Chelsea
Chelsea's underlying attack profile is modest at 1.80 xG per match, while their defence leaks 1.41—a pattern consistent with a side that creates opportunities but fails clinical finishing and defensive discipline in equal measure. Recent form has been volatile across seven fixtures: two wins, one draw, and four losses illustrate inconsistency despite the underlying metrics suggesting competitive balance. With no imminent fixture in the prediction window, the focus remains on understanding their true performance level. Bawler's Poisson model has identified banker opportunities on Chelsea matches at a 71% hit rate, indicating strong predictive value in this team's volatility.
How to read this: the green bar shows the average goals Chelsea 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, Chelsea are above average there.
How to read this: the solid line is the goals Chelsea 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 Chelsea's perspective. Tap a tile to see Bawler's full prediction for that match.
When Bawler issues a Banker pick on a Chelsea fixture, the model lands 5 out of 8 (63%). Every pick is logged before kickoff and settled publicly.
How to read this: each row groups settled Banker picks Bawler issued on Chelsea 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 Chelsea matches.