Serie A · Italy

SassuolovTorino

Saturday 29 August at 17:30MAPEI Stadium - Città del Tricolorelineups not announced

Referee

Not appointed

0 matches on record

Fouls per game

—

League average

22.9

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

Fouls43 playersHighest: Saúl Coco, 1.49 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
Saúl CocoDEF	Torino	1.52	89provisional	1.49	44%	67	023% 133% 225% 312% 45% 51% 6+1%
Cesare CasadeiMID	Torino	1.99	63provisional	1.38	39%	38	030% 131% 221% 311% 45% 52% 6+1%
Gvidas GineitisMID	Torino	2.14	54provisional	1.28	36%	42	033% 131% 220% 310% 44% 51% 6+1%
Nikola VlašićMID	Torino	1.34	77provisional	1.15	32%	63	033% 135% 220% 38% 43% 51% 6+0%
Valentino LazaroMID	Torino	1.45	72provisional	1.15	32%	57	035% 133% 220% 38% 43% 51% 6+0%
Giovanni SimeoneFWD	Torino	1.44	70provisional	1.12	31%	31	034% 135% 220% 38% 43% 51% 6+0%
Domenico BerardiFWD	Sassuolo	1.31	76provisional	1.10	30%	25	035% 135% 220% 38% 42% 51% 6+0%
Guillermo MaripánDEF	Torino	1.20	82provisional	1.09	30%	52	035% 135% 219% 37% 42% 51% 6+0%
Armand LaurientéFWD	Sassuolo	1.39	69provisional	1.06	29%	36	037% 135% 219% 37% 42% 51% 6+0%
Kristian ThorstvedtMID	Sassuolo	1.23	77provisional	1.05	29%	30	037% 134% 218% 37% 42% 51% 6+0%

10 of 43 players shown, ranked by projection. Show all 43 →

Tackles43 playersHighest: Guillermo Maripán, 1.64 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
Guillermo MaripánDEF	Torino	1.81	82provisional	1.64	47%	52	023% 130% 223% 313% 46% 53% 6+1%
Saúl CocoDEF	Torino	1.59	89provisional	1.56	45%	67	024% 131% 223% 313% 46% 52% 6+1%
Nikola VlašićMID	Torino	1.82	77provisional	1.56	44%	63	026% 130% 222% 312% 46% 52% 6+1%
Emirhan İlkhanMID	Torino	2.45	54provisional	1.46	40%	15	030% 130% 220% 311% 45% 52% 6+1%
Rafa ObradorDEF	Torino	1.73	70provisional	1.35	38%	14	030% 131% 221% 311% 44% 52% 6+1%
Ardian IsmajliDEF	Torino	1.55	76provisional	1.32	37%	23	031% 132% 220% 310% 44% 52% 6+1%
Sebastian WalukiewiczDEF	Sassuolo	1.41	84provisional	1.32	37%	33	030% 133% 221% 310% 44% 51% 6+1%
Kristian ThorstvedtMID	Sassuolo	1.53	77provisional	1.31	37%	30	032% 131% 220% 310% 44% 52% 6+1%
Ulisses GarciaDEF	Sassuolo	1.61	73provisional	1.30	36%	11	033% 131% 219% 310% 44% 52% 6+1%
Nemanja MatićMID	Sassuolo	1.44	79provisional	1.25	35%	33	032% 133% 220% 39% 44% 51% 6+0%

