West Brom operate as a controlled, defensively sound side with an xG profile tilted towards solidity over flair—averaging 1.34 goals scored against 1.06 conceded per match. Recent form shows a stabilising pattern across five settled fixtures, combining two wins with two draws and a single loss, suggesting the underlying model is translating into results. With no immediate fixtures in the prediction window, the focus remains on their underlying structure: a team that shapes matches tightly and punishes slack opponents. Bawler's model has backed West Brom selections at an 80% banker hit rate, reflecting strong predictive alignment on their low-variance output profile.
How to read this: the green bar shows the average goals West Brom 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, West Brom are above average there.
How to read this: the solid line is the goals West Brom 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 West Brom's perspective. Tap a tile to see Bawler's full prediction for that match.
When Bawler issues a Banker pick on a West Brom fixture, the model lands 4 out of 5 (80%). This is well above the cross-league baseline of ~65%. Every pick is logged before kickoff and settled publicly.