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Monza cruise to a comfortable 1-3 victory over Cesena.

📝 Match Report

How It Unfolded

Monza beat Cesena 1-3 at Stadio Dino Manuzzi, Regular Season - 28, in the Serie B. With the result on the board, the sections below measure it against everything the model and the numbers projected in advance.

The Model vs The Result

The Poisson model went into this projecting Cesena 1.00 xG and Monza 1.36 xG, a combined 2.36. The scoreboard read 1-3 for 4 actual goals. Monza outscored their 1.36 projection by 1.6. Those figures were built on strength ratings of Cesena attack 0.97 / defence 1.31 against Monza attack 0.94 / defence 0.82, drawn from 65/27 games (CurrentSeason).

On the result, the model split it Cesena 26% | Draw 30% | Monza 44%, with Monza to win its most likely call at 44%. That is exactly how it finished — the model's leading outcome was vindicated.

Goals & Markets

The model rated Over 2.5 goals at 42%. The game delivered 4, so it went over — the opposite of the projected direction. Over 1.5 had been 69% and landed. Over 3.5 was 21% and came in. On both teams to score, the model sat at 48% and the match saw both sides score — a miss on BTTS. Historically the two sides average 46% Over 2.5 across their same-competition games (Cesena 45%, Monza 48%), a base rate that pointed the other way from today's over. Their combined BTTS history runs at 55%, which matched the both-scored outcome.

Trading Patterns vs Reality

Cesena's trading profile (65 games, 31 home) set some clear expectations: BTTS lands in 58% of their matches — today it did.

Monza's trading profile (65 games, 31 away) set some clear expectations: BTTS lands in 51% of their matches — today it did.

Form vs Result

The form lines were close — Cesena 1.35 PPG, Monza 1.15 PPG — offering no strong steer, and the Monza win broke the near-deadlock. Cesena (home/away splits) shipped 3 against a 1.23 concession average — a leakier day than usual. Monza (home/away splits) scored 3 against a 1.00 average — above their attacking norm.

Verdict

Grading the result against the stored data, 1 of 3 pre-match signals came in: result (hit), Over 2.5 (miss), BTTS (miss). The data was on the wrong side of this result more often than not — a reminder that a single match sits well inside the model's variance.

💡 Key Insights