Serie AStadio Olimpico, Roma28°8,4 mm16 km/h

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    RomaRomaPossession control
    vs
    FiorentinaFiorentinaBalanced & physical
    The model's lean: 1 · Roma (64%)

    RomaFiorentina · Serie A

    1 · Roma 64%X 22%14% Fiorentina · 2

    Analysis: RomaFiorentina

    Sofia Andersson · · The model's read on the match · How the predictions work

    Five straight wins for AS Roma make them a formidable force as they face ACF Fiorentina. With a model giving AS Roma a 64% chance of victory, the numbers echo confidence in the home side's ability to extend their streak. ACF Fiorentina's chances, though not negligible, sit at a mere 14%, which speaks volumes about the current form and the expected flow of this match.

    AS Roma have an enviable record at home, winning 62% of their matches in front of their fans. This, coupled with their impressive run of scoring in 15 consecutive league games, suggests that their attacking prowess will likely find the back of the net again. The expected goals tally of 1.87 for AS Roma against ACF Fiorentina's 0.87 suggests a game where the home side should dominate both possession and opportunities.

    ACF Fiorentina's balanced and physical style might aim to disrupt AS Roma's possession control, but with only three wins in their last 10 head-to-head meetings since 2021, history is not on their side. Moreover, the average of 3.1 goals per meeting between these teams hints at the potential for goals, although the weather could play a role in dampening the final tally. The over 2.5 goals chance is sitting narrowly above half at 52%, indicating a slight inclination towards a lower-scoring affair, reinforced by the 50% probability for both teams to score.

    The model's most likely scorelines point to a 1-0 or 2-0 win for AS Roma, fitting the narrative that their defense, boasting an xGA of 0.89 per match, can handle ACF Fiorentina's attack. Given the value found with Betsson and Nordicbet offering odds of 1.6, there's a slim but tangible edge for those backing AS Roma to clinch all three points. While no bet is guaranteed, the numbers suggest the smart money leans towards a controlled AS Roma victory, potentially a straightforward 1-0 affair.

    RomaRoma
    Form WWWWW
    League ranking xG #4xGA #1xT #5xP/match #2Points #3
    Key players
    • Donyell MalenFxG 0.71 · xT 0.11
    • Zeki CelikRWBxG 0.11 · xT 0.11
    • Wesley FrançaLWBxG 0.05 · xT 0.18
    FiorentinaFiorentina
    Form DLDWD
    League ranking xG #8xGA #19xT #10xP/match #12Points #15
    Key players
    • Moise KeanFxG 0.57 · xT 0.02
    • DodôRWBxG 0.06 · xT 0.21
    • Roberto PiccoliFxG 0.30 · xT -0.02

    Match prediction: RomaFiorentina

    Predicted score matrix

    Fiorentina
    Roma
    0
    1
    2
    3
    4+
    0
    0–06.7%
    0–15.3%
    0–22.4%
    0–30.7%
    0–4+0.2%
    1
    1–011.7%
    1–110.8%
    1–24.6%
    1–31.3%
    1–4+0.4%
    2
    2–011.2%
    2–19.8%
    2–24.3%
    2–31.3%
    2–4+0.3%
    3
    3–07.0%
    3–16.1%
    3–22.7%
    3–30.8%
    3–4+0.2%
    4+
    4+–05.0%
    4+–14.4%
    4+–21.9%
    4+–30.6%
    4+–4+0.1%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-012%
    2. 2.2-011%
    3. 3.1-111%
    4. 4.2-110%
    5. 5.3-07%
    Expected goals
    1,870,87
    Both teams to score
    50%

    Over/under goals

    Expected goals: 2,7
    Under 2,548%
    @1.93
    Over 2,552%
    @1.89

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Roma to win64%
    • Over 1.5 goals76%

    Combined probability

    49%

    Fair odds

    2.05

    Two legs pulling the same way — the probability is computed exactly from the score matrix, not multiplied.

    02 · 3 legs

    Balanced

    • Roma to win64%
    • Over 2.5 goals52%
    • Donyell Malen to score25%

    Combined probability

    Fair odds

    The whole slip is priced jointly via 20,000 simulated matches — the scorer interacts with result and total goals, never naive multiplication.

    03 · 4 legs

    Bold

    • Both teams to score50%
    • Over 2.5 goals52%
    • Donyell Malen to score25%
    • Daniele Rugani to be booked20%

    Combined probability

    Fair odds

    The goal-fest: both teams score with at least three goals, plus the match's most likely scorer and card candidate — all priced jointly via 20,000 simulated matches.

    Odds & value

    The model's value spots

    Bets where the model's probability beats what the odds imply (EV+).

    • 1 · Roma64% probability@1.60BetssonEV+2%reference odds
    • 1 · Roma64% probability@1.60NordicbetEV+2%reference odds
    • 1 · Roma64% probability@1.58BetsafeEV+1%reference odds
    Bookmaker1 · RomaX2 · Fiorentina
    Betsafe
    EV+ 1%
    1.58
    3.855.90
    Betsson
    EV+ 2%
    1.60
    3.905.95
    Nordicbet
    EV+ 2%
    1.60
    3.905.95

    Odds updated 18 Aug, 11:37

    Odds movement

    10 %
    62 %57 %

    1.601.60

    X0 %
    27 %22 %

    3.903.90

    20 %
    19 %14 %

    5.955.95

    Over 2,5-1 %
    53 %48 %

    1.911.89

    Betsson · 2 recorded price levels · 18/08/2026 → 18/08/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    10 matches
    Roma 5Draw 2Fiorentina 3
    Goals: 1714 (⌀ 3,1)

    Head-to-head based on Serie A data since 2021.

