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Shock result as Frosinone defy the odds to beat Brescia 2-1.

📝 Match Report

How It Unfolded

Frosinone beat Brescia 2-1 at Stadio Benito Stirpe, Regular Season - 30, 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 Frosinone 0.94 xG and Brescia 1.13 xG, a combined 2.07. The scoreboard read 2-1 for 3 actual goals. Frosinone beat their projection by 1.1 — clinical relative to the chances the model priced in. Those figures were built on strength ratings of Frosinone attack 0.80 / defence 1.25 against Brescia attack 0.82 / defence 0.97, drawn from 29/67 games (CurrentSeason).

On the result, the model split it Frosinone 28% | Draw 34% | Brescia 38%, with Brescia to win its most likely call at 38%. The actual Frosinone win had been the model's second-ranked read at 28%, so the result diverged from the top call without being a shock.

Goals & Markets

The model rated Over 2.5 goals at 34%. The game delivered 3, so it went over — the opposite of the projected direction. Over 1.5 had been 63% and landed. On both teams to score, the model sat at 43% and the match saw both sides score — a miss on BTTS. Historically the two sides average 44% Over 2.5 across their same-competition games (Frosinone 52%, Brescia 36%), a base rate that pointed the other way from today's over. Their combined BTTS history runs at 57%, which matched the both-scored outcome.

Trading Patterns vs Reality

Frosinone's trading profile (67 games, 34 home) set some clear expectations: BTTS lands in 60% of their matches — today it did.

Brescia's trading profile (67 games, 34 away) set some clear expectations: BTTS lands in 55% of their matches — today it did.

Form vs Result

The form lines were close — Frosinone 0.97 PPG, Brescia 1.18 PPG — offering no strong steer, and the Frosinone win broke the near-deadlock.

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