Lorient
Lorient are a brittle attacking unit whose xG profile (1.31 for, 1.63 against) reveals a side struggling to create clear chances whilst remaining vulnerable to transition. Recent form has been inconsistent across seven matches—two wins, two draws, three losses—reflecting their inability to convert marginal opportunities into results. With no upcoming fixtures in the current window, focus remains on their underlying structure: the defensive fragility that continues to expose them in Ligue 1. Bawler's banker selections on Lorient have registered a 57% hit rate, suggesting the model identifies genuine edges in their matches despite surface-level volatility.
How to read this: the green bar shows the average goals Lorient were expected to score per match (their xG output). The red bar shows what opponents are expected to score against them. The diamond on each bar marks the FRANCE: Ligue 1 average — if the bar extends past the diamond, Lorient are above average there.
How to read this: the solid line is the goals Lorient actually scored each match. The dashed line is the goals the model expected them to score (xG). When the solid line is above the dashed, they overperformed — they finished better than the chances they created suggested. When it's below, they underperformed. Persistent underperformance often regresses; a one-off gap usually doesn't.
How to read this: each tile is one settled match, most recent first. Green = win, amber = draw, red = loss. Numbers show the actual scoreline from Lorient's perspective. Tap a tile to see Bawler's full prediction for that match.
When Bawler issues a Banker pick on a Lorient fixture, the model lands 4 out of 7 (57%). Every pick is logged before kickoff and settled publicly.
How to read this: each row groups settled Banker picks Bawler issued on Lorient fixtures by market type, so you can see where the model has the strongest read on this team. Higher hit rate = more reliable category for Lorient matches.