Serie A · Italy

ParmavCagliari

Saturday 22 August at 19:45Stadio Ennio Tardiniexpected lineup

Referee

Daniele Perenzoni

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

Fouls per game

25.5

+10% vs league

League average

23.2

fouls per match, both teams

Angles

every priced line builder

formHarry Winks over 0.5 shots: 8/10 of his last 10, 8 in a row
Last 20: 14/20 · 4/4 away · strip 1 2 1 1 1 3 5 1 0 0 · market 58% · best 1.80 (BetMGM) · bet365 1.73
formAdam Obert over 1.5 tackles: 8/10 of his last 10, 6 in a row
Last 20: 13/20 · 5/5 away · strip 3 2 2 4 3 3 1 3 2 0 · market 71% · best 1.40 (TalkSportBet) · bet365 1.36
formAlessandro Deiola over 0.5 shots: 8/10 of his last 10, 7 in a row
Last 20: 12/20 · 4/5 away · strip 2 2 1 1 1 5 4 0 0 1 · market 80% · best 1.35 (Coral) · bet365 1.30

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

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 v20260816-1555 · Shots v20260816-1555 · Shots on target v20260816-1555 · Fouls won v20260816-1555 · Saves v20260816-1229

Model projections

Fouls45 playersHighest: Gennaro Borrelli, 1.41 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
Gennaro BorrelliFWD	Cagliari	2.28	48provisional	1.41	39%	27	029% 132% 221% 311% 45% 52% 6+1%
Sebastiano EspositoFWD	Cagliari	1.51	75provisional	1.33	38%	69	028% 134% 223% 310% 44% 51% 6+0%
Gabriel StrefezzaFWD	Parma	1.50	74provisional	1.30	37%	51	029% 134% 222% 310% 43% 51% 6+0%
Zito LuvumboFWD	Cagliari	1.76	60provisional	1.29	37%	48	030% 133% 221% 310% 44% 51% 6+0%
Zé PedroDEF	Cagliari	1.38	77provisional	1.22	34%	23	031% 135% 221% 39% 43% 51% 6+0%
Mariano TroiloDEF	Parma	1.28	79provisional	1.16	32%	21	033% 135% 220% 38% 43% 51% 6+0%
Alessandro DeiolaMID	Cagliari	1.42	66provisional	1.12	31%	49	035% 134% 219% 38% 43% 51% 6+0%
HernaniMID	Parma	2.06	39provisional	1.10	30%	29	036% 134% 218% 38% 43% 51% 6+0%
Hans Nicolussi CavigliaMID	Parma	1.26	75provisional	1.10	30%	61	035% 135% 219% 38% 42% 51% 6+0%
Yerry MinaDEF	Cagliari	1.14	83provisional	1.07	29%	57	035% 136% 219% 37% 42% 50% 6+0%

10 of 45 players shown, ranked by projection. Show all 45 →

Shots45 playersHighest: Gabriel Strefezza, 1.85 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
Gabriel StrefezzaFWD	Parma	2.17	74provisional	1.85	53%	51	018% 128% 225% 316% 48% 53% 6+2%
Sebastiano EspositoFWD	Cagliari	1.94	75provisional	1.67	49%	69	021% 130% 224% 314% 46% 53% 6+1%
Adrián BernabéMID	Parma	1.77	75provisional	1.53	44%	53	023% 132% 224% 313% 45% 52% 6+1%
Jacob OndrejkaFWD	Parma	2.54	45provisional	1.42	39%	28	030% 131% 220% 311% 45% 52% 6+1%
Hans Nicolussi CavigliaMID	Parma	1.49	75provisional	1.28	36%	61	031% 133% 221% 310% 44% 51% 6+0%
Gennaro BorrelliFWD	Cagliari	2.16	48provisional	1.27	35%	27	034% 131% 219% 39% 44% 52% 6+1%
Zito LuvumboFWD	Cagliari	1.67	60provisional	1.19	33%	48	034% 133% 220% 39% 43% 51% 6+0%
Alessandro DeiolaMID	Cagliari	1.41	66provisional	1.08	30%	49	037% 134% 218% 38% 43% 51% 6+0%
El Bilal TouréFWD	—	2.87	26provisional	1.03	26%	12	041% 133% 215% 36% 43% 51% 6+1%
Daniel MaldiniMID	—	2.15	37provisional	1.01	26%	51	043% 131% 215% 37% 43% 51% 6+1%

