Serie A · Italy

RomavFiorentina

Monday 24 August at 19:45Stadio Olimpicolineups not announced

Referee

Matteo Marcenaro

20 matches on record

Fouls per game

24.4

+5% vs league

League average

23.2

fouls per match, both teams

Angles

every priced line builder

opponentFiorentina concede 5.1 shots on target a game — 1st most of 23 in Serie A
Over their last 10. Good news for Roma's shooters.
opponentFiorentina concede 15.4 shots a game — 1st most of 23 in Serie A
Over their last 10. Good news for Roma's shooters.
opponentRoma concede 18.0 tackles a game — 3rd most of 23 in Serie A
Over their last 10. Good news for Fiorentina's tacklers.

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

Fouls49 playersHighest: Mateo Pellegrino, 2.10 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
Mateo PellegrinoFWD	—	2.35	77provisional	2.10	61%	50	014% 125% 225% 318% 410% 55% 6+3%
Gianluca ManciniDEF	Roma	1.85	85provisional	1.77	52%	73	018% 130% 226% 316% 47% 53% 6+1%
Bryan CristanteMID	Roma	1.81	79provisional	1.64	48%	67	021% 131% 225% 314% 46% 52% 6+1%
Marin PongracicDEF	Fiorentina	1.85	67provisional	1.46	42%	55	028% 131% 222% 312% 45% 52% 6+1%
Mario HermosoDEF	Roma	1.64	73provisional	1.39	40%	39	027% 133% 223% 311% 44% 51% 6+0%
Daniele GhilardiDEF	Roma	1.79	61provisional	1.34	38%	47	030% 133% 221% 310% 44% 51% 6+1%
WesleyDEF	Roma	1.43	82provisional	1.33	38%	30	027% 134% 223% 310% 44% 51% 6+0%
Moise KeanFWD	Fiorentina	1.35	83provisional	1.27	36%	58	029% 135% 222% 310% 43% 51% 6+0%
Santiago CastroFWD	—	1.52	71provisional	1.27	36%	71	030% 134% 222% 310% 43% 51% 6+0%
Manu KonéMID	Roma	1.56	69provisional	1.26	36%	63	031% 133% 221% 310% 44% 51% 6+0%

