# Cremonese vs Como > Serie A · Kickoff Sun 24 May 2026, 18:45 UTC · [Canonical HTML](https://betsprinter.com/fixtures/1021) **Status:** Scheduled ## Model verdict - **Cremonese win:** 10% - **Draw:** 18% - **Como win:** 72% - **Source:** model ## Top published picks | Market | Selection | Best odds | Bookmaker | Model % | Edge | | --- | --- | ---: | --- | ---: | ---: | | btts | No | 2.05 | 888Sport | 66% | +17.7 pp | | h2h | Away | 1.63 | 1xbet | 76% | +14.7 pp | | totals | Under | 2.25 | 1xbet | 51% | +7.0 pp | ## Pre-match deep dive ### Two contrasting runs collide as injuries shape final reckoning ## The stage A late-May Serie A fixture kicks off Sun 24 May 2026, 00:00 UTC, a match that folds into the domestic run-in and carries whatever competitive stakes each side still contests this season[^fact-1]. The temporal specificity places the game at the very end of the calendar month and marks it as one of the season’s closing tests[^fact-1]. ## Form & momentum Formlines draw a clear split. USC arrive on a run that reads WWLLD over their last 10 matches — 3-1-6 (W-D-L) — yielding 1.00 points per game, with an attacking output of 1.00 goals scored and 1.50 conceded per match[^fact-2]. By contrast, COM have been the hotter side across the same sample: WWDWL in the last 10 — 5-2-3 (W-D-L) — translating to 1.70 points per game, and symmetric offensive and defensive numbers of 1.70 goals scored and 1.00 conceded per match[^fact-3]. Those raw vectors point to a team (COM) that is getting more from both ends of the pitch in recent weeks and another (USC) that has struggled to find consistent returns, particularly in attack where their goals per game sit at 1.00[^fact-2][^fact-3]. Momentum, then, is tilted toward the visitors on form alone[^fact-3]. ## Personnel Spotlight players on either side have driven recent output. Federico Bonazzoli is the standout in-form figure for USC with 2 goals in his last five appearances, no assists, and an average match rating of 7.29 across that run[^fact-4]. For COM, Lucas Da Cunha carries the attack-minded upside: 1 goal and 1 assist in his last five outings and an average rating of 7.43[^fact-5]. Those short-term numbers frame both as go-to contributors in tight moments[^fact-4][^fact-5]. Availability alters picture. USC will be without Romano Floriani Mussolini due to injury; his absence removes a player who logged 346 minutes in the recent run, a chunk of playing time that affected rotation and match rhythm[^fact-6]. COM miss Nico Paz through injury as well; Paz accumulated 753 minutes in the recent run, indicating he was a consistent presence whose absence will have a larger minutes-shaped effect on selection and tactical balance[^fact-7]. Both absences matter, but the raw minutes suggest COM have lost a longer-running on-field contributor[^fact-6][^fact-7]. ## Where the model sees value The quantitative read is straightforward: COM’s superior points-per-game (1.70 vs 1.00) and better goal differential profile in the recent sample (1.70 scored / 1.00 conceded vs 1.00 scored / 1.50 conceded) mark them as the cleaner side over the last 10 matches[^fact-2][^fact-3]. That statistical tilt creates two natural angles for an edge-seeking model. First, lines that underweight COM’s higher recent scoring rate are exploitable; their 1.70 goals per match in the sample suggests a greater likelihood of generating clear chances through the run than USC’s 1.00[^fact-3][^fact-2]. Second, markets that assume parity in defensive solidity miss how COM have conceded just 1.00 per match in this period compared with USC’s 1.50, a differential that compounds COM’s offensive advantage[^fact-3][^fact-2]. Contextual caveats matter: the absences change personnel probabilities. USC’s loss of a 346-minute contributor and COM’s absence of a 753-minute regular shift the expected lineups and could compress or expand those edges depending on the actual replacements and system tweaks made on matchday[^fact-6][^fact-7]. No market odds or implied probabilities are supplied in the available facts, so the model flags these structural edges without attaching specific price targets. ## Verdict The model leans toward the side with better recent balance: COM’s higher points-per-game and stronger goals-for/goals-against profile across the last 10 matches give them the statistical initiative, while the minutes lost to injury (especially the 753 minutes tied to COM’s absence) are the principal uncertainty that could blunt or accentuate that advantage[^fact-3][^fact-7]. ### Cited facts [^fact-1]: **Kickoff** — Sun 24 May 2026, 00:00 UTC — Serie A [^fact-2]: **USC recent form** — WWLLD last 10: 3-1-6 (W-D-L), 1.00 PPG, 1.00 goals scored / 1.50 conceded per match. [^fact-3]: **COM recent form** — WWDWL last 10: 5-2-3 (W-D-L), 1.70 PPG, 1.70 goals scored / 1.00 conceded per match. [^fact-4]: **USC in-form player** — Federico Bonazzoli — 2 goals, 0 assists in last 5 appearances, avg rating 7.29. [^fact-5]: **COM in-form player** — Lucas Da Cunha  — 1 goals, 1 assists in last 5 appearances, avg rating 7.43. [^fact-6]: **USC key absence** — Romano Floriani Mussolini out (injury), 346 minutes in recent run. [^fact-7]: **COM key absence** — Nico Paz out (injury), 753 minutes in recent run. --- Methodology: . Canonical HTML: .