Premier League · England

Nottingham ForestvLeeds United

Saturday 22 August at 15:00The City Groundlineups not announced

Referee

Not appointed

0 matches on record

Fouls per game

—

League average

22.9

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

Fouls41 playersHighest: Ethan Ampadu, 1.35 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
Ethan AmpaduMID	Leeds United	1.43	85provisional	1.35	39%	62	027% 134% 223% 311% 44% 51% 6+0%
Ibrahim SangaréMID	Nottingham Forest	1.83	65provisional	1.32	38%	32	033% 129% 220% 311% 45% 52% 6+1%
Anton StachMID	Leeds United	1.37	82provisional	1.25	35%	28	030% 135% 222% 39% 43% 51% 6+0%
Dominic Calvert-LewinFWD	Leeds United	1.42	78provisional	1.23	35%	31	032% 133% 221% 39% 43% 51% 6+0%
Ryan YatesMID	Nottingham Forest	2.33	45provisional	1.15	30%	29	039% 130% 216% 38% 44% 52% 6+1%
Jayden BogleDEF	Leeds United	1.21	85provisional	1.14	32%	77	033% 136% 220% 38% 42% 51% 6+0%
Igor JesusFWD	Nottingham Forest	1.59	63provisional	1.11	31%	31	037% 133% 219% 38% 43% 51% 6+0%
Ao TanakaMID	Leeds United	1.36	66provisional	0.99	27%	55	042% 131% 217% 37% 42% 51% 6+0%
Gabriel GudmundssonDEF	Leeds United	1.05	83provisional	0.97	25%	31	039% 136% 218% 36% 42% 5+0%
Ilia GruevMID	Leeds United	1.30	66provisional	0.95	25%	36	043% 132% 217% 36% 42% 50% 6+0%

10 of 41 players shown, ranked by projection. Show all 41 →

Tackles41 playersHighest: Neco Williams, 2.47 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
Neco WilliamsDEF	Nottingham Forest	2.77	80provisional	2.47	65%	66	015% 121% 221% 317% 412% 57% 6+7%
Anton StachMID	Leeds United	2.42	82provisional	2.20	61%	28	015% 125% 224% 317% 410% 55% 6+4%
Nicolás DomínguezMID	Nottingham Forest	3.82	52provisional	2.19	56%	44	021% 123% 219% 314% 410% 56% 6+7%
Ibrahim SangaréMID	Nottingham Forest	2.94	65provisional	2.13	56%	32	023% 122% 219% 315% 410% 56% 6+6%
Jayden BogleDEF	Leeds United	2.19	85provisional	2.08	58%	77	016% 126% 224% 317% 49% 55% 6+3%
Ethan AmpaduMID	Leeds United	2.14	85provisional	2.01	56%	62	018% 126% 224% 316% 49% 54% 6+3%
Gabriel GudmundssonDEF	Leeds United	2.15	83provisional	1.97	55%	31	018% 127% 224% 316% 49% 54% 6+3%
James JustinDEF	Leeds United	2.65	65provisional	1.93	51%	22	028% 122% 218% 314% 49% 55% 6+5%
Ao TanakaMID	Leeds United	2.46	66provisional	1.79	48%	55	027% 125% 219% 313% 48% 54% 6+3%
Sean LongstaffMID	Leeds United	3.51	44provisional	1.72	40%	13	037% 123% 213% 39% 47% 55% 6+6%

