Championship · England

MiddlesbroughvLincoln City

Saturday 15 August at 15:00Riverside Stadiumconfirmed lineup

Referee

Robert Madley

29 matches on record

Fouls per game

21.9

-5% vs league

League average

23.1

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

Fouls8 playersHighest: Leo Castledine, 1.56 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
Leo CastledineMID	Middlesbrough	1.56	90confirmed	1.56	46%	5	021% 132% 225% 313% 45% 52% 6+1%
Callum BrittainDEF	Middlesbrough	1.20	89confirmed	1.19	33%	44	031% 136% 221% 39% 43% 51% 6+0%
Neto BorgesDEF	Middlesbrough	1.24	85confirmed	1.16	32%	34	032% 136% 221% 38% 42% 51% 6+0%
Adilson MalandaDEF	Middlesbrough	1.16	90confirmed	1.16	32%	24	032% 136% 221% 38% 42% 51% 6+0%
Jeremy SarmientoFWD	Middlesbrough	1.66	63confirmed	1.16	32%	8	032% 136% 221% 38% 42% 51% 6+0%
Morgan WhittakerFWD	Middlesbrough	1.14	78confirmed	0.99	26%	49	038% 136% 218% 36% 42% 5+0%
Luke AylingDEF	Middlesbrough	0.84	87confirmed	0.81	20%	66	045% 136% 214% 34% 41% 5+0%
Sol BrynnGK	Middlesbrough	0.07	90confirmed	0.07	0%	55	093% 17% 2+0%

Tackles8 playersHighest: Luke Ayling, 2.97 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
Luke AylingDEF	Middlesbrough	3.07	87confirmed	2.97	75%	66	08% 117% 221% 319% 414% 59% 6+11%
Neto BorgesDEF	Middlesbrough	2.63	85confirmed	2.47	67%	34	011% 122% 223% 319% 412% 57% 6+6%
Callum BrittainDEF	Middlesbrough	2.22	89confirmed	2.19	61%	44	014% 125% 224% 317% 410% 55% 6+4%
Morgan WhittakerFWD	Middlesbrough	1.85	78confirmed	1.60	46%	49	023% 131% 223% 313% 46% 52% 6+1%
Jeremy SarmientoFWD	Middlesbrough	2.09	63confirmed	1.47	42%	8	026% 132% 223% 312% 45% 52% 6+1%
Leo CastledineMID	Middlesbrough	1.45	90confirmed	1.45	41%	5	026% 133% 223% 311% 45% 52% 6+1%
Adilson MalandaDEF	Middlesbrough	1.37	90confirmed	1.37	39%	24	028% 133% 222% 311% 44% 51% 6+1%
Sol BrynnGK	Middlesbrough	0.10	90confirmed	0.10	1%	55	091% 19% 2+1%

Shots8 playersHighest: Leo Castledine, 4.63 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
Leo CastledineMID	Middlesbrough	4.63	90confirmed	4.63	92%	5	02% 16% 212% 316% 417% 515% 6+33%
Morgan WhittakerFWD	Middlesbrough	4.97	78confirmed	4.30	90%	49	02% 17% 213% 317% 417% 515% 6+28%
Jeremy SarmientoFWD	Middlesbrough	3.27	63confirmed	2.29	65%	8	012% 124% 225% 319% 411% 56% 6+4%
Callum BrittainDEF	Middlesbrough	1.41	89confirmed	1.40	40%	44	026% 134% 223% 311% 44% 51% 6+0%
Luke AylingDEF	Middlesbrough	1.26	87confirmed	1.22	34%	66	031% 135% 221% 39% 43% 51% 6+0%
Neto BorgesDEF	Middlesbrough	0.95	85confirmed	0.90	23%	34	042% 136% 216% 35% 41% 5+0%
Adilson MalandaDEF	Middlesbrough	0.74	90confirmed	0.74	17%	24	049% 134% 213% 33% 41% 5+0%
Sol BrynnGK	Middlesbrough	0.00	90confirmed	0.00	—	55	0100% 1+0%

Fouls won8 playersHighest: Leo Castledine, 2.23 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
Leo CastledineMID	Middlesbrough	2.23	90confirmed	2.23	63%	5	012% 124% 225% 319% 411% 55% 6+3%
Morgan WhittakerFWD	Middlesbrough	2.21	78confirmed	1.91	56%	49	016% 128% 226% 316% 48% 54% 6+2%
Luke AylingDEF	Middlesbrough	1.80	87confirmed	1.74	51%	66	019% 130% 225% 315% 47% 53% 6+1%
Jeremy SarmientoFWD	Middlesbrough	2.08	63confirmed	1.46	42%	8	025% 133% 224% 312% 45% 52% 6+1%
Neto BorgesDEF	Middlesbrough	1.33	85confirmed	1.25	35%	34	030% 135% 221% 39% 43% 51% 6+0%
Callum BrittainDEF	Middlesbrough	0.91	89confirmed	0.90	23%	44	042% 136% 216% 35% 41% 5+0%
Adilson MalandaDEF	Middlesbrough	0.57	90confirmed	0.57	11%	24	057% 132% 29% 32% 4+0%
Sol BrynnGK	Middlesbrough	0.18	90confirmed	0.18	1%	55	084% 115% 2+1%

Cards8 playersHighest: Sol Brynn, 0.40 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
Sol BrynnGK	Middlesbrough	0.40	90confirmed	0.40	33%	55	067% 126% 25% 3+1%
Adilson MalandaDEF	Middlesbrough	0.21	90confirmed	0.21	19%	24	081% 117% 22% 3+0%
Callum BrittainDEF	Middlesbrough	0.19	89confirmed	0.19	17%	44	083% 116% 22% 3+0%
Leo CastledineMID	Middlesbrough	0.17	90confirmed	0.17	16%	5	084% 114% 2+1%
Luke AylingDEF	Middlesbrough	0.17	87confirmed	0.17	15%	66	085% 114% 2+1%
Neto BorgesDEF	Middlesbrough	0.16	85confirmed	0.15	14%	34	086% 113% 2+1%
Jeremy SarmientoFWD	Middlesbrough	0.17	63confirmed	0.12	11%	8	089% 111% 2+1%
Morgan WhittakerFWD	Middlesbrough	0.11	78confirmed	0.10	9%	49	091% 19% 2+0%

Saves1 playersHighest: Sol Brynn, 2.35 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
Sol BrynnGK	Middlesbrough	2.35	90confirmed	2.35	41%	55	012% 123% 225% 319% 412% 56% 6+5%

1 of 7 markets have no projection for this fixture.