PER90

Serie A · Italy

AtalantavSassuolo

Gewiss Stadiumexpected lineup

Referee

Valerio Crezzini

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

Fouls per game

26.8

+16% 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 — 7 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

Fouls47 playersHighest: Nikola Krstović, 1.62 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
Nikola KrstovićFWDAtalanta1.8874provisional1.6247%70
022%
131%
224%
314%
46%
52%
6+1%
Kieron BowieFWD1.7084provisional1.6248%14
020%
132%
225%
314%
46%
52%
6+1%
Isak HienDEFAtalanta1.4277provisional1.2736%58
030%
134%
222%
310%
43%
51%
6+0%
Honest AhanorDEFAtalanta1.5165provisional1.1833%28
032%
135%
220%
39%
43%
51%
6+0%
Sead KolasinacDEFAtalanta1.4965provisional1.1632%42
034%
134%
220%
38%
43%
51%
6+0%
Marten de RoonMIDAtalanta1.2283provisional1.1532%70
032%
136%
221%
38%
42%
51%
6+0%
Giorgio ScalviniDEFAtalanta1.3273provisional1.1331%30
033%
135%
220%
38%
42%
51%
6+0%
ÉdersonMIDAtalanta1.1879provisional1.0729%67
035%
136%
219%
37%
42%
50%
6+0%
Armand LaurientéFWDSassuolo1.2472provisional1.0528%38
036%
136%
219%
37%
42%
50%
6+0%
Gianluca ScamaccaFWDAtalanta1.5851provisional1.0428%25
038%
134%
218%
37%
42%
51%
6+0%

10 of 47 players shown, ranked by projection. Show all 47 →

Shots47 playersHighest: Nikola Krstović, 3.98 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
Nikola KrstovićFWDAtalanta4.7174provisional3.9885%70
04%
110%
215%
317%
416%
513%
6+24%
Gianluca ScamaccaFWDAtalanta3.7951provisional2.3762%25
015%
123%
222%
316%
411%
57%
6+7%
Giacomo RaspadoriFWDAtalanta3.3257provisional2.2458%51
019%
123%
220%
315%
410%
56%
6+6%
Kieron BowieFWD1.9784provisional1.8654%14
017%
129%
226%
316%
48%
53%
6+2%
Kamaldeen SulemanaFWDAtalanta2.6847provisional1.5642%51
028%
129%
220%
312%
46%
53%
6+2%
Charles De KetelaereMIDAtalanta2.1958provisional1.5243%67
027%
131%
222%
312%
46%
52%
6+1%
Armand LaurientéFWDSassuolo1.8172provisional1.5143%38
025%
132%
223%
312%
45%
52%
6+1%
Andrea PinamontiFWDSassuolo1.8966provisional1.4441%72
028%
131%
221%
312%
45%
52%
6+1%
Lazar SamardžićMIDAtalanta2.6442provisional1.4038%57
031%
131%
219%
310%
45%
52%
6+1%
ÉdersonMIDAtalanta1.5579provisional1.3940%67
027%
133%
222%
311%
44%
51%
6+1%