10 of 45 players shown, ranked by projection. Show all 45 →

Shots on target43 playersHighest: Gabriel Strefezza, 0.62 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
Gabriel StrefezzaFWD	Parma	0.73	74provisional	0.62	45%	51	055% 132% 210% 32% 4+1%
Jacob OndrejkaFWD	Parma	1.11	45provisional	0.62	44%	28	056% 130% 210% 33% 41% 5+0%
Sebastiano EspositoFWD	Cagliari	0.62	75provisional	0.53	41%	69	059% 130% 28% 32% 4+0%
Gennaro BorrelliFWD	Cagliari	0.82	48provisional	0.48	36%	27	064% 127% 27% 32% 4+0%
El Bilal TouréFWD	—	1.14	26provisional	0.41	32%	12	068% 124% 26% 31% 4+0%
Zito LuvumboFWD	Cagliari	0.55	60provisional	0.39	31%	48	069% 125% 25% 31% 4+0%
Adrián BernabéMID	Parma	0.43	75provisional	0.38	31%	53	069% 125% 25% 3+1%
Andrea BelottiFWD	Cagliari	1.06	26provisional	0.37	28%	26	072% 122% 25% 31% 4+0%
Daniel MaldiniMID	—	0.76	37provisional	0.36	28%	51	072% 122% 25% 31% 4+0%
Mattia FeliciFWD	Cagliari	0.76	34provisional	0.34	28%	32	072% 123% 24% 31% 4+0%
Alessandro DeiolaMID	Cagliari	0.43	66provisional	0.33	28%	49	072% 123% 24% 3+1%
Adrian BenedyczakFWD	Parma	0.67	37provisional	0.32	26%	23	074% 121% 24% 31% 4+0%
Hans Nicolussi CavigliaMID	Parma	0.36	75provisional	0.31	26%	61	074% 122% 24% 3+0%
Semih KılıçsoyFWD	Cagliari	0.68	34provisional	0.30	25%	22	075% 120% 24% 31% 4+0%
Pontus AlmqvistFWD	Parma	0.69	32provisional	0.30	25%	42	075% 121% 24% 3+1%
Milan DjuricFWD	Parma	0.71	31provisional	0.29	24%	51	076% 120% 24% 31% 4+0%
Harry WinksMID	—	0.32	77provisional	0.28	24%	56	076% 121% 23% 3+0%
Leonardo PavolettiFWD	Cagliari	0.93	17provisional	0.24	21%	39	079% 118% 22% 3+0%
Michel AdopoMID	Cagliari	0.24	78provisional	0.22	19%	73	081% 117% 22% 3+0%
Enrico DelpratoDEF	Parma	0.21	85provisional	0.20	18%	69	082% 116% 22% 3+0%
HernaniMID	Parma	0.39	39provisional	0.20	17%	29	083% 115% 22% 3+0%
Christian OrdóñezMID	Parma	0.30	53provisional	0.19	17%	28	083% 115% 22% 3+0%
Jacopo FazziniMID	—	0.40	36provisional	0.18	16%	40	084% 114% 22% 3+0%
Lautaro ValentiDEF	Parma	0.19	82provisional	0.17	16%	47	084% 114% 2+1%
Emanuele ValeriDEF	Parma	0.21	70provisional	0.17	15%	69	085% 114% 2+1%
Mandela KeitaMID	Parma	0.19	74provisional	0.17	15%	67	085% 114% 2+1%
Yerry MinaDEF	Cagliari	0.17	83provisional	0.16	15%	57	085% 113% 2+1%
Matteo PratiMID	Cagliari	0.24	52provisional	0.15	14%	45	086% 113% 2+1%
Gabriele ZappaDEF	Cagliari	0.18	74provisional	0.15	14%	68	086% 113% 2+1%
Sascha BritschgiDEF	Parma	0.20	64provisional	0.15	14%	29	086% 113% 2+1%
Mariano TroiloDEF	Parma	0.16	79provisional	0.14	13%	21	087% 112% 2+1%
Oliver SørensenMID	Parma	0.24	41provisional	0.12	12%	34	088% 111% 2+1%
Sebastiano LupertoDEF	Cagliari	0.12	89provisional	0.12	12%	70	088% 111% 2+1%
Adam ObertDEF	Cagliari	0.13	73provisional	0.11	10%	56	090% 110% 2+1%
Abdoulaye NdiayeDEF	Parma	0.15	62provisional	0.11	10%	11	090% 110% 2+1%
Riyad IdrissiDEF	Cagliari	0.28	28provisional	0.11	10%	23	090% 19% 2+1%
Alessandro CircatiDEF	Parma	0.11	86provisional	0.10	10%	37	090% 19% 2+1%
Zé PedroDEF	Cagliari	0.11	77provisional	0.10	9%	23	091% 19% 2+0%
Nahuel EstévezMID	Parma	0.21	30provisional	0.08	8%	46	092% 18% 2+0%
Juan RodríguezDEF	Cagliari	0.11	66provisional	0.08	8%	17	092% 17% 2+0%
Mathias LøvikDEF	Parma	0.20	30provisional	0.08	8%	15	092% 17% 2+0%
Botond BaloghDEF	Parma	0.08	74provisional	0.07	7%	29	093% 16% 2+0%
Franco CarboniDEF	Parma	0.14	33provisional	0.06	6%	15	094% 15% 2+0%

