PER90

Serie A · Italy

MonzavUdinese

U-Power Stadiumlineups not announced

Referee

Not appointed

0 matches on record

Fouls per game

League average

22.6

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.

  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 v20260813-1451 · Tackles v20260813-1451 · Shots v20260813-1451 · Fouls won v20260813-1451 · Cards v20260813-1451 · Saves v20260813-1451

Model projections

Fouls45 playersHighest: Nicolò Zaniolo, 1.98 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
Nicolò ZanioloFWDUdinese2.5171provisional1.9857%29
017%
126%
224%
317%
49%
54%
6+2%
Armando IzzoDEFMonza1.9882provisional1.8053%28
020%
128%
225%
316%
48%
53%
6+1%
Sandi LovricMIDUdinese2.3359provisional1.5344%35
026%
130%
222%
313%
46%
52%
6+1%
Warren BondoMIDMonzanow at AC Milan1.5781provisional1.4141%19
026%
132%
223%
312%
44%
51%
6+0%
Keinan DavisFWDUdinese2.0959provisional1.3839%40
031%
130%
220%
311%
45%
52%
6+1%
Jean-Daniel Akpa AkproMIDMonza1.7369provisional1.3338%12
030%
132%
222%
311%
44%
51%
6+0%
Christian KabaseleDEFUdinese1.5674provisional1.2937%42
029%
134%
222%
310%
44%
51%
6+0%
Jesper KarlströmMIDUdinese1.3387provisional1.2837%73
028%
135%
222%
310%
43%
51%
6+0%
Pablo Marí VillarDEFMonza1.3086provisional1.2435%19
029%
136%
222%
39%
43%
51%
6+0%
Thomas KristensenDEFUdinese1.3582provisional1.2235%49
031%
134%
221%
39%
43%
51%
6+0%

10 of 45 players shown, ranked by projection. Show all 45 → 2 of the 45 have since left the club — the squad is built from who has played for these teams, not from who is registered today, so they are shown rather than quietly dropped.

Tackles45 playersHighest: Andrea Carboni, 2.09 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.

