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Prediction vindicated as Sassuolo edge out Salernitana 1-2.

📝 Match Report

How It Unfolded

Sassuolo beat Salernitana 1-2 at Stadio Arechi, Regular Season - 21, in the Serie B. The remainder of the report sets that outcome against the pre-match model, the markets and the teams' data profiles.

The Model vs The Result

The Poisson model went into this projecting Salernitana 1.14 xG and Sassuolo 1.64 xG, a combined 2.77. The scoreboard read 1-2 for 3 actual goals. Both sides finished within a goal of their individual projections, so the scoreline sat close to the model's expected shape. Those figures were built on strength ratings of Salernitana attack 0.89 / defence 1.28 against Sassuolo attack 1.24 / defence 1.04, drawn from 20/20 games (CurrentSeason).

On the result, the model split it Salernitana 25% | Draw 28% | Sassuolo 47%, with Sassuolo to win its most likely call at 47%. The result followed the model's preferred path, landing its top-rated outcome.

Goals & Markets

The model rated Over 2.5 goals at 52%. The game delivered 3, so it went over — in line with the projection. Over 1.5 had been 78% and landed. On both teams to score, the model sat at 57% and the match saw both sides score — another call in the model's favour. Historically the two sides average 56% Over 2.5 across their same-competition games (Salernitana 57%, Sassuolo 55%), a base rate that agreed with today's over. Their combined BTTS history runs at 58%, which matched the both-scored outcome.

Trading Patterns vs Reality

Salernitana's trading profile (58 games, 29 home) set some clear expectations: BTTS lands in 55% of their matches — today it did.

Sassuolo's trading profile (58 games, 29 away) set some clear expectations: BTTS lands in 60% of their matches — today it did.

Form vs Result

On form, Sassuolo arrived the stronger side — 1.31 PPG against 0.60. Form held, and they took the win.

Verdict

Grading the result against the stored data, 4 of 4 pre-match signals came in: result (hit), Over 2.5 (hit), BTTS (hit), form (hit). A strong night for the model: the result sat comfortably inside what the pre-match data projected.

💡 Key Insights