Championship · England

Preston North EndvWolverhampton Wanderers

Saturday 22 August at 15:00Deepdalelineups not announced

Referee

Elliot Bell

17 matches on record

Fouls per game

22.6

-3% vs league

League average

23.2

fouls per match, both teams

Angles

every priced line builder

formAndrew Hughes over 0.5 shots: 7/10 of his last 10, 5 in a row
Last 20: 12/20 · 3/4 at home · strip 1 1 1 1 1 0 0 1 3 0 · market 45% · best 2.38 (Bet365) · bet365 2.38
formHarry Clarke over 0.5 shots: 8/10 of his last 10, 3 in a row
Last 20: 10/20 · 5/5 at home · strip 1 1 1 0 2 2 1 0 2 1 · market 64% · best 2.20 (Bet365) · bet365 2.20
formYerson Mosquera over 0.5 shots: 8/10 of his last 10
Last 20: 14/20 · 4/5 away · strip 0 2 2 1 3 1 0 1 1 1 · market 71% · best 1.44 (Bet365) · bet365 1.44
opponentPreston North End concede 16.0 shots a game — 3rd most of 27 in the Championship
Over their last 10. Good news for Wolverhampton Wanderers's shooters.
opponentPreston North End concede 8.7 fouls a game — 25th most of 27 in the Championship
Over their last 10. A hard place to get fouls.
opponentPreston North End concede 12.4 tackles a game — 25th most of 27 in the Championship
Over their last 10. A hard place to get tackles.
refereeElliot Bell: 22.6 fouls and 4.5 cards a game (league 22.3 / 3.4)
+0.3 fouls and +1.1 cards against his league's average over his last 17.

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 — 3 live calls

Yerson Mosqueraover 1.50 Shots3.00 at bet365 · fair 2.60+15.4%
Andrew Hughesover 0.50 Shots2.38 at bet365 · fair 2.20+8.0%
Yerson Mosqueraover 0.50 Shots on target3.40 at bet365 · fair 3.20+6.3%

Published at the price shown and scored against the closing line whatever happens next — the same rows, with staking context, are on the value board and in the track record.

