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Prediction vindicated as Coventry edge out Preston 2-1.

📝 Match Report

How It Unfolded

Coventry beat Preston 2-1 at The Coventry Building Society Arena, Regular Season - 34, in the Championship. 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 Coventry 1.38 xG and Preston 0.99 xG, a combined 2.36. 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 Coventry attack 1.05 / defence 1.01 against Preston attack 0.95 / defence 0.98, drawn from 79/79 games (CurrentSeason).

On the result, the model split it Coventry 45% | Draw 28% | Preston 27%, with Coventry to win its most likely call at 45%. 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 3, so it went over — the opposite of the projected direction. Over 1.5 had been 69% and landed. On both teams to score, the model sat at 47% and the match saw both sides score — a miss on BTTS. Historically the two sides average 55% Over 2.5 across their same-competition games (Coventry 58%, Preston 52%), a base rate that agreed with today's over. Their combined BTTS history runs at 56%, which matched the both-scored outcome.

Trading Patterns vs Reality

Coventry's trading profile (79 games, 39 home) set some clear expectations: BTTS lands in 58% of their matches — today it did.

Preston's trading profile (79 games, 39 away) set some clear expectations: BTTS lands in 53% of their matches — today it did.

Form vs Result

The form lines were close — Coventry 1.41 PPG, Preston 1.33 PPG — offering no strong steer, and the Coventry win broke the near-deadlock.

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