Charlotte
Charlotte operate as a below-average attacking side with a lean defensive profile—1.27 xG for against 1.49 conceded marks a team vulnerable to pressure. Recent form shows volatility across seven settled fixtures, though they've managed four wins alongside two losses and a draw, suggesting inconsistency rather than directional trend. With no upcoming fixtures in the current window, focus shifts to the underlying model: Bawler's banker selections on Charlotte have landed at 57% hit rate, indicating modest predictive edge on this squad's performances going forward.
How to read this: the green bar shows the average goals Charlotte 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 USA: MLS average — if the bar extends past the diamond, Charlotte are above average there.
How to read this: the solid line is the goals Charlotte 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 Charlotte's perspective. Tap a tile to see Bawler's full prediction for that match.
When Bawler issues a Banker pick on a Charlotte fixture, the model lands 4 out of 8 (50%). This sits below the cross-league baseline — the model finds this team harder to read than most. Every pick is logged before kickoff and settled publicly.
How to read this: each row groups settled Banker picks Bawler issued on Charlotte 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 Charlotte matches.