Serie A · Italy

UdinesevComo

Saturday 22 August at 17:30Dacia Arenaexpected lineup

Referee

Alberto Arena

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

Fouls per game

22.6

-3% vs league

League average

23.2

fouls per match, both teams

Angles

every priced line builder

formNicolò Zaniolo over 0.5 shots on target: 7/10 of his last 10, 5 in a row
Last 20: 9/20 · 3/5 at home · strip 1 1 1 1 1 0 2 0 0 1 · market 56% · best 1.80 (Ladbrokes) · bet365 1.80
formOumar Solet over 1.5 tackles: 8/10 of his last 10, 4 in a row
Last 20: 15/20 · 4/4 at home · strip 2 3 3 6 0 2 4 3 2 0 · market 67% · best 1.50 (10Bet) · bet365 1.36
formJacobo Ramón over 0.5 fouls: 8/10 of his last 10, 5 in a row
Last 20: 13/20 · 5/5 away · strip 1 2 1 1 2 0 1 2 0 2 · market 69% · best 1.44 (Parimatch) · bet365 1.20
formAnastasios Douvikas over 0.5 shots on target: 8/10 of his last 10, 5 in a row
Last 20: 13/20 · 4/5 away · strip 2 1 1 1 1 0 0 1 1 1 · market 78% · best 1.44 (Coral) · bet365 1.25
opponentComo concede 18.7 tackles a game — 2nd most of 23 in Serie A
Over their last 10. Good news for Udinese's tacklers.
refereeAlberto Arena: 22.6 fouls and 3.3 cards a game (league 25.3 / 3.5)
-2.7 fouls and -0.3 cards against his league's average over his last 12. Lets play flow — leans fouls unders.
opponentUdinese concede 14.7 shots a game — 3rd most of 23 in Serie A
Over their last 10. Good news for Como's shooters.
opponentComo concede 2.2 shots on target a game — 23rd most of 23 in Serie A
Over their last 10. A hard place to get shots on target.

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 — 2 live calls

Jesper Karlströmover 0.50 Fouls1.33 at bet365 · fair 1.22+9.3%
Jurgen Ekkelenkampover 1.50 Shots2.63 at bet365 · fair 2.45+7.1%

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

Fouls57 playersHighest: Nicolò Zaniolo, 1.47 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
Nicolò ZanioloFWD	Udinese	1.93	63provisional	1.47	42%	55	026% 131% 222% 312% 45% 52% 6+1%
Keinan DavisFWD	Udinese	1.62	66provisional	1.29	37%	53	030% 133% 221% 310% 44% 51% 6+0%
Sandi LovrićMID	Udinese	1.66	63provisional	1.28	36%	50	030% 134% 222% 310% 44% 51% 6+0%
Nico PazMID	Como	1.35	82provisional	1.25	36%	70	030% 135% 222% 39% 43% 51% 6+0%
Jesper KarlströmMID	Udinese	1.28	86provisional	1.24	35%	73	029% 135% 222% 39% 43% 51% 6+0%
Diego CarlosDEF	Como	1.49	67provisional	1.19	33%	37	033% 134% 220% 39% 43% 51% 6+0%
James AbankwahDEF	Udinese	1.33	77provisional	1.18	33%	56	032% 135% 221% 39% 43% 51% 6+0%
Adam BuksaFWD	Udinese	2.08	42provisional	1.16	32%	25	035% 133% 218% 38% 43% 51% 6+0%
Kingsley EhizibueDEF	Udinese	1.34	73provisional	1.14	31%	65	034% 134% 220% 38% 43% 51% 6+0%
Enzo EbosseDEF	Udinese	1.28	76provisional	1.13	31%	19	034% 135% 220% 38% 42% 51% 6+0%

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

Shots57 playersHighest: Nico Paz, 2.71 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
Nico PazMID	Como	2.94	82provisional	2.71	72%	70	09% 119% 223% 320% 414% 58% 6+8%
Iván AzónFWD	—	2.93	48provisional	1.73	47%	38	024% 128% 221% 313% 47% 54% 6+3%
Assane DiaoFWD	Como	2.08	68provisional	1.65	47%	42	023% 130% 223% 314% 47% 53% 6+1%
Nicolò ZanioloFWD	Udinese	2.20	63provisional	1.63	46%	55	025% 129% 222% 313% 47% 53% 6+2%
Anastasios DouvikasFWD	Como	2.18	60provisional	1.55	44%	71	026% 130% 222% 312% 46% 52% 6+1%
Keinan DavisFWD	Udinese	1.88	66provisional	1.46	42%	53	027% 131% 222% 312% 45% 52% 6+1%
Jesús RodríguezFWD	Como	1.89	52provisional	1.20	33%	52	035% 132% 219% 39% 44% 51% 6+1%
Martin BaturinaMID	Como	1.58	64provisional	1.19	33%	29	035% 132% 219% 39% 43% 51% 6+0%
Lucas Da CunhaMID	Como	1.23	77provisional	1.08	29%	72	036% 135% 219% 37% 42% 51% 6+0%
Giorgi ChakvetadzeMID	—	1.23	77provisional	1.08	29%	68	036% 135% 219% 37% 42% 51% 6+0%

