Kamil Majchrzak vs Alejandro Tabilo: AI Prediction | Games, Spread, Aces & Double Faults

The model's edge for Tabilo comes mainly from surface fit, head-to-head and recent-form components. Notably, the model attributes +4.4 percentage points to surface fit and +3.5 to head-to-head in Tabilo’s favor; this is interesting given Majchrzak’s higher surface strength index (24.60) compared to Tabilo’s 7.69. In other words, the internal model weighting still favors Tabilo on grass despite that surface-strength number, so expect the model to be counting other grass-related match-up signals in Tabilo’s favour. The recent-form driver also nudges toward Tabilo (+3.1), per the explainability output, even though the raw recent results show Majchrzak with stronger outcomes. Rank and ratings are close: Majchrzak is ranked 45 with an Elo of 1676, Tabilo 33 with Elo 1662; neither player carries tournament fatigue. Majchrzak presents stronger return numbers (mean return index 94.90 vs Tabilo’s 86.73 — a >5 point gap), and the model gives Majchrzak a +2.7 boost for serve & return. Their mean serve indices are similar (97.07 vs 96.42), so no big serve-rating gap. Over the last three matches Majchrzak went 2–1 with two notable wins on grass, while Tabilo’s last three are 0–3 with straight-set losses at Mallorca and in London and a tough clay loss — a form picture that contrasts with the model’s recent-form weighting.