    Key facts

    • A high-scoring fixture: 3.1 goals per meeting on average.
    • AS Roma come into this round on 5 straight wins.
    • AS Roma have scored in 15 consecutive league matches.
    • AS Roma win 62% of their home matches all-time (95 played).
    xG & xGA per match — 3-game rolling average

    Solid line = created (xG), dashed = conceded (xGA).

    Roma
    Fiorentina
    When goals are scored and conceded 2025
    Roma (5931)
    Fiorentina (4150)
    Pass networks

    Last 5 matches. Circle size = pass volume, line width = combinations between players. Attacking left to right.

    Roma
    Mario Hermoso: 236 passningar, xT 0.28HermosoBryan Cristante: 228 passningar, xT 0.61CristanteGianluca Mancini: 194 passningar, xT 0.1ManciniZeki Celik: 181 passningar, xT 0.22CelikNiccolo Pisilli: 180 passningar, xT 0.12PisilliPaulo Dybala: 157 passningar, xT 1.22DybalaEvan Ndicka: 146 passningar, xT 0.06NdickaWesley França: 141 passningar, xT 0.37FrançaMile Svilar: 125 passningar, xT 0.04SvilarMatias Soule: 125 passningar, xT 0.51SouleNeil El Aynaoui: 124 passningar, xT 0.2Aynaoui
    Fiorentina
    Dodô: 190 passningar, xT 1.04DodôNicolò Fagioli: 172 passningar, xT 0.11FagioliLuca Ranieri: 146 passningar, xT 0.19RanieriCher Ndour: 126 passningar, xT 0.03NdourManor Solomon: 123 passningar, xT 0.11SolomonRobin Gosens: 120 passningar, xT 0.13GosensMarin Pongracic: 100 passningar, xT 0.06PongracicDavid De Gea: 93 passningar, xT 0.13GeaAlbert Gudmundsson: 88 passningar, xT 0.11GudmundssonRolando Mandragora: 82 passningar, xT -0.06MandragoraJack David Harrison: 76 passningar, xT 1.09Harrison
    xT networks

    The same network weighted by offensive threat (xT): circle size = threat created by the player, line width = threat of the combinations. Last 5 matches, attacking left to right.

    Roma
    Mario Hermoso: 236 passningar, xT 0.28HermosoBryan Cristante: 228 passningar, xT 0.61CristanteGianluca Mancini: 194 passningar, xT 0.1ManciniZeki Celik: 181 passningar, xT 0.22CelikNiccolo Pisilli: 180 passningar, xT 0.12PisilliPaulo Dybala: 157 passningar, xT 1.22DybalaEvan Ndicka: 146 passningar, xT 0.06NdickaWesley França: 141 passningar, xT 0.37FrançaMile Svilar: 125 passningar, xT 0.04SvilarMatias Soule: 125 passningar, xT 0.51SouleNeil El Aynaoui: 124 passningar, xT 0.2Aynaoui
    Fiorentina
    Dodô: 190 passningar, xT 1.04DodôNicolò Fagioli: 172 passningar, xT 0.11FagioliLuca Ranieri: 146 passningar, xT 0.19RanieriCher Ndour: 126 passningar, xT 0.03NdourManor Solomon: 123 passningar, xT 0.11SolomonRobin Gosens: 120 passningar, xT 0.13GosensMarin Pongracic: 100 passningar, xT 0.06PongracicDavid De Gea: 93 passningar, xT 0.13GeaAlbert Gudmundsson: 88 passningar, xT 0.11GudmundssonRolando Mandragora: 82 passningar, xT -0.06MandragoraJack David Harrison: 76 passningar, xT 1.09Harrison

    The teams in numbers

    PerformanceRomaFiorentina
    Points7342
    xPoints62.848.6
    xG per match1.71.4
    xGA per match0.891.6
    xG within 8s of winning the ball0.320.2
    xGA within 8s of losing the ball0.120.17
    Playing styleRomaFiorentina
    Build-up efficiency0.290.31
    Field tilt0.660.45
    xT per match1.10.83
    xTA per match0.651
    Won balls, offensive half3023
    Pressing intensity0.210.23
    Pressing efficiency0.30.25
    Pressing efficiency, offensive half0.330.28
    Entries into the box per match1511
    Entries into the box against914
    Pass completion %0.80.8
    Pass completion % under pressure0.760.74
    Passes per match423367
    Passes against per match312358
    Switches of play per match31.324.6
    Long balls per match3028
    Set piecesRomaFiorentina
    xG from free kicks0.080.11
    Corners per match5.14.4
    Corners against per match3.54.6
    xG per corner0.080.06
    xGA per corner against0.050.08
    First touch, offensive corners %0.450.4
    First touch, defensive corners %0.540.48
    OtherRomaFiorentina
    Throw-in control0.710.79
    The goalkeepersMile Svilar (Roma)David De Gea (Fiorentina)
    Saves107122
    Save %78%72%
    xG prevented62%51%
    Claims0 (0%)0 (0%)

    Frequently asked questions

    Who wins Roma vs Fiorentina according to our model?

    The model gives Roma a 64% win probability. Full 1X2 picture: Roma 64%, draw 22%, Fiorentina 14%.

    What is the most likely scoreline?

    The model's most likely final score is 1-0 at 12% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 52% and under at 48%.

    Will both teams score?

    The probability of both teams scoring is 50% according to the model.

    Why are some legs locked in the bet builder?

    The same rules as the bookmakers’ builders: legs that contradict or already follow from your slip cannot be combined — for example correct score 2–1 with under 2.5 goals. The difference is that we don’t look the rules up in a table; we compute them straight from the score matrix.

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    Predictions come from PlaymakerAI's match model and reflect the model's assessment — not betting advice. Gamble responsibly.