PER90

Championship · England

Blackburn RoversvMiddlesbrough

Ewood Parklineups not announced

Referee

Tom Reeves

7 matches on record — under 15, so the model falls back toward the league mean

Fouls per game

20.4

-12% vs league

League average

23.2

fouls per match, both teams

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

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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

Fouls57 playersHighest: Will Lankshear, 1.26 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.

PlayerTeamModel /90Exp. minsProjectedOver 1.5nDistribution
Will LankshearFWDMiddlesbrough1.6365provisional1.2636%59
031%
133%
221%
310%
44%
51%
6+0%
Kyle JosephFWDMiddlesbrough1.5362provisional1.1732%63
033%
134%
220%
39%
43%
51%
6+0%
Yuki OhashiFWDBlackburn Rovers1.5062provisional1.1231%83
036%
134%
219%
38%
43%
51%
6+0%
Axel HenrikssonMIDBlackburn Rovers1.7244provisional1.0026%18
041%
132%
216%
37%
42%
51%
6+0%
Sam MorsyMIDBlackburn Rovers1.2167provisional0.9725%52
040%
134%
217%
36%
42%
50%
6+0%
Hayden CarterDEFBlackburn Rovers1.0082provisional0.9424%26
039%
136%
217%
35%
41%
5+0%
Aidan MorrisMIDMiddlesbrough0.9784provisional0.9223%78
041%
136%
217%
35%
41%
5+0%
Makhtar GueyeFWDBlackburn Rovers2.0031provisional0.8922%60
045%
132%
214%
35%
42%
51%
6+0%
Andri GudjohnsenFWDBlackburn Rovers1.2557provisional0.8923%26
044%
134%
215%
35%
41%
5+0%
Moussa BaradjiMIDBlackburn Rovers1.3053provisional0.8622%32
046%
132%
215%
35%
42%
5+0%

10 of 57 players shown, ranked by projection. Show all 57 →

Shots57 playersHighest: Morgan Whittaker, 2.20 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.