PlayerTeamModel /90Exp. minsProjectedOver 1.5nDistribution
Andrea CarboniDEFMonza2.2384provisional2.0959%26
016%
126%
224%
317%
410%
55%
6+3%
Oumar Solet BomawokoDEFUdinese1.9686provisional1.8753%52
019%
128%
224%
315%
48%
54%
6+2%
Jean-Daniel Akpa AkproMIDMonza2.4269provisional1.8652%12
022%
126%
222%
315%
48%
54%
6+3%
Warren BondoMIDMonzanow at AC Milan1.7781provisional1.5946%19
025%
130%
223%
313%
46%
52%
6+1%
Jesper KarlströmMIDUdinese1.6287provisional1.5745%73
024%
131%
223%
313%
46%
52%
6+1%
Pedro Miguel Almeida Lopes PereiraDEFMonza1.8177provisional1.5544%32
026%
129%
222%
312%
46%
52%
6+1%
Alessandro BiancoMIDMonza1.7777provisional1.5142%32
027%
131%
222%
312%
46%
52%
6+1%
Matteo PessinaMIDMonza1.6678provisional1.4441%11
027%
132%
222%
311%
45%
52%
6+1%
Kingsley EhizibueDEFUdinese1.9366provisional1.4240%52
032%
128%
219%
311%
45%
52%
6+1%
Pablo Marí VillarDEFMonza1.4686provisional1.3939%19
028%
133%
222%
311%
44%
52%
6+1%
Jurgen EkkelenkampMIDUdinese1.9563provisional1.3738%50
032%
130%
220%
310%
45%
52%
6+1%
Sandi LovricMIDUdinese2.0859provisional1.3738%35
032%
130%
220%
311%
45%
52%
6+1%
Armando IzzoDEFMonza1.5082provisional1.3639%28
030%
131%
221%
311%
44%
52%
6+1%
Danilo D'AmbrosioDEFMonza2.2155provisional1.3436%13
038%
126%
217%
310%
45%
52%
6+2%
Giorgos KiriakopoulosDEFMonza1.4384provisional1.3338%34
029%
133%
222%
310%
44%
51%
6+1%
Nicolò BertolaDEFUdinese1.8863provisional1.3136%23
034%
130%
219%
310%
45%
52%
6+1%
Jakub PiotrowskiMIDUdinese2.2852provisional1.3035%22
035%
130%
218%
310%
45%
52%
6+1%
Alessandro ZanoliDEFUdinese1.6568provisional1.2535%17
033%
132%
220%
39%
44%
51%
6+1%
Hassane KamaraDEFUdinese1.5769provisional1.2133%47
035%
132%
219%
39%
44%
51%
6+1%
Thomas KristensenDEFUdinese1.2682provisional1.1431%49
036%
133%
219%
38%
43%
51%
6+0%
Samuele BirindelliDEFMonza1.3970provisional1.0830%18
039%
132%
218%
38%
43%
51%
6+0%
Patrick CiurriaMIDMonza1.8553provisional1.0829%13
044%
127%
215%
38%
44%
51%
6+1%
Gaetano CastrovilliMIDMonza1.8650provisional1.0327%10
041%
132%
216%
37%
43%
51%
6+0%
Luca CaldirolaDEFMonza1.4863provisional1.0327%12
040%
133%
217%
37%
42%
51%
6+0%
Lennon MillerMIDUdinese2.1941provisional1.0026%13
045%
129%
214%
37%
43%
51%
6+1%
Nicolò ZanioloFWDUdinese1.1771provisional0.9224%29
043%
133%
216%
36%
42%
50%
6+0%
Rui Manuel Muati ModestoMIDUdinese2.5331provisional0.8821%9
048%
130%
212%
35%
42%
51%
6+1%
Christian KabaseleDEFUdinese1.0574provisional0.8722%42
044%
133%
215%
35%
41%
50%
6+0%
Daniel MaldiniMIDMonzanow at Cagliari1.1866provisional0.8622%17
046%
132%
215%
35%
42%
50%
6+0%
Oier Zarraga EgañaMIDUdinese1.9529provisional0.6314%16
060%
126%
29%
33%
41%
51%
6+0%
Gianluca CaprariFWDMonza1.1449provisional0.6214%20
058%
127%
210%
33%
41%
5+0%
Stefano SensiMIDMonza2.3823provisional0.6013%3
060%
127%
29%
33%
41%
50%
6+0%
Keita Baldé DiaoFWDMonza0.8259provisional0.5411%7
061%
128%
29%
32%
4+1%
Dany Mota CarvalhoFWDMonza0.6768provisional0.5110%27
062%
128%
28%
32%
4+0%
Samuele VignatoMIDMonza1.6027provisional0.4810%4
066%
124%
27%
32%
41%
5+0%
Juan David ArizalaMIDUdinese2.0118provisional0.417%1
070%
123%
25%
31%
40%
5+0%
Keinan DavisFWDUdinese0.5959provisional0.397%40
069%
124%
26%
31%
4+0%
Adam BuksaFWDUdinese0.7336provisional0.294%10
076%
120%
24%
31%
4+0%
Milan ĐurićFWDMonza0.2771provisional0.212%17
081%
117%
22%
3+0%
Idrissa GueyeFWDUdinese0.8421provisional0.202%3
083%
115%
22%
3+0%
Andrea PetagnaFWDMonza0.6125provisional0.172%3
085%
113%
22%
3+0%
Vakoun Issouf BayoFWDUdinese0.4532provisional0.162%6
086%
112%
22%
3+0%
Razvan SavaGKUdinese0.0189provisional0.0119
099%
1+1%
Stefano TuratiGKMonza0.0089provisional0.0030
0100%
1+0%
Maduka OkoyeGKUdinese0.0088provisional0.0054
0100%
1+0%

All 45 players shown, ranked by projection. Show fewer ↥ 2 of the 45 have since left the club — the squad is built from who has played for these teams, not from who is registered today, so they are shown rather than quietly dropped.

Shots45 playersHighest: Nicolò Zaniolo, 2.17 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
Nicolò ZanioloFWDUdinese2.7571provisional2.1760%29
016%
124%
223%
317%
410%
55%
6+4%
Daniel MaldiniMIDMonzanow at Cagliari2.9466provisional2.1459%17
018%
124%
222%
317%
410%
55%
6+4%
Milan ĐurićFWDMonza2.3171provisional1.8151%17
021%
128%
223%
315%
48%
54%
6+2%
Dany Mota CarvalhoFWDMonza2.3068provisional1.7449%27
022%
129%
223%
314%
47%
53%
6+2%
Keita Baldé DiaoFWDMonza2.5459provisional1.6747%7
026%
127%
221%
313%
47%
53%
6+2%
Keinan DavisFWDUdinese2.2759provisional1.5042%40
030%
128%
220%
312%
46%
53%
6+1%
Gianluca CaprariFWDMonza2.4249provisional1.3135%20
036%
129%
217%
310%
45%
52%
6+1%
Sandi LovricMIDUdinese1.7059provisional1.1231%35
037%
132%
218%
38%
43%
51%
6+0%
Jakub PiotrowskiMIDUdinese1.8452provisional1.0528%22
040%
131%
217%
37%
43%
51%
6+0%
Alessandro BiancoMIDMonza1.1177provisional0.9425%32
041%
134%
217%
36%
42%
50%
6+0%

