingham City	1.09	90provisional	1.09	30%	43	036% 135% 219% 37% 42% 51% 6+0%
Yukinari SugawaraDEF	Southampton	1.93	51provisional	1.09	29%	22	041% 130% 216% 38% 43% 51% 6+1%
Demarai GrayFWD	Birmingham City	1.58	62provisional	1.08	29%	29	038% 132% 218% 38% 43% 51% 6+0%
Ethan LairdDEF	Birmingham City	2.22	43provisional	1.06	28%	12	043% 129% 215% 37% 43% 51% 6+1%
Jay StansfieldFWD	Birmingham City	1.23	75provisional	1.03	27%	42	038% 134% 218% 37% 42% 51% 6+0%
Joshua QuarshieDEF	Southampton	1.25	73provisional	1.01	28%	11	043% 129% 217% 37% 43% 51% 6+0%
Carlos Vicente RoblesFWD	Birmingham City	1.51	58provisional	0.98	26%	13	044% 130% 215% 37% 43% 51% 6+0%
Keshi AndersonFWD	Birmingham City	2.23	38provisional	0.94	24%	11	046% 130% 214% 36% 43% 51% 6+1%
Nathan Wood-GordonDEF	Southampton	1.17	72provisional	0.94	25%	40	044% 131% 216% 36% 42% 51% 6+0%
Tom FellowsMID	Southampton	1.40	60provisional	0.93	24%	31	044% 132% 215% 36% 42% 51% 6+0%
Kuryu MatsukiMID	Southampton	1.61	51provisional	0.90	23%	13	047% 129% 214% 36% 42% 51% 6+0%
Jack RobinsonDEF	Birmingham City	1.08	75provisional	0.90	23%	15	043% 134% 216% 35% 42% 50% 6+0%
Taylor Harwood-BellisDEF	Southampton	0.91	87provisional	0.88	22%	76	044% 134% 215% 35% 41% 5+0%
Willum Þór WillumssonMID	Birmingham City	1.93	39provisional	0.84	22%	5	055% 123% 212% 36% 43% 51% 6+0%
Leonardo Weschenfelder-ScienzaMID	Southampton	1.07	66provisional	0.79	19%	35	048% 132% 213% 34% 41% 5+0%
Ronnie EdwardsDEF	Southampton	1.24	57provisional	0.78	21%	8	054% 125% 213% 35% 42% 51% 6+0%
Adam ArmstrongFWD	Southampton	0.91	67provisional	0.68	16%	42	053% 131% 211% 33% 41% 5+0%
Ryan FraserFWD	Southampton	1.11	50provisional	0.61	14%	15	058% 128% 210% 33% 41% 5+0%
Lewis KoumasFWD	Birmingham City	1.52	32provisional	0.55	12%	10	062% 126% 28% 33% 41% 5+0%
Ross StewartFWD	Southampton	1.23	38provisional	0.52	11%	21	063% 126% 28% 32% 41% 5+0%
Cameron ArcherFWD	Southampton	1.09	38provisional	0.45	9%	30	067% 124% 27% 32% 40% 5+0%
Cyle LarinFWD	Southampton	0.71	53provisional	0.41	8%	12	068% 124% 26% 31% 4+0%
Samuel EdozieFWD	Southampton	1.49	25provisional	0.41	7%	5	069% 124% 26% 31% 40% 5+0%
August PriskeFWD	Birmingham City	0.65	54provisional	0.39	7%	12	070% 123% 26% 31% 4+0%
Kyogo FuruhashiFWD	Birmingham City	0.80	36provisional	0.32	5%	14	075% 120% 24% 31% 4+0%
Marvin DuckschFWD	Birmingham City	0.37	60provisional	0.25	3%	26	079% 118% 23% 3+0%
Damion DownsFWD	Southampton	0.68	25provisional	0.19	2%	4	083% 115% 22% 3+0%
Ryan AllsopGK	Birmingham City	0.07	90provisional	0.07	0%	11	093% 17% 2+0%
James BeadleGK	Birmingham City	0.03	90provisional	0.03	—	35	097% 1+3%
Alex McCarthyGK	Southampton	0.01	90provisional	0.01	—	12	099% 1+1%
Gavin BazunuGK	Southampton	0.01	90provisional	0.01	—	19	099% 1+1%
Daniel PeretzGK	Southampton	0.01	91provisional	0.01	—	22	099% 1+1%
Aaron RamsdaleGK	Southampton	0.01	90provisional	0.01	—	30	099% 1+1%

