Hull operate as a careful, defensive-minded outfit, conceding marginally more than they create—1.31 xG for against 1.57 against per match. Their recent five-game run reflects this cautious profile: two wins bookended four draws without loss, a pattern that mirrors their restricted attacking output. With no imminent fixtures in the prediction window, the immediate focus rests on identifying upcoming opportunities where their defensive solidity offers value. Bawler's model has proved reliable on Hull selections, landing 80 per cent of banker picks across the sample.
How to read this: the green bar shows the average goals Hull 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, Hull are above average there.
How to read this: the solid line is the goals Hull 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 Hull's perspective. Tap a tile to see Bawler's full prediction for that match.
When Bawler issues a Banker pick on a Hull 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.