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Shock result as Lorient defy the odds to beat Grenoble 1-2.

📝 Match Report

How It Unfolded

Lorient beat Grenoble 1-2 at Stade des Alpes, Regular Season - 28, in the Ligue 2. 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 Grenoble 1.32 xG and Lorient 1.04 xG, a combined 2.37. The scoreboard read 1-2 for 3 actual goals. Lorient outscored their 1.04 projection by 1.0. Those figures were built on strength ratings of Grenoble attack 0.95 / defence 1.00 against Lorient attack 1.01 / defence 1.03, drawn from 65/27 games (CurrentSeason).

On the result, the model split it Grenoble 43% | Draw 28% | Lorient 29%, with Grenoble to win its most likely call at 43%. The actual Lorient win had been the model's second-ranked read at 29%, so the result diverged from the top call without being a shock.

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 68% and landed. On both teams to score, the model sat at 48% and the match saw both sides score — a miss on BTTS. Historically the two sides average 54% Over 2.5 across their same-competition games (Grenoble 49%, Lorient 59%), a base rate that agreed with today's over. Their combined BTTS history runs at 49%, which did not match the both-scored outcome.

Trading Patterns vs Reality

Grenoble's trading profile (61 games, 30 home) set some clear expectations: BTTS lands in 48% of their matches — today it did.

Lorient's trading profile (61 games, 30 away) set some clear expectations: BTTS lands in 51% of their matches — today it did.

Form vs Result

The form lines were close — Grenoble 1.31 PPG, Lorient 1.38 PPG — offering no strong steer, and the Lorient win broke the near-deadlock. Grenoble (home/away splits) shipped 2 against a 1.10 concession average — a leakier day than usual. Lorient (home/away splits) scored 2 against a 1.03 average — above their attacking norm.

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