PlayerTeamModel /90Exp. minsProjectedOver 1.5nDistribution
Morgan WhittakerFWDMiddlesbrough2.5376provisional2.2062%80
014%
124%
224%
318%
411%
55%
6+4%
Yuki OhashiFWDBlackburn Rovers2.2162provisional1.6145%83
026%
129%
222%
313%
46%
53%
6+2%
Tommy ConwayFWDMiddlesbrough1.7676provisional1.5344%84
024%
131%
223%
313%
45%
52%
6+1%
David StrelecFWDMiddlesbrough1.8465provisional1.4140%35
028%
132%
222%
311%
45%
52%
6+1%
Leo CastledineMIDMiddlesbrough2.7739provisional1.3736%12
032%
131%
219%
39%
45%
52%
6+2%
Ryoya MorishitaMIDBlackburn Rovers1.4874provisional1.2636%38
030%
134%
221%
310%
43%
51%
6+0%
Will LankshearFWDMiddlesbrough1.6765provisional1.2635%59
032%
132%
220%
310%
44%
51%
6+0%
Riley McGreeMIDMiddlesbrough1.8255provisional1.2033%46
035%
132%
219%
39%
44%
51%
6+1%
Todd CantwellMIDBlackburn Rovers1.5763provisional1.1632%66
036%
132%
219%
38%
43%
51%
6+0%
Aidan MorrisMIDMiddlesbrough1.1984provisional1.1231%78
034%
135%
220%
38%
42%
51%
6+0%
Andri GudjohnsenFWDBlackburn Rovers1.5557provisional1.0629%26
039%
132%
217%
37%
43%
51%
6+0%
Kyle JosephFWDMiddlesbrough1.4162provisional1.0428%63
038%
134%
218%
37%
42%
51%
6+0%
Makhtar GueyeFWDBlackburn Rovers2.4331provisional0.9925%60
044%
131%
214%
36%
43%
51%
6+1%
Oladapo AfolayanFWDBlackburn Rovers1.7844provisional0.9826%48
043%
131%
215%
37%
42%
51%
6+0%
Alex GilbertMIDMiddlesbrough1.5051provisional0.9224%28
045%
131%
215%
36%
42%
51%
6+0%
Moussa BaradjiMIDBlackburn Rovers1.4453provisional0.9124%32
045%
131%
215%
36%
42%
51%
6+0%
Jayden FevrierFWDBlackburn Rovers1.5145provisional0.8421%12
048%
131%
213%
35%
42%
51%
6+0%
Marcus ForssFWDMiddlesbrough2.4324provisional0.8019%25
050%
131%
212%
34%
42%
51%
6+0%
Augustus KargboFWDBlackburn Rovers1.8630provisional0.7618%18
050%
132%
212%
34%
41%
50%
6+0%
Luke AylingDEFMiddlesbrough0.8282provisional0.7618%73
048%
134%
213%
34%
41%
5+0%
Sondre TronstadMIDBlackburn Rovers0.8083provisional0.7518%67
048%
134%
213%
34%
41%
5+0%
Sontje HansenFWDMiddlesbrough2.1125provisional0.7517%19
050%
132%
212%
34%
41%
50%
6+0%
Ryan HedgesFWDBlackburn Rovers1.1847provisional0.6916%66
053%
131%
211%
33%
41%
5+0%
Callum BrittainDEFMiddlesbrough0.7186provisional0.6915%78
051%
133%
212%
33%
41%
5+0%
Myles Peart-HarrisMIDMiddlesbrough1.1946provisional0.6716%50
055%
130%
211%
33%
41%
5+0%
Mathias JørgensenFWDBlackburn Rovers1.2541provisional0.6414%20
057%
129%
210%
33%
41%
5+0%
Sean McLoughlinDEFBlackburn Rovers0.6487provisional0.6313%82
054%
133%
211%
32%
4+0%
Tom AtchesonDEFBlackburn Rovers0.6979provisional0.6213%15
055%
132%
210%
32%
4+1%
Sam MorsyMIDBlackburn Rovers0.7467provisional0.5812%52
058%
130%
29%
32%
4+1%
Adam ForshawMIDBlackburn Rovers0.8556provisional0.5812%55
058%
129%
29%
32%
4+1%
Ryan AlebiosuDEFBlackburn Rovers0.6282provisional0.5812%40
057%
131%
29%
32%
4+0%
Jeremy SarmientoFWDMiddlesbrough1.6425provisional0.5712%64
059%
129%
29%
32%
41%
5+0%
Sam SilveraFWDMiddlesbrough1.1737provisional0.5511%33
060%
129%
29%
32%
40%
5+0%
Nathan RedmondFWDBlackburn Rovers1.3430provisional0.5411%10
062%
127%
28%
32%
41%
5+0%
Lewis MillerDEFBlackburn Rovers0.7165provisional0.5411%29
060%
129%
29%
32%
4+0%
Hayden CarterDEFBlackburn Rovers0.5882provisional0.5410%26
059%
131%
28%
32%
4+0%
Micah HamiltonFWDMiddlesbrough1.6821provisional0.5110%17
063%
127%
27%
32%
41%
5+0%
Axel HenrikssonMIDBlackburn Rovers0.9344provisional0.5111%18
063%
127%
28%
32%
4+1%
Neto BorgesDEFMiddlesbrough0.5678provisional0.499%77
062%
129%
28%
31%
4+0%
Kaly SèneFWDMiddlesbrough1.3324provisional0.458%28
065%
126%
26%
31%
4+0%
Scott WhartonDEFBlackburn Rovers0.6160provisional0.438%12
067%
126%
26%
31%
4+0%
Adilson MalandaDEFMiddlesbrough0.4486provisional0.437%25
066%
127%
26%
31%
4+0%
Harry PickeringDEFBlackburn Rovers0.5467provisional0.427%31
067%
126%
26%
31%
4+0%
Sidnei TavaresMIDBlackburn Rovers0.9235provisional0.418%13
068%
124%
26%
31%
4+0%
Ashley PhillipsDEF0.4086provisional0.386%75
069%
125%
25%
3+1%
Alex BanguraDEFMiddlesbrough0.6445provisional0.366%13
071%
123%
25%
31%
4+0%
Dion De NeveMIDBlackburn Rovers0.8330provisional0.335%27
074%
121%
24%
31%
4+0%
Sverre NypanMIDMiddlesbrough0.8328provisional0.325%20
073%
122%
24%
3+1%
George PrattDEFBlackburn Rovers0.3480provisional0.314%10
074%
122%
24%
3+0%
Yuri RibeiroDEFBlackburn Rovers0.4165provisional0.314%38
074%
121%
24%
3+1%
Kristi MontgomeryMIDBlackburn Rovers0.4556provisional0.304%25
075%
121%
24%
3+1%
Alfie JonesDEFMiddlesbrough0.3370provisional0.263%64
078%
119%
23%
3+0%
George EdmundsonDEFMiddlesbrough0.4051provisional0.253%32
079%
118%
23%
3+0%
Balázs TóthGKBlackburn Rovers0.0089provisional0.0041
0100%
1+0%
Aynsley PearsGKBlackburn Rovers0.0088provisional0.0053
0100%
1+0%
Sol BrynnGKMiddlesbrough0.0089provisional0.0055
0100%
1+0%
Radek VitekGKMiddlesbrough0.0089provisional0.0042
0100%
1+0%

All 57 players shown, ranked by projection. Show fewer ↥

Shots on target57 playersHighest: Morgan Whittaker, 0.66 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.

