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Prediction vindicated as MVV edge out VVV Venlo 2-1.

📝 Match Report

How It Unfolded

MVV beat VVV Venlo 2-1 at De Geusselt, Regular Season - 31, in the Eerste Divisie. 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 MVV 1.70 xG and VVV Venlo 1.48 xG, a combined 3.18. The scoreboard read 2-1 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 MVV attack 1.05 / defence 1.07 against VVV Venlo attack 0.94 / defence 0.99, drawn from 68/68 games (CurrentSeason).

On the result, the model split it MVV 42% | Draw 25% | VVV Venlo 33%, with MVV to win its most likely call at 42%. The result followed the model's preferred path, landing its top-rated outcome.

Goals & Markets

The model rated Over 2.5 goals at 62%. The game delivered 3, so it went over — in line with the projection. Over 1.5 had been 83% and landed. On both teams to score, the model sat at 64% and the match saw both sides score — another call in the model's favour. Historically the two sides average 59% Over 2.5 across their same-competition games (MVV 59%, VVV Venlo 59%), a base rate that agreed with today's over. Their combined BTTS history runs at 51%, which matched the both-scored outcome.

Trading Patterns vs Reality

MVV's trading profile (68 games, 33 home) set some clear expectations: BTTS lands in 52% of their matches — today it did.

VVV Venlo's trading profile (68 games, 33 away) set some clear expectations: BTTS lands in 50% of their matches — today it did.

Form vs Result

The form lines were close — MVV 1.06 PPG, VVV Venlo 1.15 PPG — offering no strong steer, and the MVV win broke the near-deadlock.

Verdict

Grading the result against the stored data, 3 of 3 pre-match signals came in: result (hit), Over 2.5 (hit), BTTS (hit). A strong night for the model: the result sat comfortably inside what the pre-match data projected.

💡 Key Insights