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

Shots on target53 playersHighest: Nico Paz, 1.01 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
Nico PazMID	Como	1.10	82provisional	1.01	62%	70	038% 135% 218% 37% 42% 50% 6+0%
Assane DiaoFWD	Como	0.83	68provisional	0.66	47%	42	053% 132% 211% 33% 41% 5+0%
Anastasios DouvikasFWD	Como	0.90	60provisional	0.64	45%	71	055% 131% 211% 33% 41% 5+0%
Keinan DavisFWD	Udinese	0.82	66provisional	0.63	45%	53	055% 131% 211% 33% 41% 5+0%
Iván AzónFWD	—	1.07	48provisional	0.63	44%	38	056% 130% 210% 33% 41% 5+0%
Nicolò ZanioloFWD	Udinese	0.72	63provisional	0.54	40%	55	060% 129% 29% 32% 4+0%
Martin BaturinaMID	Como	0.54	64provisional	0.40	32%	29	068% 125% 26% 31% 4+0%
Jesús RodríguezFWD	Como	0.62	52provisional	0.39	31%	52	069% 125% 26% 31% 4+0%
Lucas Da CunhaMID	Como	0.43	77provisional	0.38	31%	72	069% 125% 25% 3+1%
Giorgi ChakvetadzeMID	—	0.44	77provisional	0.38	31%	68	069% 125% 25% 3+1%