10 of 47 players shown, ranked by projection. Show all 47 →

Shots on target44 playersHighest: Nikola Krstović, 1.39 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
Nikola KrstovićFWDAtalanta1.6474provisional1.3972%70
028%
132%
222%
311%
44%
52%
6+1%
Gianluca ScamaccaFWDAtalanta1.4951provisional0.9357%25
043%
133%
216%
36%
42%
51%
6+0%
Giacomo RaspadoriFWDAtalanta1.2657provisional0.8553%51
047%
131%
214%
35%
42%
50%
6+0%
Kieron BowieFWD0.7284provisional0.6849%14
051%
134%
212%
33%
41%
5+0%
Kamaldeen SulemanaFWDAtalanta1.0547provisional0.6143%51
057%
129%
210%
33%
41%
5+0%
Charles De KetelaereMIDAtalanta0.8458provisional0.5842%67
058%
130%
29%
32%
4+1%
Andrea PinamontiFWDSassuolo0.7566provisional0.5742%72
058%
130%
29%
32%
4+1%
Armand LaurientéFWDSassuolo0.6872provisional0.5742%38
058%
131%
29%
32%
4+0%
Domenico BerardiFWDSassuolo0.6377provisional0.5642%26
058%
131%
29%
32%
4+0%
Lazar SamardžićMIDAtalanta0.9942provisional0.5339%57
061%
128%
28%
32%
40%
5+0%
ÉdersonMIDAtalanta0.4779provisional0.4234%67
066%
127%
26%
31%
4+0%
Benja DomínguezFWD0.6247provisional0.3629%39
071%
123%
25%
31%
4+0%
Gianluca GaetanoMID0.5058provisional0.3529%61
071%
123%
25%
3+1%
Davide ZappacostaMIDAtalanta0.4464provisional0.3328%65
072%
123%
24%
3+1%
Kristian ThorstvedtMIDSassuolo0.3379provisional0.3026%32
074%
122%
23%
3+0%
Nicola ZalewskiMIDAtalanta0.4259provisional0.3025%56
075%
121%
24%
3+0%
Mario PašalićMIDAtalanta0.4455provisional0.2924%67
076%
120%
23%
3+1%
Cristian VolpatoMIDSassuolo0.5336provisional0.2521%24
079%
118%
23%
3+0%
Giorgio ScalviniDEFAtalanta0.2773provisional0.2320%30
080%
118%
22%
3+0%
Ismaël KonéMIDSassuolo0.2480provisional0.2219%35
081%
117%
22%
3+0%
Raoul BellanovaMIDAtalanta0.3060provisional0.2119%59
081%
116%
22%
3+0%
Honest AhanorDEFAtalanta0.2765provisional0.2118%28
082%
116%
22%
3+0%
Nicholas PieriniFWDSassuolo0.7418provisional0.2018%13
082%
116%
22%
3+0%
Vasilije AdžićMID0.7315provisional0.1715%16
085%
114%
21%
3+0%
Ibrahim SulemanaMIDAtalanta0.3733provisional0.1614%28
086%
113%
21%
3+0%
Marten de RoonMIDAtalanta0.1783provisional0.1615%70
085%
113%
2+1%
Luca MoroFWDSassuolo0.6515provisional0.1614%14
086%
113%
21%
3+0%
Lorenzo BernasconiMIDAtalanta0.2161provisional0.1514%23
086%
113%
2+1%
Berat DjimsitiDEFAtalanta0.1766provisional0.1312%68
088%
111%
2+1%
Isak HienDEFAtalanta0.1577provisional0.1312%58
088%
111%
2+1%
Thomas KristensenDEF0.1483provisional0.1312%52
088%
111%
2+1%
Rafa ObradorDEF0.1573provisional0.1312%16
088%
111%
2+1%
Josh DoigDEFSassuolo0.1671provisional0.1312%30
088%
111%
2+1%
Luca LipaniMIDSassuolo0.2145provisional0.1211%24
089%
110%
2+1%
Ulisses GarciaDEFSassuolo0.1375provisional0.1111%13
089%
110%
2+1%
Odilon KossounouDEFAtalanta0.1943provisional0.1010%37
090%
19%
2+1%
Woyo CoulibalyDEFSassuolo0.1267provisional0.109%38
091%
19%
2+1%
Nemanja MatićMIDSassuolo0.1268provisional0.109%34
091%
19%
2+1%
Sead KolasinacDEFAtalanta0.1165provisional0.088%42
092%
17%
2+0%
Fali CandéDEFSassuolo0.1062provisional0.087%29
093%
17%
2+0%
Aster VranckxMIDSassuolo0.1344provisional0.077%30
093%
17%
2+0%
Edoardo IannoniMIDSassuolo0.2317provisional0.066%15
094%
15%
2+0%
Sebastian WalukiewiczDEFSassuolo0.0676provisional0.065%65
095%
15%
2+0%
Jay IdzesDEFSassuolo0.0688provisional0.065%70
095%
15%
2+0%

All 44 players shown, ranked by projection. Show fewer ↥

Fouls won47 playersHighest: Kristian Thorstvedt, 1.55 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
Kristian ThorstvedtMIDSassuolo1.7379provisional1.5545%32
024%
131%
224%
313%
46%
52%
6+1%
Nicola ZalewskiMIDAtalanta2.1359provisional1.4943%56
026%
131%
222%
312%
45%
52%
6+1%
Kieron BowieFWD1.5484provisional1.4542%14
025%
133%
224%
312%
45%
51%
6+1%
ÉdersonMIDAtalanta1.5679provisional1.3940%67
027%
133%
223%
311%
44%
51%
6+1%
Ismaël KonéMIDSassuolo1.5380provisional1.3840%35
027%
134%
223%
311%
44%
51%
6+0%
Armand LaurientéFWDSassuolo1.6072provisional1.3238%38
029%
134%
222%
310%
44%
51%
6+0%
Benja DomínguezFWD2.2347provisional1.2634%39
036%
130%
218%
39%
44%
52%
6+1%
Domenico BerardiFWDSassuolo1.4177provisional1.2335%26
031%
135%
221%
39%
43%
51%
6+0%
Honest AhanorDEFAtalanta1.6065provisional1.2034%28
033%
134%
220%
39%
43%
51%
6+0%
Nikola KrstovićFWDAtalanta1.3174provisional1.1030%70
036%
134%
219%
38%
42%
51%
6+0%

10 of 47 players shown, ranked by projection. Show all 47 →

Saves3 playersHighest: Arijanet Murić, 3.71 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
Arijanet MurićGKSassuolo3.7489provisional3.7168%50
04%
111%
217%
319%
417%
513%
6+19%
Stefano TuratiGKSassuolo3.3388provisional3.2761%36
05%
114%
220%
320%
416%
511%
6+13%
Marco CarnesecchiGKAtalanta2.5689provisional2.5445%71
010%
121%
224%
320%
413%
57%
6+6%

2 of 7 markets have no projection for this fixture.