10 of 49 players shown, ranked by projection. Show all 49 →

Shots49 playersHighest: Donyell Malen, 2.50 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
Donyell MalenFWD	Roma	3.63	58provisional	2.50	63%	67	016% 121% 220% 316% 412% 58% 6+8%
Moise KeanFWD	Fiorentina	2.58	83provisional	2.41	67%	58	011% 122% 224% 319% 412% 56% 6+5%
Paulo DybalaFWD	Roma	2.69	68provisional	2.12	59%	46	017% 124% 223% 317% 410% 55% 6+4%
Santiago CastroFWD	—	2.37	71provisional	1.95	55%	71	018% 127% 224% 316% 49% 54% 6+3%
Lorenzo PellegriniMID	Roma	1.88	67provisional	1.47	42%	49	025% 132% 223% 312% 45% 52% 6+1%
Matías SouléFWD	Roma	2.06	59provisional	1.43	40%	60	030% 130% 221% 311% 45% 52% 6+1%
Mateo PellegrinoFWD	—	1.58	77provisional	1.39	40%	50	027% 133% 222% 311% 44% 51% 6+1%
Tommaso BaldanziMID	Roma	2.17	47provisional	1.27	35%	49	033% 132% 219% 39% 44% 51% 6+1%
Bryan CristanteMID	Roma	1.21	79provisional	1.08	29%	67	036% 135% 219% 37% 42% 51% 6+0%
Arthur AttaMID	—	1.31	72provisional	1.08	29%	59	037% 134% 218% 38% 42% 51% 6+0%
Rolando MandragoraMID	Fiorentina	1.41	61provisional	1.02	27%	63	040% 133% 217% 37% 42% 51% 6+0%
M'Bala NzolaFWD	—	1.65	50provisional	1.01	27%	30	042% 132% 216% 37% 43% 51% 6+0%
Niccolò PisilliMID	Roma	1.38	60provisional	0.98	26%	53	042% 132% 216% 37% 42% 51% 6+0%
Franco MastantuonoFWD	—	1.65	46provisional	0.94	25%	23	044% 132% 215% 36% 42% 51% 6+0%
Stephan El ShaarawyFWD	Roma	2.24	29provisional	0.89	22%	51	045% 133% 214% 35% 42% 51% 6+0%
Albert GudmundssonFWD	Fiorentina	1.31	57provisional	0.89	23%	57	044% 133% 215% 35% 42% 50% 6+0%
Konstantinos KoulierakisDEF	—	0.85	85provisional	0.80	20%	59	046% 135% 214% 34% 41% 5+0%
Manu KonéMID	Roma	1.00	69provisional	0.80	20%	63	048% 133% 214% 34% 41% 5+0%
Riccardo SottilFWD	Fiorentina	1.39	46provisional	0.79	19%	45	049% 131% 213% 34% 41% 5+0%
Christian KouaméFWD	Fiorentina	1.76	33provisional	0.76	18%	28	051% 131% 212% 34% 41% 50% 6+0%
WesleyDEF	Roma	0.81	82provisional	0.75	18%	30	048% 134% 213% 34% 41% 5+0%
Mario HermosoDEF	Roma	0.90	73provisional	0.75	18%	39	049% 133% 213% 34% 41% 5+0%
Nicolò FagioliMID	Fiorentina	0.86	70provisional	0.70	16%	65	051% 132% 212% 33% 41% 5+0%
Evan NdickaDEF	Roma	0.70	88provisional	0.68	15%	69	051% 134% 212% 33% 41% 5+0%
Jack HarrisonFWD	Fiorentina	1.05	53provisional	0.68	16%	60	054% 131% 211% 33% 41% 5+0%
Fabiano ParisiDEF	Fiorentina	0.90	63provisional	0.66	15%	49	054% 131% 211% 33% 41% 5+0%
Giovanni FabbianMID	Fiorentina	1.25	41provisional	0.65	15%	59	056% 129% 210% 33% 41% 5+0%
Robinio VazFWD	Roma	2.33	18provisional	0.64	14%	12	053% 133% 211% 32% 4+1%
Nahuel MolinaDEF	—	1.00	51provisional	0.62	14%	56	057% 129% 210% 33% 41% 5+0%
Gianluca ManciniDEF	Roma	0.62	85provisional	0.59	12%	73	056% 132% 210% 32% 4+0%
Cher NdourMID	Fiorentina	0.86	52provisional	0.54	11%	42	061% 128% 29% 32% 4+1%
Marco BrescianiniMID	Fiorentina	0.84	51provisional	0.52	11%	55	061% 128% 28% 32% 4+0%
DodôDEF	Fiorentina	0.52	87provisional	0.50	9%	71	061% 130% 28% 31% 4+0%
Álex JiménezDEF	—	0.59	72provisional	0.49	9%	54	062% 129% 27% 31% 4+0%
Neil El AynaouiMID	Roma	0.77	43provisional	0.42	7%	25	067% 125% 26% 31% 4+0%
Luca RanieriDEF	Fiorentina	0.40	81provisional	0.37	6%	70	070% 125% 25% 3+1%
Amir RichardsonMID	Fiorentina	0.87	31provisional	0.36	6%	29	071% 123% 25% 31% 4+0%
Niccolò FortiniDEF	Fiorentina	0.88	29provisional	0.35	5%	16	071% 124% 24% 31% 4+0%
João MárioDEF	—	0.43	61provisional	0.31	4%	20	074% 122% 24% 3+1%
Daniele GhilardiDEF	Roma	0.43	61provisional	0.31	4%	47	074% 121% 24% 3+1%
Devyne RenschDEF	Roma	0.52	45provisional	0.29	4%	38	076% 120% 24% 3+1%
Radu DrăgușinDEF	—	0.41	49provisional	0.25	3%	26	079% 118% 23% 3+0%
Pablo MaríDEF	Fiorentina	0.23	70provisional	0.18	2%	43	084% 115% 22% 3+0%
Jan ZiolkowskiDEF	Roma	0.54	24provisional	0.18	2%	18	084% 114% 22% 3+0%
Mattia VitiDEF	Fiorentina	0.22	63provisional	0.16	1%	40	085% 113% 21% 3+0%
Marin PongracicDEF	Fiorentina	0.19	67provisional	0.15	1%	55	087% 112% 2+1%
Mile SvilarGK	Roma	0.01	89provisional	0.01	—	76	099% 1+1%
Devis VásquezGK	—	0.00	88provisional	0.00	—	32	0100% 1+0%
David de GeaGK	Fiorentina	0.00	89provisional	0.00	—	72	0100% 1+0%

