# AC Milan vs Cagliari > Serie A · Kickoff Sun 24 May 2026, 18:45 UTC · [Canonical HTML](https://betsprinter.com/fixtures/1026) **Status:** Finished **Final score:** AC Milan 1–2 Cagliari ## Model verdict - **AC Milan win:** 78% - **Draw:** 14% - **Cagliari win:** 8% - **Source:** model ## Pre-match deep dive ### Heavy favourites tasked with seeing off stubborn visitors ## The stage A late-Sunday Serie A fixture kicks off at 18:45 UTC on 24 May 2026[^fact-1]. The match pairs a clear home favourite against an away side that has struggled for consistency this season; the model makes that gap explicit in its match probabilities[^fact-2]. ## Form & momentum The numerical story is straightforward. Milan carry a substantial Elo edge into the game — an advantage of +328 points after home advantage is applied[^fact-3]. Recent league form for Milan reads WLLDW over the last ten matches, translating to 4 wins, 1 draw and 5 losses, with 1.30 points per game and a scoring/defensive profile of 0.90 goals scored and 1.30 conceded per match[^fact-4]. Cagliari arrive with a record of WLDWL in their last ten, a 3-1-6 split, averaging 1.00 points per game and producing 0.90 goals while conceding 1.60 on average[^fact-5]. On balance the underlying numbers favour the home side: higher points per game, a sizeable Elo cushion and marginally better defensive numbers than their opponents[^fact-3][^fact-4][^fact-5]. ## Personnel Milan’s most notable in-form profile belongs to Adrien Rabiot, who has contributed 1 goal and 0 assists across his last five appearances and carries an average match rating of 7.09 in that run[^fact-8]. Cagliari’s best recent attacking return comes from Paul Mendy, with 2 goals, 0 assists and an average rating of 6.81 over his last five matches[^fact-9]. Availability is a factor for both sides: Milan will be without Samuele Ricci due to injury — Ricci logged 288 minutes in the recent run before his absence[^fact-10] — while Cagliari are missing Michael Folorunsho, who accounted for 665 minutes in their recent minutes tally prior to injury[^fact-11]. Those absences remove midfield minutes and influence rotation options without altering the raw model probabilities already cited[^fact-2][^fact-10][^fact-11]. ## Where the model sees value Two distinct edges stand out when the model is compared to market pricing across three markets analysed[^fact-12]. First, the model favours the Under 2.5 goals market with a 62% probability against a market price implying a lower probability at 2.25 on 1xbet — an edge of 17.7 percentage points and flagged with high confidence by the model[^fact-6]. Given the recent goals data (both teams averaging 0.90 goals scored in their respective recent runs) that projection aligns with a low-scoring expectation from both sides[^fact-4][^fact-5]. Second, the match-winner market is tilted toward the hosts: the model assigns a 78% chance to the home win versus a market price on 1xbet that implies less certainty at odds of 1.33, yielding a smaller edge of 3.1 percentage points and lower confidence[^fact-2][^fact-7]. That is consistent with the +328 Elo differential and the model’s outright probabilities, but the model itself marks this as a low-confidence value relative to the Under 2.5 projection[^fact-3][^fact-2][^fact-7]. Across the three markets analysed the clearest, highest-confidence divergence is the unders market; the home-match pick carries a meaningful model probability but with lower confidence in the edge estimate[^fact-12][^fact-6][^fact-7]. ## Verdict The model leans decisively to the home side (78% home win probability) with an expectation of a tight, low-scoring game — the strongest single market edge being Under 2.5 goals at 62% versus market pricing[^fact-2][^fact-6]. The contest looks framed as an Elo-backed home favourite managing a compact game against an opponent that concedes more and has fewer consistent attacking returns[^fact-3][^fact-5][^fact-9]. ### Cited facts [^fact-1]: **Kickoff** — Sun 24 May 2026, 18:45 UTC — Serie A [^fact-2]: **Model verdict** — Home 78% / Draw 14% / Away 8% (source: model; confidence high, 64 pp gap to runner-up). [^fact-3]: **Elo edge** — MIL vs CAG — Elo differential +328 points (with home advantage applied). [^fact-4]: **MIL recent form** — WLLDW last 10: 4-1-5 (W-D-L), 1.30 PPG, 0.90 goals scored / 1.30 conceded per match. [^fact-5]: **CAG recent form** — WLDWL last 10: 3-1-6 (W-D-L), 1.00 PPG, 0.90 goals scored / 1.60 conceded per match. [^fact-6]: **Value pick #1** — Under in Goals O/U 2.5 — model 62% vs market price 2.25 at 1xbet, edge 17.7 pp (high confidence). [^fact-7]: **Value pick #2** — Home in Match Winner — model 78% vs market price 1.33 at 1xbet, edge 3.1 pp (low confidence). [^fact-8]: **MIL in-form player** — Adrien Rabiot — 1 goals, 0 assists in last 5 appearances, avg rating 7.09. [^fact-9]: **CAG in-form player** — Paul Mendy  — 2 goals, 0 assists in last 5 appearances, avg rating 6.81. [^fact-10]: **MIL key absence** — Samuele Ricci out (injury), 288 minutes in recent run. [^fact-11]: **CAG key absence** — Michael Folorunsho out (injury), 665 minutes in recent run. [^fact-12]: **Markets analysed** — 3 market(s) compared against the model. --- Methodology: . 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