10 of 41 players shown, ranked by projection. Show all 41 →

Shots41 playersHighest: Dominic Calvert-Lewin, 1.89 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
Dominic Calvert-LewinFWD	Leeds United	2.18	78provisional	1.89	54%	31	020% 127% 223% 316% 49% 54% 6+2%
Morgan Gibbs-WhiteMID	Nottingham Forest	1.99	84provisional	1.85	54%	70	018% 129% 225% 316% 48% 53% 6+2%
Daniel JamesFWD	Leeds United	2.85	58provisional	1.82	49%	36	028% 124% 218% 314% 49% 55% 6+4%
Igor JesusFWD	Nottingham Forest	2.57	63provisional	1.79	50%	31	023% 127% 222% 314% 48% 54% 6+2%
Chris WoodFWD	Nottingham Forest	2.07	76provisional	1.75	50%	46	021% 129% 224% 315% 47% 53% 6+2%
Joël PiroeFWD	Leeds United	2.77	54provisional	1.66	44%	38	033% 123% 217% 312% 48% 54% 6+3%
Brenden AaronsonMID	Leeds United	1.86	73provisional	1.50	43%	74	026% 131% 223% 312% 45% 52% 6+1%
Anton StachMID	Leeds United	1.55	82provisional	1.41	41%	28	026% 133% 223% 311% 44% 51% 6+1%
Wilfried GnontoFWD	Leeds United	2.86	43provisional	1.35	35%	32	039% 126% 215% 310% 46% 53% 6+2%
Noah OkaforFWD	Leeds United	1.96	56provisional	1.22	34%	21	035% 131% 219% 39% 44% 51% 6+1%

10 of 41 players shown, ranked by projection. Show all 41 →

Fouls won41 playersHighest: Gabriel Gudmundsson, 1.49 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
Gabriel GudmundssonDEF	Leeds United	1.63	83provisional	1.49	43%	31	025% 132% 224% 312% 45% 52% 6+1%
Brenden AaronsonMID	Leeds United	1.62	73provisional	1.31	37%	74	030% 132% 221% 310% 44% 51% 6+1%
Neco WilliamsDEF	Nottingham Forest	1.38	80provisional	1.23	35%	66	032% 133% 220% 39% 43% 51% 6+0%
Morgan Gibbs-WhiteMID	Nottingham Forest	1.20	84provisional	1.11	30%	70	034% 135% 220% 38% 42% 51% 6+0%
Ethan AmpaduMID	Leeds United	1.12	85provisional	1.05	28%	62	037% 135% 219% 37% 42% 51% 6+0%
Dominic Calvert-LewinFWD	Leeds United	1.20	78provisional	1.04	28%	31	038% 134% 218% 37% 42% 51% 6+0%
Ryan YatesMID	Nottingham Forest	2.10	45provisional	1.04	27%	29	043% 130% 215% 37% 43% 51% 6+1%
Igor JesusFWD	Nottingham Forest	1.48	63provisional	1.03	28%	31	040% 133% 217% 37% 42% 51% 6+0%
Jayden BogleDEF	Leeds United	1.08	85provisional	1.02	27%	77	037% 135% 218% 37% 42% 50% 6+0%
Wilfried GnontoFWD	Leeds United	2.15	43provisional	1.02	27%	32	046% 127% 214% 37% 43% 51% 6+1%