10 of 45 players shown, ranked by projection. Show all 45 → 2 of the 45 have since left the club — the squad is built from who has played for these teams, not from who is registered today, so they are shown rather than quietly dropped.

Fouls won45 playersHighest: Nicolò Zaniolo, 2.02 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
Nicolò ZanioloFWDUdinese2.5671provisional2.0257%29
018%
125%
223%
317%
49%
55%
6+3%
Daniel MaldiniMIDMonzanow at Cagliari2.6666provisional1.9454%17
020%
126%
222%
316%
49%
54%
6+3%
Warren BondoMIDMonzanow at AC Milan2.0081provisional1.8052%19
020%
128%
224%
315%
48%
53%
6+2%
Keita Baldé DiaoFWDMonza2.6759provisional1.7649%7
025%
127%
221%
314%
48%
54%
6+2%
Alessandro BiancoMIDMonza2.0277provisional1.7249%32
022%
129%
223%
314%
47%
53%
6+2%
Armando IzzoDEFMonza1.6882provisional1.5244%28
025%
131%
223%
313%
45%
52%
6+1%
Gianluca CaprariFWDMonza2.5349provisional1.3737%20
035%
128%
218%
310%
45%
52%
6+1%
Jean-Daniel Akpa AkproMIDMonza1.7669provisional1.3639%12
030%
131%
221%
311%
44%
52%
6+1%
Dany Mota CarvalhoFWDMonza1.7468provisional1.3137%27
031%
132%
221%
310%
44%
51%
6+1%
Matteo PessinaMIDMonza1.4878provisional1.2836%11
030%
134%
221%
310%
44%
51%
6+0%

10 of 45 players shown, ranked by projection. Show all 45 → 2 of the 45 have since left the club — the squad is built from who has played for these teams, not from who is registered today, so they are shown rather than quietly dropped.

Cards45 playersHighest: Nicolò Zaniolo, 0.26 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.

PlayerTeamModel /90Exp. minsProjectedOver 0.5nDistribution
Nicolò ZanioloFWDUdinese0.3371provisional0.2623%29
077%
120%
23%
3+0%
Armando IzzoDEFMonza0.2882provisional0.2522%28
078%
119%
23%
3+0%
Pedro Miguel Almeida Lopes PereiraDEFMonza0.2577provisional0.2119%32
081%
117%
22%
3+0%
Jesper KarlströmMIDUdinese0.2287provisional0.2119%73
081%
117%
22%
3+0%
Luca CaldirolaDEFMonza0.2863provisional0.1917%12
083%
115%
22%
3+0%
Jean-Daniel Akpa AkproMIDMonza0.2469provisional0.1917%12
083%
115%
22%
3+0%
Thomas KristensenDEFUdinese0.2082provisional0.1817%49
083%
115%
21%
3+0%
Sandi LovricMIDUdinese0.2859provisional0.1817%35
083%
115%
22%
3+0%
Alessandro BiancoMIDMonza0.2177provisional0.1816%32
084%
115%
21%
3+0%
Christian KabaseleDEFUdinese0.2274provisional0.1816%42
084%
115%
2+1%

10 of 45 players shown, ranked by projection. Show all 45 → 2 of the 45 have since left the club — the squad is built from who has played for these teams, not from who is registered today, so they are shown rather than quietly dropped.

Saves3 playersHighest: Razvan Sava, 2.87 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
Razvan SavaGKUdinese2.8889provisional2.8753%19
08%
118%
222%
320%
415%
59%
6+9%
Maduka OkoyeGKUdinese2.9188provisional2.8653%54
08%
118%
222%
320%
415%
59%
6+9%
Stefano TuratiGKMonza2.6189provisional2.5947%30
09%
120%
224%
320%
413%
57%
6+6%

1 of 7 markets have no projection for this fixture.