Serie A · Italy

NapolivComo

Sunday 30 August at 17:30Stadio Diego Armando Maradonalineups 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.

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

Model projections

Fouls52 playersHighest: Nicolás Paz Martínez, 1.46 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
Nicolás Paz MartínezMID	Como	1.65	80provisional	1.46	42%	63	026% 132% 223% 312% 45% 52% 6+1%
Diego Carlos Santos SilvaDEF	Como	1.71	72provisional	1.37	39%	24	028% 133% 222% 311% 44% 51% 6+1%
Edoardo GoldanigaDEF	Como	1.59	75provisional	1.33	38%	28	032% 130% 221% 311% 44% 51% 6+1%
Alieu FaderaFWD	Como	1.99	59provisional	1.30	37%	20	035% 128% 219% 311% 45% 52% 6+1%
Juan Guilherme Nunes JesusDEF	Napoli	1.63	71provisional	1.28	37%	32	033% 130% 220% 310% 44% 51% 6+0%
Antonio VergaraMID	Napoli	2.21	51provisional	1.26	36%	8	040% 124% 218% 311% 45% 52% 6+1%
Giovanni Di LorenzoDEF	Napoli	1.26	89provisional	1.25	35%	63	029% 135% 222% 39% 43% 51% 6+0%
Alessandro BuongiornoDEF	Napoli	1.37	81provisional	1.23	35%	50	031% 134% 221% 39% 43% 51% 6+0%
Romelu Lukaku MenamaFWD	Napoli	1.55	71provisional	1.22	35%	35	034% 132% 221% 310% 43% 51% 6+0%
Rasmus Winther HøjlundFWD	Napoli	1.26	84provisional	1.18	33%	32	032% 135% 221% 38% 43% 51% 6+0%

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

Tackles52 playersHighest: Nicolás Paz Martínez, 1.96 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.

Player	Team	Model /90	Exp. mins	Projected	Over 1.5	n	Distribution
Nicolás Paz MartínezMID	Como	2.21	80provisional	1.96	55%	63	019% 126% 223% 315% 49% 54% 6+3%
Mathías Olivera MiramontesDEF	Napoli	2.61	66provisional	1.90	51%	46	023% 126% 220% 314% 48% 54% 6+4%
Alieu FaderaFWD	Como	2.79	59provisional	1.82	48%	20	028% 124% 219% 313% 48% 54% 6+4%
Álex Valle GómezDEF	Como	2.28	71provisional	1.80	50%	36	025% 126% 221% 314% 48% 54% 6+3%
Giovanni Di LorenzoDEF	Napoli	1.79	89provisional	1.77	51%	63	020% 129% 224% 315% 47% 53% 6+2%
Ignace Van Der BremptDEF	Como	2.76	55provisional	1.68	44%	25	031% 125% 218% 312% 47% 54% 6+3%
Juan Guilherme Nunes JesusDEF	Napoli	2.11	71provisional	1.66	46%	32	028% 126% 220% 313% 47% 53% 6+2%
Maximo PerroneMID	Como	1.96	74provisional	1.62	46%	57	025% 130% 222% 313% 46% 53% 6+2%
Jacobo Ramón NaverosDEF	Como	1.67	86provisional	1.59	45%	32	024% 131% 223% 313% 46% 52% 6+1%
Maxence CaqueretMID	Como	2.55	54provisional	1.52	42%	38	028% 130% 220% 312% 46% 53% 6+2%

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

Shots52 playersHighest: Nicolás Paz Martínez, 2.38 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
Nicolás Paz MartínezMID	Como	2.69	80provisional	2.38	65%	63	013% 122% 223% 318% 412% 57% 6+5%
Scott McTominayMID	Napoli	2.42	86provisional	2.30	64%	65	012% 123% 224% 319% 411% 56% 6+4%
Rasmus Winther HøjlundFWD	Napoli	2.01	84provisional	1.87	54%	32	018% 128% 225% 316% 48% 53% 6+2%
Alisson de Almeida SantosFWD	Napoli	2.54	60provisional	1.69	47%	11	024% 129% 222% 313% 47% 53% 6+2%
Romelu Lukaku MenamaFWD	Napoli	2.02	71provisional	1.60	46%	35	026% 128% 222% 313% 46% 53% 6+1%
Kevin De BruyneMID	Napoli	2.00	65provisional	1.45	41%	17	026% 132% 222% 312% 45% 52% 6+1%
Assane Diao DiaouneFWD	Como	1.75	73provisional	1.42	41%	31	026% 133% 223% 311% 45% 52% 6+1%
Matteo PolitanoFWD	Napoli	1.78	71provisional	1.41	40%	62	029% 131% 222% 311% 45% 52% 6+1%
Anastasios DouvikasFWD	Como	2.10	56provisional	1.31	36%	37	033% 131% 219% 310% 44% 52% 6+1%
Jesús Rodríguez CaraballoFWD	Como	1.94	56provisional	1.20	33%	26	035% 132% 219% 39% 44% 51% 6+1%

