# Cremonese vs Pisa > Serie A · Kickoff Sun 10 May 2026, 13:00 UTC · [Canonical HTML](https://betsprinter.com/fixtures/751) **Status:** Finished **Final score:** Cremonese 3–0 Pisa ## Model verdict - **Cremonese win:** 81% - **Draw:** 11% - **Pisa win:** 8% - **Source:** model ## Pre-match deep dive ### Clear Home Advantage Meets Fragile Defences in Key Weekend Clash ## The stage A mid-May Serie A fixture kicks off on Sun 10 May 2026 at 13:00 UTC, offering a final splash of top-flight urgency before the season's run-in[^fact-1]. The model assigns a dominant probability to the home side, putting the match-win outlook at Home 81% / Draw 11% / Away 8%[^fact-2]. That skew frames this as a game where the home team is expected to control the narrative from the start[^fact-2]. ## Form & momentum Recent results underline a pair of low-output campaigns for both sides. The home team has produced a sequence logged as LLDLL across the last 10 matches, translating to 1 win, 1 draw and 8 losses, with 0.40 points per game and 0.60 goals scored per match against 2.00 conceded[^fact-4]. The visitors arrive in even worse rhythm: LLLLL across their last 10 with 1 win, 0 draws and 9 losses, 0.30 points per game and 0.50 goals scored per match against 2.10 conceded[^fact-5]. Those raw results are mirrored by a substantive Elo gap: the model applies a +140-point Elo differential in favour of the home side after accounting for venue effects[^fact-3]. The 140-point edge helps explain the model’s strong home probability and suggests the home team’s baseline quality advantage outweighs both sides’ recent defensive fragility[^fact-3][^fact-4][^fact-5]. ## Personnel Offensive production has been limited, but a couple of individuals stand out. Federico Bonazzoli is the home side’s most notable in-form attacker, returning 2 goals and 0 assists in his last 5 appearances and carrying an average match rating of 7.10 over that span[^fact-8]. On the visitor side, Simone Canestrelli has contributed 1 goal and 0 assists in his last 5 appearances with an average rating of 6.69[^fact-9]. Absences sharpen the tactical picture. The home team will be missing Federico Baschirotto through injury; he accumulated 291 minutes in the recent run prior to his unavailability[^fact-10]. The visitors are without Matteo Tramoni, who had 382 minutes in the recent stretch before his injury absence[^fact-11]. Those minutes figures quantify the defensive and midfield disruption each side must manage and help explain the elevated goals-against rates seen in both teams’ recent records[^fact-4][^fact-5][^fact-10][^fact-11]. ## Where the model sees value Three market lines were analysed against the model’s probabilities[^fact-12]. The clearest edge sits on the home match-winner: the model prices Home at 75% while the market quote available at 22Bet was 2.04, producing an edge of 26.5 percentage points and flagged with high confidence by the model[^fact-6][^fact-12]. That divergence aligns with the model’s 81% match-win probability for the home side and the substantial Elo cushion[^fact-2][^fact-3]. A secondary market signal appears on Both Teams to Score (BTTS). The model assigns a 54% chance to BTTS while the Betfair Exchange market offered 2.10, giving a modest edge of 5.9 percentage points and a mid confidence grade[^fact-7][^fact-12]. The underlying case for BTTS is the combination of very low scoring rates for both sides but disproportionately higher goals conceded figures: the home team concedes 2.00 per match and the visitors 2.10 per match in their recent runs[^fact-4][^fact-5]. Those conceded rates increase the plausibility of both sides finding the net despite their limited attacking returns[^fact-4][^fact-5]. ## Verdict The model leans decisively to the home side, with Home 81% / Draw 11% / Away 8% as the central projection and an Elo advantage of +140 points underpinning that stance[^fact-2][^fact-3]. Personnel gaps on both teams and the low recent scoring combine to make this look like a home win likely to include goals at both ends, according to the model’s preferred market edges[^fact-4][^fact-5][^fact-6][^fact-7]. ### Cited facts [^fact-1]: **Kickoff** — Sun 10 May 2026, 13:00 UTC — Serie A [^fact-2]: **Model verdict** — Home 81% / Draw 11% / Away 8% (source: model; confidence high, 70 pp gap to runner-up). [^fact-3]: **Elo edge** — USC vs PIS — Elo differential +140 points (with home advantage applied). [^fact-4]: **USC recent form** — LLDLL last 10: 1-1-8 (W-D-L), 0.40 PPG, 0.60 goals scored / 2.00 conceded per match. [^fact-5]: **PIS recent form** — LLLLL last 10: 1-0-9 (W-D-L), 0.30 PPG, 0.50 goals scored / 2.10 conceded per match. [^fact-6]: **Value pick #1** — Home in Match Winner — model 75% vs market price 2.04 at 22Bet, edge 26.5 pp (high confidence). [^fact-7]: **Value pick #2** — Yes in Both Teams to Score — model 54% vs market price 2.10 at Betfair Exchange, edge 5.9 pp (mid confidence). [^fact-8]: **USC in-form player** — Federico Bonazzoli — 2 goals, 0 assists in last 5 appearances, avg rating 7.10. [^fact-9]: **PIS in-form player** — Simone Canestrelli — 1 goals, 0 assists in last 5 appearances, avg rating 6.69. [^fact-10]: **USC key absence** — Federico Baschirotto out (injury), 291 minutes in recent run. [^fact-11]: **PIS key absence** — Matteo Tramoni out (injury), 382 minutes in recent run. [^fact-12]: **Markets analysed** — 3 market(s) compared against the model. --- Methodology: . Canonical HTML: .