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Shock result as Lecce defy the odds to beat Monza 2-1.

📝 Match Report

How It Unfolded

Lecce beat Monza 2-1 at Stadio Ettore Giardiniero - Via del Mare, Regular Season - 16, in the Serie A. 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 Lecce 1.02 xG and Monza 1.30 xG, a combined 2.32. The scoreboard read 2-1 for 3 actual goals. Lecce beat their projection by 1.0 — clinical relative to the chances the model priced in. Those figures were built on strength ratings of Lecce attack 0.82 / defence 1.18 against Monza attack 0.84 / defence 0.93, drawn from 53/53 games (CurrentSeason).

On the result, the model split it Lecce 29% | Draw 28% | Monza 43%, with Monza to win its most likely call at 43%. The actual Lecce win had been the model's second-ranked read at 29%, so the result diverged from the top call without being a shock.

Goals & Markets

The model rated Over 2.5 goals at 41%. The game delivered 3, so it went over — the opposite of the projected direction. Over 1.5 had been 67% and landed. On both teams to score, the model sat at 46% and the match saw both sides score — a miss on BTTS. Historically the two sides average 37% Over 2.5 across their same-competition games (Lecce 36%, Monza 38%), a base rate that pointed the other way from today's over. Their combined BTTS history runs at 43%, which did not match the both-scored outcome.

Trading Patterns vs Reality

Lecce's trading profile (53 games, 26 home) set some clear expectations: BTTS lands in 40% of their matches — today it did.

Monza's trading profile (53 games, 26 away) set some clear expectations: BTTS lands in 47% of their matches — today it did.

Form vs Result

The form lines were close — Lecce 0.96 PPG, Monza 1.04 PPG — offering no strong steer, and the Lecce win broke the near-deadlock. Lecce (home/away splits) scored 2 against a 0.88 average — above their attacking norm.

Verdict

Grading the result against the stored data, 0 of 3 pre-match signals came in: result (miss), 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