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Prediction vindicated as AS Roma edge out Parma 0-1.

📝 Match Report

How It Unfolded

AS Roma beat Parma 0-1 at Stadio Ennio Tardini, Regular Season - 25, 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 Parma 1.28 xG and AS Roma 1.67 xG, a combined 2.95. The scoreboard read 0-1 for 1 actual goal. Parma fell 1.3 short of their projected output. Those figures were built on strength ratings of Parma attack 0.93 / defence 1.41 against AS Roma attack 0.92 / defence 1.02, drawn from 24/62 games (CurrentSeason).

On the result, the model split it Parma 26% | Draw 30% | AS Roma 43%, with AS Roma to win its most likely call at 43%. That is exactly how it finished — the model's leading outcome was vindicated.

Goals & Markets

The model rated Over 2.5 goals at 56%. The game delivered 1, so it stayed under — the opposite of the projected direction. Over 1.5 had been 82% and missed. On both teams to score, the model sat at 62% and the match did not — a miss on BTTS. Historically the two sides average 56% Over 2.5 across their same-competition games (Parma 56%, AS Roma 55%), a base rate that pointed the other way from today's under. Their combined BTTS history runs at 64%, which did not match the one-sided outcome.

Trading Patterns vs Reality

Parma's trading profile (62 games, 31 home) set some clear expectations: BTTS lands in 68% of their matches — today it did not.

AS Roma's trading profile (62 games, 31 away) set some clear expectations: BTTS lands in 60% of their matches — today it did not.

Form vs Result

The form lines were close — Parma 1.55 PPG, AS Roma 1.56 PPG — offering no strong steer, and the AS Roma win broke the near-deadlock. Parma (home/away splits) managed 0 against a 1.68 scoring average — below par going forward. AS Roma (home/away splits) conceded 0 against a 1.42 average — tighter than their form line.

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