# Parma vs Roma > Serie A · Kickoff Sun 10 May 2026, 16:00 UTC · [Canonical HTML](https://betsprinter.com/fixtures/782) **Status:** Finished **Final score:** Parma 2–3 Roma ## Model verdict - **Parma win:** 8% - **Draw:** 85% - **Roma win:** 7% - **Source:** model ## Pre-match deep dive ### Draw-heavy prognosis as market and model diverge on goals ## The stage A late-season Serie A meeting kicks off Sun 10 May 2026, 16:00 UTC, with Parma hosting Roma in a match the model sees overwhelmingly as draw-heavy[^fact-1][^fact-2]. Home advantage has been applied to the ratings used in the model; despite that, Parma sit behind on Elo by 110 points after the home adjustment[^fact-3]. ## Form & momentum Recent form leans in Roma’s favour on balance. Parma’s ten-match sequence reads LWWDD (3 wins, 4 draws, 3 losses) and the side has averaged 1.30 points per game, scoring 0.70 goals and conceding 1.10 per match over that span[^fact-4]. Roma’s ten-match sequence is WWDWL (5 wins, 2 draws, 3 losses) and the team has averaged 1.70 points per game, with 2.10 goals scored and 1.30 conceded in the same window[^fact-5]. That gulf in offensive output — 0.70 for Parma versus 2.10 for Roma in the recent sample — is the clearest indicator of which team is carrying attacking momentum into the fixture[^fact-4][^fact-5]. The Elo gap, adjusted for the home team, reinforces a measurable quality advantage to Roma of 110 points[^fact-3]. ## Personnel Parma’s most noticeable in-form contributor is Nesta Elphege, who has 2 goals and 1 assist across his last four appearances and carries an average match rating of 6.86 in that run[^fact-9]. Roma’s attacking stock is concentrated in Donyell Malen, who has 4 goals and 2 assists over his last five outings with an average rating of 7.48[^fact-10]. Key absences are straightforward and potentially meaningful. Parma will be without Adrián Bernabé, who has accumulated 515 minutes in the recent run and is out injured[^fact-11]. Roma are missing Zeki Çelik, who logged 723 minutes in the comparable period before being ruled out[^fact-12]. Those minutes figures indicate both players have been regular contributors in recent matches for their sides, and their absences remove known quantities from each starting XI[^fact-11][^fact-12]. ## Where the model sees value The model’s market comparisons cover three markets[^fact-13] and expose several clear edges against public prices. First, on total goals over/under 2.5 the model gives divergent signals against different retail prices: the model assigns a 40% probability to Over 2.5 while the market price listed at Paddy Power implies much higher odds (67.00), producing what the model calls a 39.0 percentage-point edge in favour of backing Over at that specific price[^fact-6]. Second, the model favours Under 2.5 with a 54% probability against the Unibet price of 2.70, an edge of 17.3 percentage points for the model’s Under lean there[^fact-7]. Those two positions highlight the underlying uncertainty the model sees in goal volume — the model’s probabilities switch depending on which bookmaker’s market is used to imply prices[^fact-6][^fact-7]. Third, on the 1X2 market the model assigns the largest single probability to a draw relative to the bookmakers: the model’s internal probability for a draw is 39% versus a Betfair Exchange price implying a 4.60 outcome, yielding a 17.0 percentage-point edge for the draw selection in that market comparison[^fact-8]. This dovetails with the model’s headline match verdict, which places the draw as the dominant outcome in its distribution[^fact-2][^fact-8]. Those three market checks are the complete set analysed against the model for this fixture[^fact-13]. The mixed signals on goals — sizeable edges both for Over at one price and Under at another — reflect how bookmaker pricing differences, rather than consistent model disagreement, create value opportunities according to the desk’s calculations[^fact-6][^fact-7]. ## Verdict The model’s lean is stark: draw is the single most likely result with an 85% model probability spread across outcomes that leaves only thin chances for a home or away win (Home 8%, Away 7%)[^fact-2]. That conclusion sits alongside a clear Elo advantage for Roma of 110 points after home adjustment and stronger attacking output in the recent sample, yet the model’s probability mass coalesces on stalemate — a picture reinforced by the model’s stated market edges, where the draw and both goal markets show exploitable divergences against specific bookmaker prices[^fact-3][^fact-5][^fact-6][^fact-7][^fact-8]. ### Cited facts [^fact-1]: **Kickoff** — Sun 10 May 2026, 16:00 UTC — Serie A [^fact-2]: **Model verdict** — Home 8% / Draw 85% / Away 7% (source: model; confidence high, 77 pp gap to runner-up). [^fact-3]: **Elo edge** — PRM vs ROM — Elo differential -110 points (with home advantage applied). [^fact-4]: **PRM recent form** — LWWDD last 10: 3-4-3 (W-D-L), 1.30 PPG, 0.70 goals scored / 1.10 conceded per match. [^fact-5]: **ROM recent form** — WWDWL last 10: 5-2-3 (W-D-L), 1.70 PPG, 2.10 goals scored / 1.30 conceded per match. [^fact-6]: **Value pick #1** — Over in Goals O/U 2.5 — model 40% vs market price 67.00 at Paddy Power, edge 39.0 pp (high confidence). [^fact-7]: **Value pick #2** — Under in Goals O/U 2.5 — model 54% vs market price 2.70 at Unibet, edge 17.3 pp (high confidence). [^fact-8]: **Value pick #3** — Draw in Match Winner — model 39% vs market price 4.60 at Betfair Exchange, edge 17.0 pp (high confidence). [^fact-9]: **PRM in-form player** — Nesta Elphege — 2 goals, 1 assists in last 4 appearances, avg rating 6.86. [^fact-10]: **ROM in-form player** — Donyell Malen — 4 goals, 2 assists in last 5 appearances, avg rating 7.48. [^fact-11]: **PRM key absence** — Adrián Bernabé out (injury), 515 minutes in recent run. [^fact-12]: **ROM key absence** — Zeki Çelik out (injury), 723 minutes in recent run. [^fact-13]: **Markets analysed** — 3 market(s) compared against the model. --- Methodology: . Canonical HTML: .