10 of 43 players shown, ranked by projection. Show all 43 →

Shots43 playersHighest: Andrea Pinamonti, 2.35 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
Andrea PinamontiFWD	Sassuolo	2.96	72provisional	2.35	64%	31	015% 121% 222% 318% 412% 57% 6+5%
Giovanni SimeoneFWD	Torino	2.96	70provisional	2.31	63%	31	014% 123% 223% 318% 411% 56% 6+5%
Armand LaurientéFWD	Sassuolo	2.88	69provisional	2.20	61%	36	015% 124% 223% 317% 411% 56% 6+4%
Domenico BerardiFWD	Sassuolo	2.31	76provisional	1.95	56%	25	017% 127% 225% 316% 49% 54% 6+2%
Ché AdamsFWD	Torino	2.26	66provisional	1.66	47%	58	024% 129% 222% 313% 47% 53% 6+2%
Kristian ThorstvedtMID	Sassuolo	1.73	77provisional	1.48	42%	30	027% 131% 222% 312% 45% 52% 6+1%
Duván ZapataFWD	Torino	2.69	48provisional	1.45	39%	22	032% 129% 218% 311% 46% 53% 6+2%
Nikola VlašićMID	Torino	1.48	77provisional	1.27	36%	63	031% 133% 221% 310% 44% 51% 6+0%
Cristian VolpatoMID	Sassuolo	2.56	44provisional	1.26	34%	16	036% 130% 217% 39% 44% 52% 6+1%
Cesare CasadeiMID	Torino	1.35	63provisional	0.94	25%	38	043% 132% 216% 36% 42% 51% 6+0%

10 of 43 players shown, ranked by projection. Show all 43 →

Fouls won43 playersHighest: Kristian Thorstvedt, 1.78 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
Kristian ThorstvedtMID	Sassuolo	2.09	77provisional	1.78	51%	30	021% 128% 223% 315% 48% 53% 6+2%
Ismaël KonéMID	Sassuolo	1.82	79provisional	1.60	46%	34	022% 131% 224% 313% 46% 52% 6+1%
Armand LaurientéFWD	Sassuolo	1.93	69provisional	1.47	42%	36	026% 131% 222% 312% 45% 52% 6+1%
Domenico BerardiFWD	Sassuolo	1.74	76provisional	1.47	42%	25	025% 132% 223% 312% 45% 52% 6+1%
Giovanni SimeoneFWD	Torino	1.67	70provisional	1.31	37%	31	030% 133% 221% 310% 44% 51% 6+0%
Nemanja MatićMID	Sassuolo	1.39	79provisional	1.21	34%	33	032% 134% 221% 39% 43% 51% 6+0%
Nikola VlašićMID	Torino	1.30	77provisional	1.12	31%	63	035% 134% 219% 38% 43% 51% 6+0%
Andrea PinamontiFWD	Sassuolo	1.36	72provisional	1.08	30%	31	037% 133% 219% 38% 42% 51% 6+0%
Aster VranckxMID	Sassuolo	2.20	43provisional	1.06	28%	10	042% 130% 216% 38% 43% 51% 6+0%
Gvidas GineitisMID	Torino	1.53	54provisional	0.92	24%	42	044% 132% 215% 36% 42% 51% 6+0%

10 of 43 players shown, ranked by projection. Show all 43 →

Cards43 playersHighest: Saúl Coco, 0.21 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
Saúl CocoDEF	Torino	0.22	89provisional	0.21	19%	67	081% 117% 22% 3+0%
Gvidas GineitisMID	Torino	0.30	54provisional	0.18	16%	42	084% 115% 22% 3+0%
Kristian ThorstvedtMID	Sassuolo	0.21	77provisional	0.18	16%	30	084% 115% 21% 3+0%
Guillermo MaripánDEF	Torino	0.19	82provisional	0.17	16%	52	084% 114% 2+1%
Ardian IsmajliDEF	Torino	0.19	76provisional	0.16	15%	23	085% 114% 2+1%
Sebastian WalukiewiczDEF	Sassuolo	0.17	84provisional	0.16	15%	33	085% 114% 2+1%
Valentino LazaroMID	Torino	0.20	72provisional	0.16	14%	57	086% 113% 2+1%
Cesare CasadeiMID	Torino	0.22	63provisional	0.16	14%	38	086% 113% 2+1%
Adam MasinaDEF	Torino	0.20	65provisional	0.15	13%	24	087% 112% 2+1%
Luca LipaniMID	Sassuolo	0.30	43provisional	0.14	13%	12	087% 112% 2+1%

10 of 43 players shown, ranked by projection. Show all 43 →

Saves2 playersHighest: Alberto Paleari, 3.01 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
Alberto PaleariGK	Torino	3.01	90provisional	3.01	56%	30	07% 116% 221% 320% 415% 510% 6+11%
Arijanet MurićGK	Sassuolo	2.81	90provisional	2.81	51%	32	08% 118% 223% 320% 414% 59% 6+8%

1 of 7 markets have no projection for this fixture.