10 of 41 players shown, ranked by projection. Show all 41 →

Cards41 playersHighest: Ethan Ampadu, 0.25 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
Ethan AmpaduMID	Leeds United	0.26	85provisional	0.25	22%	62	078% 119% 22% 3+0%
Ibrahim SangaréMID	Nottingham Forest	0.32	65provisional	0.23	20%	32	080% 117% 22% 3+0%
Ryan YatesMID	Nottingham Forest	0.43	45provisional	0.21	18%	29	082% 116% 22% 3+0%
Jayden BogleDEF	Leeds United	0.22	85provisional	0.21	19%	77	081% 117% 22% 3+0%
Anton StachMID	Leeds United	0.22	82provisional	0.20	18%	28	082% 116% 22% 3+0%
MurilloDEF	Nottingham Forest	0.20	87provisional	0.19	17%	61	083% 116% 22% 3+0%
Jaka BijolDEF	Leeds United	0.23	76provisional	0.19	17%	23	083% 115% 22% 3+0%
Gabriel GudmundssonDEF	Leeds United	0.20	83provisional	0.18	17%	31	083% 115% 2+2%
MoratoDEF	Nottingham Forest	0.33	48provisional	0.18	16%	26	084% 114% 22% 3+0%
Nicolò SavonaDEF	Nottingham Forest	0.21	73provisional	0.17	16%	12	084% 114% 21% 3+0%
Neco WilliamsDEF	Nottingham Forest	0.19	80provisional	0.17	16%	66	084% 114% 2+1%
Lucas PerriGK	Leeds United	0.17	90provisional	0.17	16%	16	084% 114% 2+1%
Nicolás DomínguezMID	Nottingham Forest	0.29	52provisional	0.17	15%	44	085% 114% 21% 3+0%
Morgan Gibbs-WhiteMID	Nottingham Forest	0.17	84provisional	0.16	15%	70	085% 113% 2+1%
Ilia GruevMID	Leeds United	0.21	66provisional	0.15	14%	36	086% 113% 2+1%
Ao TanakaMID	Leeds United	0.21	66provisional	0.15	14%	55	086% 112% 2+1%
Ola AinaDEF	Nottingham Forest	0.15	87provisional	0.15	14%	53	086% 113% 2+1%
Nikola MilenkovićDEF	Nottingham Forest	0.14	89provisional	0.14	13%	75	087% 112% 2+1%
Sebastiaan BornauwDEF	Leeds United	0.34	37provisional	0.14	12%	6	088% 111% 21% 3+0%
James JustinDEF	Leeds United	0.18	65provisional	0.13	12%	22	088% 111% 2+1%
Joe RodonDEF	Leeds United	0.13	88provisional	0.13	12%	80	088% 111% 2+1%
Dominic Calvert-LewinFWD	Leeds United	0.14	78provisional	0.12	11%	31	089% 111% 2+1%
Omari HutchinsonFWD	Nottingham Forest	0.19	54provisional	0.11	10%	22	090% 110% 2+1%
Sam ByramDEF	Leeds United	0.26	38provisional	0.11	10%	16	090% 19% 2+1%
Wilfried GnontoFWD	Leeds United	0.22	43provisional	0.10	10%	32	090% 19% 2+1%
Brenden AaronsonMID	Leeds United	0.13	73provisional	0.10	10%	74	090% 19% 2+1%
Dan NdoyeFWD	Nottingham Forest	0.19	49provisional	0.10	10%	15	090% 19% 2+1%
Igor JesusFWD	Nottingham Forest	0.15	63provisional	0.10	10%	31	090% 19% 2+1%
Sean LongstaffMID	Leeds United	0.21	44provisional	0.10	9%	13	091% 19% 2+1%
Daniel JamesFWD	Leeds United	0.14	58provisional	0.09	8%	36	092% 18% 2+0%
Noah OkaforFWD	Leeds United	0.14	56provisional	0.09	8%	21	092% 18% 2+0%
Dilane BakwaFWD	Nottingham Forest	0.20	40provisional	0.09	8%	8	092% 18% 2+0%
Largie RamazaniFWD	Leeds United	0.24	28provisional	0.07	7%	6	093% 16% 2+0%
Lukas NmechaFWD	Leeds United	0.17	35provisional	0.07	6%	12	094% 16% 2+0%
Chris WoodFWD	Nottingham Forest	0.08	76provisional	0.06	6%	46	094% 16% 2+0%
James McAteeMID	Nottingham Forest	0.26	21provisional	0.06	6%	3	094% 15% 2+0%
Matz SelsGK	Nottingham Forest	0.06	88provisional	0.06	5%	68	095% 15% 2+0%
Joël PiroeFWD	Leeds United	0.09	54provisional	0.05	5%	38	095% 15% 2+0%
Taiwo AwoniyiFWD	Nottingham Forest	0.22	21provisional	0.05	5%	8	095% 15% 2+0%
Callum Hudson-OdoiFWD	Nottingham Forest	0.07	66provisional	0.05	5%	55	095% 15% 2+0%
Mateo JosephFWD	Leeds United	0.13	33provisional	0.05	5%	12	095% 14% 2+0%

All 41 players shown, ranked by projection. Show fewer ↥

Saves2 playersHighest: Lucas Perri, 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
Lucas PerriGK	Leeds United	3.01	90provisional	3.01	56%	16	07% 116% 221% 320% 415% 510% 6+11%
Matz SelsGK	Nottingham Forest	2.82	88provisional	2.77	51%	68	09% 118% 222% 320% 414% 58% 6+8%

1 of 7 markets have no projection for this fixture.