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

Fouls52 playersHighest: Ali McCann, 1.40 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
Ali McCannMID	Preston North End	1.55	79provisional	1.40	40%	56	026% 133% 223% 311% 44% 51% 6+0%
Liam LindsayDEF	Preston North End	1.42	75provisional	1.23	35%	62	032% 134% 221% 39% 43% 51% 6+0%
Callum LangFWD	Preston North End	1.40	76provisional	1.23	35%	46	031% 135% 221% 39% 43% 51% 6+0%
Andrew HughesDEF	Preston North End	1.20	85provisional	1.15	32%	79	032% 136% 221% 38% 42% 51% 6+0%
Andrew MoranMID	Preston North End	1.38	70provisional	1.14	32%	46	034% 135% 220% 38% 43% 51% 6+0%
AndréMID	Wolverhampton Wanderers	1.23	79provisional	1.12	31%	69	034% 136% 220% 38% 42% 51% 6+0%
Marshall MunetsiMID	Wolverhampton Wanderers	1.43	64provisional	1.10	30%	28	036% 134% 219% 38% 43% 51% 6+0%
Yerson MosqueraDEF	Wolverhampton Wanderers	1.17	82provisional	1.09	30%	33	035% 136% 220% 37% 42% 51% 6+0%
Jhon AriasFWD	Wolverhampton Wanderers	1.66	48provisional	1.03	28%	23	040% 132% 217% 37% 43% 51% 6+0%
Jordan ThompsonMID	Preston North End	1.51	54provisional	1.03	27%	44	039% 134% 217% 37% 42% 51% 6+0%
Harry ClarkeDEF	—	1.15	78provisional	1.02	27%	32	037% 135% 218% 37% 42% 5+1%
Fer LópezMID	Wolverhampton Wanderers	1.35	60provisional	1.00	27%	44	039% 134% 217% 37% 42% 50% 6+0%
Mateus ManéMID	Wolverhampton Wanderers	1.09	71provisional	0.90	23%	29	042% 134% 216% 35% 41% 5+0%
Robbie BradyMID	Preston North End	1.66	40provisional	0.90	23%	34	044% 133% 215% 35% 42% 50% 6+0%
Ladislav KrejciDEF	Wolverhampton Wanderers	0.91	86provisional	0.88	22%	58	042% 136% 216% 35% 41% 5+0%
Hee-chan HwangFWD	Wolverhampton Wanderers	1.25	57provisional	0.88	22%	47	044% 133% 215% 35% 41% 5+0%
Pol ValentínDEF	Preston North End	1.16	62provisional	0.87	22%	68	043% 135% 215% 35% 41% 5+0%
Andrija VukcevicDEF	Preston North End	1.53	44provisional	0.87	22%	30	047% 131% 214% 36% 42% 50% 6+0%
Michael SmithFWD	Preston North End	1.77	34provisional	0.85	21%	78	046% 133% 214% 35% 42% 50% 6+0%
Santiago BuenoDEF	Wolverhampton Wanderers	0.94	79provisional	0.84	21%	58	045% 134% 215% 35% 41% 5+0%
Mads Frøkjaer-JensenMID	Preston North End	1.53	40provisional	0.83	20%	56	047% 133% 214% 35% 41% 50% 6+0%
Kieran TrippierDEF	Wolverhampton Wanderers	0.99	70provisional	0.82	20%	47	045% 134% 215% 34% 41% 5+0%
Adam ArmstrongFWD	Wolverhampton Wanderers	0.95	73provisional	0.81	20%	80	045% 135% 214% 34% 41% 5+0%
Raúl JiménezFWD	Wolverhampton Wanderers	1.34	45provisional	0.78	19%	75	049% 131% 213% 34% 41% 5+0%
Delano BurgzorgFWD	Preston North End	1.04	60provisional	0.75	18%	83	049% 132% 213% 34% 41% 5+0%
Milutin OsmajicFWD	Preston North End	1.04	56provisional	0.73	17%	63	051% 132% 212% 34% 41% 5+0%
Jordan StoreyDEF	Preston North End	0.74	86provisional	0.72	16%	79	049% 135% 213% 33% 41% 5+0%
Jamal Piaras LewisDEF	Preston North End	1.18	45provisional	0.70	16%	14	052% 131% 212% 33% 41% 5+0%
Emmanuel AgbadouDEF	Wolverhampton Wanderers	0.71	83provisional	0.67	15%	30	052% 134% 211% 33% 4+1%
Jean-Ricner BellegardeMID	Wolverhampton Wanderers	1.29	37provisional	0.67	15%	61	054% 131% 211% 33% 41% 5+0%
Brad PottsDEF	Preston North End	0.91	58provisional	0.65	14%	45	053% 132% 211% 33% 41% 5+0%
Angel GomesMID	Wolverhampton Wanderers	1.11	44provisional	0.64	14%	12	055% 131% 211% 33% 41% 5+0%
Jordan JamesMID	—	1.07	45provisional	0.63	14%	34	056% 130% 210% 33% 41% 5+0%
Lewis GibsonDEF	Preston North End	0.70	72provisional	0.58	12%	64	057% 131% 210% 32% 4+0%
David Møller WolfeDEF	Wolverhampton Wanderers	0.78	61provisional	0.58	12%	23	058% 130% 210% 32% 4+0%
Odeluga OffiahDEF	Preston North End	0.96	47provisional	0.57	12%	43	059% 129% 29% 32% 41% 5+0%
Will KeaneFWD	Preston North End	1.22	32provisional	0.56	12%	29	060% 129% 29% 32% 41% 5+0%
TotiDEF	Wolverhampton Wanderers	0.62	69provisional	0.50	10%	51	062% 129% 28% 32% 4+0%
Ki-Jana HoeverDEF	Wolverhampton Wanderers	1.06	33provisional	0.50	10%	23	063% 127% 28% 32% 4+0%
Pedro LimaDEF	Wolverhampton Wanderers	1.33	24provisional	0.49	10%	13	064% 127% 27% 32% 40% 5+0%
Alfie DevineMID	Preston North End	0.55	74provisional	0.48	9%	46	063% 129% 27% 31% 4+0%
Tolu ArokodareFWD	Wolverhampton Wanderers	0.98	33provisional	0.45	8%	33	066% 126% 27% 31% 4+0%
Hugo BuenoDEF	Wolverhampton Wanderers	0.72	48provisional	0.44	8%	35	066% 126% 27% 31% 4+0%
Thierry SmallDEF	Preston North End	0.62	56provisional	0.43	8%	42	066% 127% 26% 31% 4+0%
Stefán Teitur ThórdarsonMID	Preston North End	0.74	42provisional	0.41	7%	54	067% 125% 26% 31% 4+0%
Rodrigo GomesMID	Wolverhampton Wanderers	0.57	54provisional	0.38	6%	48	069% 125% 25% 31% 4+0%
Jackson TchatchouaDEF	Wolverhampton Wanderers	0.56	53provisional	0.37	6%	68	070% 124% 25% 31% 4+0%
Tommy DoyleMID	Wolverhampton Wanderers	0.83	30provisional	0.37	6%	63	071% 123% 25% 31% 4+0%
José SáGK	Wolverhampton Wanderers	0.06	89provisional	0.06	0%	52	094% 16% 2+0%
Sam JohnstoneGK	Wolverhampton Wanderers	0.01	88provisional	0.01	—	19	099% 1+1%
David CornellGK	Preston North End	0.01	69provisional	0.00	—	18	0100% 1+0%
Daniel IversenGK	Preston North End	0.00	88provisional	0.00	—	37	0100% 1+0%