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

Fouls won52 playersHighest: Assane Diao Diaoune, 2.53 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 Diao DiaouneFWD	Como	3.11	73provisional	2.53	68%	31	011% 121% 223% 319% 413% 57% 6+6%
Scott McTominayMID	Napoli	2.20	86provisional	2.09	60%	65	015% 126% 225% 318% 410% 55% 6+3%
Rasmus Winther HøjlundFWD	Napoli	1.87	84provisional	1.74	51%	32	020% 130% 225% 315% 47% 53% 6+1%
Alieu FaderaFWD	Como	2.60	59provisional	1.70	47%	20	028% 125% 220% 314% 48% 54% 6+3%
Antonio VergaraMID	Napoli	2.69	51provisional	1.53	42%	8	036% 122% 218% 312% 47% 53% 6+2%
Martin BaturinaMID	Como	2.30	55provisional	1.40	38%	21	033% 128% 218% 311% 45% 52% 6+1%
Stanislav LobotkaMID	Napoli	1.44	79provisional	1.27	36%	61	030% 134% 221% 310% 43% 51% 6+0%
Giovanni Di LorenzoDEF	Napoli	1.26	89provisional	1.24	35%	63	030% 135% 221% 39% 43% 51% 6+0%
Anastasios DouvikasFWD	Como	1.88	56provisional	1.17	32%	37	037% 131% 218% 39% 43% 51% 6+1%
Jayden AddaiFWD	Como	1.81	57provisional	1.15	31%	10	036% 133% 218% 38% 43% 51% 6+0%

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

Cards52 playersHighest: Edoardo Goldaniga, 0.25 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.

Player	Team	Model /90	Exp. mins	Projected	Over 0.5	n	Distribution
Edoardo GoldanigaDEF	Como	0.30	75provisional	0.25	22%	28	078% 119% 23% 3+0%
Jacobo Ramón NaverosDEF	Como	0.26	86provisional	0.24	22%	32	078% 119% 22% 3+0%
Diego Carlos Santos SilvaDEF	Como	0.29	72provisional	0.24	21%	24	079% 118% 22% 3+0%
Juan Guilherme Nunes JesusDEF	Napoli	0.29	71provisional	0.23	20%	32	080% 117% 22% 3+0%
Ivan SmolčićDEF	Como	0.30	62provisional	0.21	18%	29	082% 116% 22% 3+0%
Maximo PerroneMID	Como	0.24	74provisional	0.20	18%	57	082% 116% 22% 3+0%
Jayden AddaiFWD	Como	0.27	57provisional	0.17	15%	10	085% 114% 21% 3+0%
Álex Valle GómezDEF	Como	0.20	71provisional	0.16	14%	36	086% 113% 2+1%
Alieu FaderaFWD	Como	0.23	59provisional	0.15	14%	20	086% 112% 2+1%
Assane Diao DiaouneFWD	Como	0.18	73provisional	0.15	14%	31	086% 113% 2+1%

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

Saves3 playersHighest: Jean Butez, 2.79 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
Jean ButezGK	Como	2.81	89provisional	2.79	51%	57	08% 118% 223% 320% 414% 59% 6+8%
Vanja Milinković SavićGK	Napoli	2.27	90provisional	2.27	39%	27	012% 124% 225% 318% 411% 56% 6+4%
Alex MeretGK	Napoli	2.09	89provisional	2.06	34%	45	015% 126% 225% 317% 49% 54% 6+3%

1 of 7 markets have no projection for this fixture.