PlayerTeamModel /90Exp. minsProjectedOver 0.5nDistribution
Morgan WhittakerFWDMiddlesbrough0.7676provisional0.6647%80
053%
133%
211%
33%
41%
5+0%
Tommy ConwayFWDMiddlesbrough0.7276provisional0.6346%84
054%
132%
211%
32%
4+1%
David StrelecFWDMiddlesbrough0.7765provisional0.5943%35
057%
131%
210%
32%
4+0%
Yuki OhashiFWDBlackburn Rovers0.8062provisional0.5842%83
058%
130%
29%
32%
4+1%
Will LankshearFWDMiddlesbrough0.6865provisional0.5139%59
061%
129%
28%
32%
4+0%
Leo CastledineMIDMiddlesbrough0.9739provisional0.4836%12
064%
126%
27%
32%
4+0%
Andri GudjohnsenFWDBlackburn Rovers0.6657provisional0.4535%26
065%
126%
27%
31%
4+0%
Kyle JosephFWDMiddlesbrough0.5862provisional0.4234%63
066%
126%
26%
31%
4+0%
Ryoya MorishitaMIDBlackburn Rovers0.4674provisional0.3932%38
068%
126%
25%
31%
4+0%
Todd CantwellMIDBlackburn Rovers0.5263provisional0.3931%66
069%
125%
25%
31%
4+0%

10 of 57 players shown, ranked by projection. Show all 57 →

Fouls won57 playersHighest: Aidan Morris, 1.95 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.

PlayerTeamModel /90Exp. minsProjectedOver 1.5nDistribution
Aidan MorrisMIDMiddlesbrough2.0884provisional1.9557%78
016%
127%
225%
317%
49%
54%
6+2%
Todd CantwellMIDBlackburn Rovers1.7863provisional1.3136%66
032%
131%
220%
310%
44%
52%
6+1%
Tommy ConwayFWDMiddlesbrough1.4676provisional1.2636%84
030%
134%
221%
310%
43%
51%
6+0%
Oladapo AfolayanFWDBlackburn Rovers2.3344provisional1.2534%48
036%
131%
218%
39%
44%
52%
6+1%
Will LankshearFWDMiddlesbrough1.5865provisional1.1833%59
034%
132%
220%
39%
43%
51%
6+0%
Morgan WhittakerFWDMiddlesbrough1.3676provisional1.1733%80
033%
134%
220%
39%
43%
51%
6+0%
Luke AylingDEFMiddlesbrough1.2682provisional1.1632%73
033%
135%
220%
38%
43%
51%
6+0%
Lewis MillerDEFBlackburn Rovers1.4265provisional1.0629%29
039%
132%
217%
38%
43%
51%
6+0%
Alex BanguraDEFMiddlesbrough1.8245provisional1.0027%13
042%
131%
216%
37%
43%
51%
6+0%
Myles Peart-HarrisMIDMiddlesbrough1.7346provisional0.9625%50
044%
131%
215%
36%
42%
51%
6+0%

10 of 57 players shown, ranked by projection. Show all 57 →

Saves4 playersHighest: Radek Vitek, 3.05 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.

PlayerTeamModel /90Exp. minsProjectedOver 2.5nDistribution
Radek VitekGKMiddlesbrough3.0889provisional3.0556%42
06%
116%
221%
320%
415%
510%
6+11%
Balázs TóthGKBlackburn Rovers2.5689provisional2.5345%41
010%
121%
224%
319%
413%
57%
6+6%
Sol BrynnGKMiddlesbrough2.4889provisional2.4644%55
010%
122%
224%
319%
412%
57%
6+5%
Aynsley PearsGKBlackburn Rovers2.1588provisional2.1135%53
014%
126%
225%
317%
410%
55%
6+3%

2 of 7 markets have no projection for this fixture.