All 52 players shown, ranked by projection. Show fewer ↥

Shots52 playersHighest: Jay Stansfield, 2.57 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	3.07	75provisional	2.57	69%	42	010% 120% 223% 319% 413% 57% 6+6%
Marvin DuckschFWD	Birmingham City	3.23	60provisional	2.14	57%	26	020% 123% 221% 316% 410% 56% 6+5%
Demarai GrayFWD	Birmingham City	3.00	62provisional	2.06	57%	29	018% 125% 222% 316% 410% 55% 6+4%
Adam ArmstrongFWD	Southampton	2.44	67provisional	1.82	51%	42	022% 127% 223% 315% 48% 54% 6+2%
Leonardo Weschenfelder-ScienzaMID	Southampton	2.35	66provisional	1.73	49%	35	022% 128% 223% 314% 47% 53% 6+2%
Patrick RobertsFWD	Birmingham City	2.45	63provisional	1.72	48%	28	025% 127% 221% 314% 48% 53% 6+2%
Finn AzazMID	Southampton	2.08	74provisional	1.72	49%	39	022% 129% 223% 314% 47% 53% 6+2%
August PriskeFWD	Birmingham City	2.74	54provisional	1.63	44%	12	029% 127% 219% 312% 47% 54% 6+3%
Carlos Vicente RoblesFWD	Birmingham City	2.22	58provisional	1.44	40%	13	032% 129% 219% 311% 46% 52% 6+1%
Kyogo FuruhashiFWD	Birmingham City	3.26	36provisional	1.30	33%	14	036% 130% 216% 38% 44% 52% 6+2%

10 of 52 players shown, ranked by projection. Show all 52 →

Fouls won52 playersHighest: Leonardo Weschenfelder-Scienza, 2.38 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
Leonardo Weschenfelder-ScienzaMID	Southampton	3.23	66provisional	2.38	64%	35	014% 122% 222% 318% 412% 57% 6+6%
Demarai GrayFWD	Birmingham City	1.67	62provisional	1.15	32%	29	035% 133% 219% 38% 43% 51% 6+0%
Ryan ManningDEF	Southampton	1.41	71provisional	1.11	31%	59	037% 132% 218% 38% 43% 51% 6+0%
Patrick RobertsFWD	Birmingham City	1.56	63provisional	1.10	30%	28	038% 131% 218% 38% 43% 51% 6+0%
Keshi AndersonFWD	Birmingham City	2.54	38provisional	1.07	28%	11	041% 131% 215% 37% 43% 51% 6+1%
Bright Osayi-SamuelDEF	Birmingham City	1.66	58provisional	1.06	29%	20	041% 130% 217% 38% 43% 51% 6+0%
Ethan LairdDEF	Birmingham City	2.17	43provisional	1.04	27%	12	043% 130% 215% 37% 43% 51% 6+1%
Finn AzazMID	Southampton	1.25	74provisional	1.03	28%	39	038% 134% 218% 37% 42% 51% 6+0%
Kuryu MatsukiMID	Southampton	1.83	51provisional	1.03	28%	13	043% 130% 216% 37% 43% 51% 6+0%
Caspar JanderMID	Southampton	1.16	78provisional	1.00	27%	34	040% 134% 217% 37% 42% 51% 6+0%

10 of 52 players shown, ranked by projection. Show all 52 →

Cards52 playersHighest: Flynn Downes, 0.29 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
Flynn DownesMID	Southampton	0.35	76provisional	0.29	25%	59	075% 121% 23% 3+0%
Gavin BazunuGK	Southampton	0.27	90provisional	0.27	24%	19	076% 121% 23% 3+0%
Aaron RamsdaleGK	Southampton	0.20	90provisional	0.20	18%	30	082% 116% 22% 3+0%
Taylor Harwood-BellisDEF	Southampton	0.20	87provisional	0.19	18%	76	082% 116% 22% 3+0%
Christoph KlarerDEF	Birmingham City	0.18	90provisional	0.18	17%	43	083% 115% 2+2%
James BeadleGK	Birmingham City	0.18	90provisional	0.18	16%	35	084% 115% 2+1%
Jhon Elmer Solis RomeroMID	Birmingham City	0.24	65provisional	0.17	16%	15	084% 114% 2+1%
Caspar JanderMID	Southampton	0.20	78provisional	0.17	15%	34	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	0.17	15%	45	085% 114% 2+1%

10 of 52 players shown, ranked by projection. Show all 52 →

Saves6 playersHighest: Aaron Ramsdale, 3.64 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
Aaron RamsdaleGK	Southampton	3.64	90provisional	3.64	67%	30	04% 111% 218% 319% 417% 513% 6+18%
Alex McCarthyGK	Southampton	3.05	90provisional	3.05	56%	12	06% 116% 221% 320% 415% 510% 6+11%
Daniel PeretzGK	Southampton	2.98	91provisional	3.02	56%	22	07% 116% 221% 320% 415% 510% 6+11%
Gavin BazunuGK	Southampton	2.80	90provisional	2.80	51%	19	08% 118% 223% 320% 414% 59% 6+8%
James BeadleGK	Birmingham City	2.37	90provisional	2.37	41%	35	011% 123% 225% 319% 412% 56% 6+5%
Ryan AllsopGK	Birmingham City	2.22	90provisional	2.22	38%	11	013% 124% 225% 318% 411% 55% 6+4%

1 of 7 markets have no projection for this fixture.