All 43 players shown, ranked by projection. Show fewer ↥

Fouls won45 playersHighest: Gabriel Strefezza, 2.04 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
Gabriel StrefezzaFWD	Parma	2.40	74provisional	2.04	58%	51	016% 126% 225% 317% 49% 54% 6+3%
Zito LuvumboFWD	Cagliari	2.73	60provisional	1.92	54%	48	020% 127% 223% 315% 49% 54% 6+3%
Adrián BernabéMID	Parma	2.16	75provisional	1.86	54%	53	017% 129% 225% 316% 48% 53% 6+2%
Sebastiano EspositoFWD	Cagliari	1.68	75provisional	1.45	42%	69	026% 133% 223% 312% 45% 52% 6+1%
Mandela KeitaMID	Parma	1.67	74provisional	1.42	41%	67	026% 133% 223% 311% 44% 51% 6+1%
Gennaro BorrelliFWD	Cagliari	2.44	48provisional	1.41	39%	27	031% 130% 219% 311% 45% 52% 6+1%
Yerry MinaDEF	Cagliari	1.31	83provisional	1.22	34%	57	030% 135% 221% 39% 43% 51% 6+0%
Hans Nicolussi CavigliaMID	Parma	1.32	75provisional	1.13	31%	61	035% 134% 220% 38% 43% 51% 6+0%
Pontus AlmqvistFWD	Parma	2.28	32provisional	0.95	24%	42	042% 134% 216% 36% 42% 51% 6+0%
Daniel MaldiniMID	—	2.06	37provisional	0.95	24%	51	045% 130% 214% 36% 43% 51% 6+0%

10 of 45 players shown, ranked by projection. Show all 45 →

Saves2 playersHighest: Elia Caprile, 2.98 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
Elia CaprileGK	Cagliari	3.02	88provisional	2.98	55%	60	07% 117% 222% 320% 415% 510% 6+10%
Edoardo CorviGK	Parma	2.30	87provisional	2.25	38%	17	013% 124% 225% 318% 411% 55% 6+4%

2 of 7 markets have no projection for this fixture.