Burnley
Burnley's underlying profile reveals a side fighting structural problems: they're creating just 1.00 xG per match whilst conceding 1.90, a pattern reflected in their recent run of one draw and three losses across four settled fixtures. The Poisson model consistently identifies value in their matches given the gap between actual defensive frailty and market pricing. With no fixtures in the immediate window, focus remains on how the model repositions when their next opponent is confirmed. Bawler's banker picks on Burnley have maintained a perfect 4/4 conversion rate, providing a reliable baseline for fixture analysis.
How to read this: the green bar shows the average goals Burnley 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 England: Premier League average — if the bar extends past the diamond, Burnley are above average there.
How to read this: the solid line is the goals Burnley 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 Burnley's perspective. Tap a tile to see Bawler's full prediction for that match.
When Bawler issues a Banker pick on a Burnley fixture, the model lands 5 out of 5 (100%). This is well above the cross-league baseline of ~65%. Every pick is logged before kickoff and settled publicly.