All 49 players shown, ranked by projection. Show fewer ↥

Shots on target46 playersHighest: Donyell Malen, 1.04 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
Donyell MalenFWD	Roma	1.50	58provisional	1.04	60%	67	040% 132% 217% 37% 43% 51% 6+0%
Moise KeanFWD	Fiorentina	0.99	83provisional	0.93	59%	58	041% 135% 216% 36% 41% 5+0%
Paulo DybalaFWD	Roma	1.05	68provisional	0.83	54%	46	046% 133% 214% 35% 41% 5+0%
Santiago CastroFWD	—	0.87	71provisional	0.71	49%	71	051% 133% 212% 33% 41% 5+0%
Lorenzo PellegriniMID	Roma	0.66	67provisional	0.52	40%	49	060% 130% 28% 32% 4+0%
Mateo PellegrinoFWD	—	0.58	77provisional	0.51	39%	50	061% 129% 28% 32% 4+0%
Matías SouléFWD	Roma	0.71	59provisional	0.50	38%	60	062% 128% 28% 32% 4+0%
Tommaso BaldanziMID	Roma	0.68	47provisional	0.40	32%	49	068% 125% 26% 31% 4+0%
Albert GudmundssonFWD	Fiorentina	0.54	57provisional	0.37	30%	57	070% 124% 25% 31% 4+0%
M'Bala NzolaFWD	—	0.60	50provisional	0.37	29%	30	071% 123% 25% 31% 4+0%

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

Fouls won49 playersHighest: Fabiano Parisi, 2.19 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
Fabiano ParisiDEF	Fiorentina	3.00	63provisional	2.19	59%	49	018% 123% 222% 316% 411% 56% 6+5%
Paulo DybalaFWD	Roma	2.76	68provisional	2.16	60%	46	017% 124% 223% 317% 410% 55% 6+4%
Mateo PellegrinoFWD	—	1.92	77provisional	1.68	49%	50	021% 130% 224% 314% 47% 53% 6+1%
WesleyDEF	Roma	1.72	82provisional	1.59	46%	30	022% 132% 224% 313% 46% 52% 6+1%
Moise KeanFWD	Fiorentina	1.68	83provisional	1.57	46%	58	023% 132% 224% 313% 46% 52% 6+1%
Lorenzo PellegriniMID	Roma	2.01	67provisional	1.56	45%	49	023% 132% 224% 313% 46% 52% 6+1%
Manu KonéMID	Roma	1.97	69provisional	1.55	44%	63	026% 130% 222% 313% 46% 52% 6+1%
Santiago CastroFWD	—	1.77	71provisional	1.44	41%	71	027% 132% 222% 312% 45% 52% 6+1%
João MárioDEF	—	1.96	61provisional	1.39	39%	20	030% 130% 221% 311% 45% 52% 6+1%
DodôDEF	Fiorentina	1.34	87provisional	1.31	37%	71	028% 135% 222% 310% 44% 51% 6+0%

10 of 49 players shown, ranked by projection. Show all 49 →

Saves3 playersHighest: David de Gea, 3.30 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
David de GeaGK	Fiorentina	3.33	89provisional	3.30	61%	72	05% 114% 220% 320% 416% 511% 6+14%
Mile SvilarGK	Roma	2.39	89provisional	2.38	42%	76	011% 123% 225% 319% 412% 56% 6+5%
Devis VásquezGK	—	2.22	88provisional	2.18	37%	32	013% 125% 225% 318% 410% 55% 6+3%

2 of 7 markets have no projection for this fixture.