Millwall
Millwall operate as a tightly controlled defensive unit, conceding just 1.41 xG per match whilst generating a modest 1.48 in attack—a profile built on organisation rather than creation. Recent form has been frustratingly inconsistent, with one win sandwiched between four non-wins across their last five matches, suggesting they're struggling to convert their defensive solidity into points. With no immediate fixtures in the forecast window, the model will next calibrate when fresh matchdays emerge. Bawler's Banker selections on Millwall have landed at 60% across the sample, indicating reasonable predictive grip on their low-variance, hard-to-beat approach.
How to read this: the green bar shows the average goals Millwall 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: Championship average — if the bar extends past the diamond, Millwall are above average there.
How to read this: the solid line is the goals Millwall 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 Millwall's perspective. Tap a tile to see Bawler's full prediction for that match.
When Bawler issues a Banker pick on a Millwall fixture, the model lands 3 out of 5 (60%). Every pick is logged before kickoff and settled publicly.
How to read this: each row groups settled Banker picks Bawler issued on Millwall 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 Millwall matches.