Serie A · Italy

BolognavLazio

Monday 24 August at 17:30Stadio Renato Dall'Aralineups not announced

Referee

Fabio Maresca

19 matches on record

Fouls per game

25.9

+12% vs league

League average

23.2

fouls per match, both teams

Angles

every priced line builder

opponentBologna concede 9.7 shots a game — 21st most of 23 in Serie A
Over their last 10. A hard place to get shots.
refereeFabio Maresca: 25.9 fouls and 4.4 cards a game (league 25.3 / 3.5)
+0.6 fouls and +0.9 cards against his league's average over his last 19.

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

Fouls46 playersHighest: Tommaso Pobega, 1.54 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
Tommaso PobegaMID	Bologna	2.00	64provisional	1.54	45%	47	024% 131% 223% 313% 46% 52% 6+1%
Matteo CancellieriFWD	Lazio	2.00	62provisional	1.52	44%	57	024% 132% 224% 313% 45% 52% 6+1%
Roberto PiccoliFWD	—	1.71	75provisional	1.48	43%	69	025% 132% 223% 312% 45% 52% 6+1%
Mattia ZaccagniFWD	Lazio	1.48	81provisional	1.37	39%	60	026% 134% 223% 311% 44% 51% 6+0%
Lewis FergusonMID	Bologna	1.66	69provisional	1.35	39%	43	029% 132% 222% 311% 44% 51% 6+1%
Luca PellegriniDEF	Lazio	1.66	64provisional	1.29	36%	46	030% 133% 221% 310% 44% 51% 6+0%
Nicolò RovellaMID	Lazio	1.45	76provisional	1.28	36%	44	029% 135% 222% 310% 43% 51% 6+0%
Nicolò CasaleDEF	Bologna	1.78	55provisional	1.23	34%	29	033% 133% 220% 39% 44% 51% 6+0%
Kenneth TaylorMID	Lazio	1.29	81provisional	1.20	34%	17	031% 136% 221% 39% 43% 51% 6+0%
Mattéo GuendouziMID	Lazio	1.20	88provisional	1.18	33%	53	031% 136% 221% 38% 43% 51% 6+0%

10 of 46 players shown, ranked by projection. Show all 46 →

Shots46 playersHighest: Riccardo Orsolini, 2.21 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
Riccardo OrsoliniFWD	Bologna	3.26	57provisional	2.21	59%	65	017% 124% 222% 316% 410% 56% 6+5%
Roberto PiccoliFWD	—	2.47	75provisional	2.11	59%	69	016% 125% 223% 317% 410% 55% 6+4%
Jonathan RoweFWD	Bologna	2.43	65provisional	1.84	52%	28	020% 128% 223% 315% 48% 54% 6+2%
Federico BernardeschiFWD	Bologna	2.71	55provisional	1.79	49%	29	023% 127% 221% 314% 48% 54% 6+3%
Jens OdgaardMID	Bologna	2.26	56provisional	1.51	42%	55	028% 130% 221% 312% 46% 52% 6+1%
Artem DovbykFWD	—	2.50	45provisional	1.41	38%	46	031% 131% 219% 310% 45% 52% 6+2%
Jesper KarlssonFWD	Bologna	1.87	51provisional	1.18	32%	20	034% 133% 219% 39% 43% 51% 6+0%
Tommaso PobegaMID	Bologna	1.50	64provisional	1.12	31%	47	036% 133% 219% 38% 43% 51% 6+0%
Tijjani NoslinFWD	Lazio	1.70	50provisional	1.04	28%	59	041% 131% 217% 37% 43% 51% 6+0%
Matteo CancellieriFWD	Lazio	1.34	62provisional	0.98	26%	57	040% 134% 217% 36% 42% 50% 6+0%

10 of 46 players shown, ranked by projection. Show all 46 →

Shots on target45 playersHighest: Riccardo Orsolini, 0.82 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
Riccardo OrsoliniFWD	Bologna	1.22	57provisional	0.82	53%	65	047% 132% 214% 35% 41% 5+0%
Roberto PiccoliFWD	—	0.90	75provisional	0.77	52%	69	048% 133% 213% 34% 41% 5+0%
Jonathan RoweFWD	Bologna	0.91	65provisional	0.69	48%	28	052% 132% 212% 33% 41% 5+0%
Federico BernardeschiFWD	Bologna	0.94	55provisional	0.62	44%	29	056% 130% 210% 33% 41% 5+0%
Jens OdgaardMID	Bologna	0.89	56provisional	0.60	43%	55	057% 130% 210% 33% 41% 5+0%
Artem DovbykFWD	—	0.91	45provisional	0.51	38%	46	062% 127% 28% 32% 4+1%
Jesper KarlssonFWD	Bologna	0.73	51provisional	0.46	36%	20	064% 127% 27% 31% 4+0%
Matteo CancellieriFWD	Lazio	0.54	62provisional	0.39	32%	57	068% 125% 25% 31% 4+0%
Gustav IsaksenFWD	Lazio	0.69	45provisional	0.39	31%	67	069% 125% 25% 31% 4+0%
Mattia ZaccagniFWD	Lazio	0.41	81provisional	0.38	31%	60	069% 125% 25% 3+1%

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

Fouls won46 playersHighest: Mattia Zaccagni, 2.71 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
Mattia ZaccagniFWD	Lazio	2.98	81provisional	2.71	73%	60	08% 119% 223% 321% 414% 58% 6+7%
Matteo CancellieriFWD	Lazio	2.83	62provisional	2.05	58%	57	017% 126% 224% 317% 410% 55% 6+3%
Nicolò CambiaghiFWD	Bologna	3.31	47provisional	1.89	51%	46	022% 127% 221% 313% 48% 54% 6+4%
Jonathan RoweFWD	Bologna	2.25	65provisional	1.69	48%	28	022% 129% 223% 314% 47% 53% 6+2%
Gustav IsaksenFWD	Lazio	2.54	45provisional	1.40	39%	67	029% 132% 220% 311% 45% 52% 6+1%
Nicolò RovellaMID	Lazio	1.59	76provisional	1.38	39%	44	027% 133% 222% 311% 44% 51% 6+1%
Roberto PiccoliFWD	—	1.58	75provisional	1.34	38%	69	029% 132% 222% 311% 44% 51% 6+1%
Mattéo GuendouziMID	Lazio	1.24	88provisional	1.21	34%	53	031% 135% 221% 39% 43% 51% 6+0%
Riccardo OrsoliniFWD	Bologna	1.69	57provisional	1.13	31%	65	037% 132% 218% 38% 43% 51% 6+0%
Jens OdgaardMID	Bologna	1.64	56provisional	1.08	29%	55	039% 132% 218% 38% 43% 51% 6+0%

10 of 46 players shown, ranked by projection. Show all 46 →

Saves1 playersHighest: Lukasz Skorupski, 2.06 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
Lukasz SkorupskiGK	Bologna	2.15	85provisional	2.06	34%	46	015% 126% 225% 317% 49% 54% 6+3%

2 of 7 markets have no projection for this fixture.