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

Shots52 playersHighest: Adam Armstrong, 1.97 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
Adam ArmstrongFWD	Wolverhampton Wanderers	2.34	73provisional	1.97	56%	80	017% 127% 224% 316% 49% 54% 6+3%
Alfie DevineMID	Preston North End	1.89	74provisional	1.61	46%	46	023% 130% 223% 313% 46% 52% 6+1%
Raúl JiménezFWD	Wolverhampton Wanderers	2.87	45provisional	1.59	42%	75	029% 128% 219% 311% 46% 53% 6+3%
Mateus ManéMID	Wolverhampton Wanderers	1.85	71provisional	1.51	43%	29	026% 130% 222% 312% 46% 52% 6+1%
Callum LangFWD	Preston North End	1.71	76provisional	1.48	43%	46	026% 132% 223% 312% 45% 52% 6+1%
Delano BurgzorgFWD	Preston North End	1.85	60provisional	1.30	36%	83	033% 131% 220% 310% 44% 52% 6+1%
Marshall MunetsiMID	Wolverhampton Wanderers	1.56	64provisional	1.17	32%	28	036% 132% 219% 39% 43% 51% 6+0%
Tolu ArokodareFWD	Wolverhampton Wanderers	2.71	33provisional	1.15	29%	33	040% 131% 216% 37% 44% 52% 6+1%
Milutin OsmajicFWD	Preston North End	1.47	56provisional	0.99	26%	63	042% 132% 216% 37% 42% 51% 6+0%
Fer LópezMID	Wolverhampton Wanderers	1.35	60provisional	0.96	25%	44	042% 133% 216% 36% 42% 51% 6+0%

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

Shots on target52 playersHighest: Adam Armstrong, 0.70 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
Adam ArmstrongFWD	Wolverhampton Wanderers	0.83	73provisional	0.70	49%	80	051% 133% 212% 33% 41% 5+0%
Raúl JiménezFWD	Wolverhampton Wanderers	1.11	45provisional	0.62	42%	75	058% 128% 210% 33% 41% 5+0%
Mateus ManéMID	Wolverhampton Wanderers	0.68	71provisional	0.55	41%	29	059% 130% 29% 32% 4+0%
Callum LangFWD	Preston North End	0.63	76provisional	0.55	41%	46	059% 130% 29% 32% 4+0%
Milutin OsmajicFWD	Preston North End	0.70	56provisional	0.47	36%	63	064% 127% 27% 32% 4+0%
Alfie DevineMID	Preston North End	0.53	74provisional	0.45	36%	46	064% 128% 27% 31% 4+0%
Tolu ArokodareFWD	Wolverhampton Wanderers	0.99	33provisional	0.42	32%	33	068% 124% 26% 31% 4+0%
Delano BurgzorgFWD	Preston North End	0.59	60provisional	0.41	33%	83	067% 125% 26% 31% 4+0%
Marshall MunetsiMID	Wolverhampton Wanderers	0.51	64provisional	0.38	31%	28	069% 124% 25% 31% 4+0%
Hee-chan HwangFWD	Wolverhampton Wanderers	0.47	57provisional	0.32	27%	47	073% 122% 24% 3+1%

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

Fouls won52 playersHighest: Callum Lang, 1.56 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
Callum LangFWD	Preston North End	1.81	76provisional	1.56	45%	46	024% 131% 224% 313% 46% 52% 6+1%
Mateus ManéMID	Wolverhampton Wanderers	1.87	71provisional	1.52	44%	29	026% 130% 222% 312% 46% 52% 6+1%
Yerson MosqueraDEF	Wolverhampton Wanderers	1.39	82provisional	1.28	36%	33	030% 134% 222% 310% 43% 51% 6+0%
Delano BurgzorgFWD	Preston North End	1.71	60provisional	1.19	33%	83	036% 131% 219% 39% 44% 51% 6+0%
Jordan ThompsonMID	Preston North End	1.75	54provisional	1.12	30%	44	037% 133% 218% 38% 43% 51% 6+0%
Jean-Ricner BellegardeMID	Wolverhampton Wanderers	2.40	37provisional	1.12	30%	61	039% 132% 217% 38% 43% 51% 6+1%
Andrew MoranMID	Preston North End	1.30	70provisional	1.04	28%	46	038% 134% 218% 37% 42% 51% 6+0%
AndréMID	Wolverhampton Wanderers	1.13	79provisional	1.02	27%	69	038% 135% 218% 37% 42% 50% 6+0%
Milutin OsmajicFWD	Preston North End	1.37	56provisional	0.91	24%	63	045% 132% 215% 36% 42% 51% 6+0%
Fer LópezMID	Wolverhampton Wanderers	1.24	60provisional	0.88	22%	44	045% 133% 215% 35% 42% 5+0%

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

Saves4 playersHighest: Sam Johnstone, 3.14 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
Sam JohnstoneGK	Wolverhampton Wanderers	3.20	88provisional	3.14	58%	19	06% 115% 221% 320% 416% 510% 6+12%
José SáGK	Wolverhampton Wanderers	3.16	89provisional	3.13	58%	52	06% 115% 221% 320% 416% 510% 6+12%
Daniel IversenGK	Preston North End	2.63	88provisional	2.57	46%	37	010% 121% 224% 320% 413% 57% 6+6%
David CornellGK	Preston North End	2.41	69provisional	1.93	31%	18	021% 126% 222% 315% 49% 54% 6+3%

2 of 7 markets have no projection for this fixture.