10 of 53 players shown, ranked by projection. Show all 53 →

Fouls won57 playersHighest: Assane Diao, 2.35 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
Assane DiaoFWD	Como	2.99	68provisional	2.35	64%	42	013% 122% 223% 318% 412% 56% 6+5%
Nicolò ZanioloFWD	Udinese	2.64	63provisional	1.94	54%	55	020% 126% 222% 315% 49% 54% 6+3%
Martin BaturinaMID	Como	2.34	64provisional	1.74	49%	29	023% 128% 222% 314% 47% 53% 6+2%
Keinan DavisFWD	Udinese	1.84	66provisional	1.41	40%	53	028% 131% 222% 311% 45% 52% 6+1%
Giorgi ChakvetadzeMID	—	1.57	77provisional	1.37	39%	68	027% 133% 223% 311% 44% 51% 6+0%
Alieu FaderaFWD	Como	2.84	36provisional	1.28	34%	56	035% 131% 217% 39% 44% 52% 6+1%
Jesús RodríguezFWD	Como	2.04	52provisional	1.28	35%	52	033% 132% 220% 310% 44% 51% 6+1%
Anastasios DouvikasFWD	Como	1.81	60provisional	1.27	35%	71	032% 132% 220% 310% 44% 51% 6+1%
Nico PazMID	Como	1.27	82provisional	1.16	32%	70	033% 135% 220% 38% 43% 51% 6+0%
Luis MillaMID	—	1.19	87provisional	1.16	32%	70	032% 135% 220% 38% 43% 51% 6+0%
Álvaro MorataFWD	Como	2.48	37provisional	1.15	30%	42	039% 131% 216% 38% 44% 52% 6+1%
Saba GoglichidzeDEF	Udinese	1.32	76provisional	1.15	32%	53	034% 134% 220% 38% 43% 51% 6+0%
Lennon MillerMID	Udinese	1.66	55provisional	1.09	29%	24	039% 132% 218% 38% 43% 51% 6+0%
Jakub PiotrowskiMID	Udinese	1.51	60provisional	1.07	29%	33	038% 133% 218% 37% 42% 51% 6+0%
James AbankwahDEF	Udinese	1.16	77provisional	1.01	27%	56	038% 134% 218% 37% 42% 50% 6+0%
Jayden AddaiFWD	Como	1.81	44provisional	0.97	25%	12	042% 133% 216% 36% 42% 51% 6+0%
Edoardo GoldanigaDEF	Como	1.58	51provisional	0.94	25%	34	047% 129% 214% 37% 43% 51% 6+0%
Kingsley EhizibueDEF	Udinese	1.11	73provisional	0.92	24%	65	042% 134% 216% 36% 42% 5+0%
Christian KabaseleDEF	Udinese	1.05	76provisional	0.91	23%	46	042% 135% 216% 35% 41% 5+0%
Sandi LovrićMID	Udinese	1.18	63provisional	0.87	22%	50	044% 134% 215% 35% 41% 5+0%
Jesper KarlströmMID	Udinese	0.89	86provisional	0.86	21%	73	043% 135% 215% 35% 41% 5+0%
Maxence CaqueretMID	Como	1.39	51provisional	0.86	22%	48	045% 133% 215% 35% 41% 5+0%
Oumar SoletDEF	Udinese	0.89	86provisional	0.85	21%	54	043% 135% 215% 35% 41% 5+0%
Alberto MorenoDEF	Como	1.00	73provisional	0.84	21%	43	045% 134% 215% 35% 41% 5+0%
Ignace Van der BremptDEF	Como	1.35	52provisional	0.83	21%	40	048% 130% 214% 35% 42% 50% 6+0%
Álex ValleDEF	Como	0.96	76provisional	0.83	21%	43	046% 134% 215% 35% 41% 5+0%
Iván AzónFWD	—	1.39	48provisional	0.80	20%	38	048% 132% 213% 35% 41% 5+0%
Luca MazzitelliMID	Como	1.49	42provisional	0.76	19%	29	051% 130% 213% 34% 41% 50% 6+0%
Máximo PerroneMID	Como	0.83	77provisional	0.73	17%	62	049% 134% 213% 33% 41% 5+0%
Jurgen EkkelenkampMID	Udinese	0.92	69provisional	0.73	17%	65	050% 133% 213% 33% 41% 5+0%
Adam BuksaFWD	Udinese	1.40	42provisional	0.72	17%	25	052% 131% 212% 34% 41% 5+0%
Lucas Da CunhaMID	Como	0.81	77provisional	0.71	16%	72	050% 133% 212% 33% 41% 5+0%
Marc Oliver KempfDEF	Como	0.79	79provisional	0.70	16%	65	051% 133% 212% 33% 41% 5+0%
Enzo EbosseDEF	Udinese	0.79	76provisional	0.69	15%	19	051% 133% 212% 33% 41% 5+0%
Alberto DossenaDEF	Como	0.88	67provisional	0.68	16%	35	053% 131% 212% 33% 41% 5+0%
Sergi RobertoMID	Como	1.55	31provisional	0.61	13%	33	058% 129% 29% 33% 41% 5+0%
Hassane KamaraDEF	Udinese	0.73	73provisional	0.61	13%	56	056% 132% 210% 32% 4+0%
Jacobo RamónDEF	Como	0.58	84provisional	0.54	11%	35	059% 131% 29% 32% 4+0%
Vakoun BayoFWD	Udinese	1.18	37provisional	0.54	12%	56	061% 127% 28% 32% 41% 5+0%
Unai GómezMID	—	0.88	49provisional	0.53	10%	58	061% 129% 28% 32% 4+0%
Ivan SmolcicDEF	Como	0.78	57provisional	0.52	11%	37	062% 128% 28% 32% 4+0%
Idrissa GueyeFWD	Udinese	1.78	20provisional	0.51	10%	19	061% 129% 28% 32% 40% 5+0%
Alessandro ZanoliDEF	Udinese	0.63	66provisional	0.48	9%	50	063% 128% 27% 31% 4+0%
Trevoh ChalobahDEF	—	0.67	55provisional	0.43	8%	59	067% 125% 27% 31% 4+0%
Mërgim VojvodaDEF	Como	0.65	55provisional	0.42	7%	58	067% 126% 26% 31% 4+0%
Yan CoutoDEF	—	0.94	35provisional	0.42	8%	40	068% 124% 26% 31% 4+0%
Alessandro GabrielloniFWD	Como	1.88	13provisional	0.38	6%	15	069% 125% 25% 3+1%
Nicolò BertolaDEF	Udinese	0.66	47provisional	0.37	6%	28	070% 123% 25% 31% 4+0%
Juan ArizalaMID	Udinese	0.92	31provisional	0.37	6%	10	072% 122% 25% 31% 4+0%
Oier ZarragaMID	Udinese	1.04	25provisional	0.34	6%	46	073% 122% 24% 31% 4+0%
Diego CarlosDEF	Como	0.39	67provisional	0.30	4%	37	074% 122% 24% 3+1%
Rui ModestoMID	Udinese	0.66	27provisional	0.24	3%	23	079% 118% 22% 3+0%
Jean ButezGK	Como	0.23	88provisional	0.22	2%	57	080% 118% 22% 3+0%
Nicolas KühnFWD	Como	0.62	25provisional	0.21	2%	23	082% 116% 22% 3+0%
Emil AuderoGK	Como	0.18	89provisional	0.18	2%	42	083% 115% 2+2%
Maduka OkoyeGK	Udinese	0.15	88provisional	0.14	1%	55	087% 112% 2+1%
Răzvan SavaGK	Udinese	0.09	74provisional	0.07	0%	19	093% 17% 2+0%

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

Saves4 playersHighest: Emil Audero, 3.31 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
Emil AuderoGK	Como	3.34	89provisional	3.31	61%	42	05% 114% 220% 320% 416% 511% 6+14%
Jean ButezGK	Como	2.64	88provisional	2.60	47%	57	09% 120% 223% 320% 413% 57% 6+7%
Maduka OkoyeGK	Udinese	2.65	88provisional	2.60	47%	55	09% 120% 224% 320% 413% 57% 6+7%
Răzvan SavaGK	Udinese	2.56	74provisional	2.18	37%	19	016% 125% 223% 317% 410% 55% 6+4%

2 of 7 markets have no projection for this fixture.