St. Pauli
St. Pauli operate as a transitional side caught between offensive ambition and defensive fragility, generating 1.36 xG per match while shipping 1.52—a profile suggesting they create chances but lack the clinical edge to capitalise consistently. Recent form has stalled entirely, yielding one draw and three losses across their last five matches, a run that underscores their vulnerability when efficiency dips. With no fixtures scheduled in the immediate window, the focus shifts to their next outing, where the Poisson model will illuminate whether this slump reflects tactical adjustment or genuine underlying weakness. Bawler's 80% banker hit rate on St. Pauli matches suggests strong predictive traction on their matches when the model identifies clear asymmetries.
How to read this: the green bar shows the average goals St. Pauli 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 GERMANY: Bundesliga average — if the bar extends past the diamond, St. Pauli are above average there.
How to read this: the solid line is the goals St. Pauli 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 St. Pauli's perspective. Tap a tile to see Bawler's full prediction for that match.
When Bawler issues a Banker pick on a St. Pauli 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.