CÓMO IMPORTA CADA FACTOR
Level (Elo/ranking)▸ Birrell●●●
Birrell (Elo 1631, ranking #69) outranks Rakhimova (Elo 1564, ranking #83) by 67 Elo points and 14 places. Model gives 50/50, but raw hierarchy favors opponent.
Surface▸ Birrell●●●
Hard court penalizes Rakhimova: 26% vs baseline 35% (−9 pts), favors Birrell 51% vs baseline 44% (+7 pts). Rakhimova's weakness on hard is structural.
Serve/Return▸ Birrell●●
Birrell serves 59% (vs Rakhimova 55%) and returns identically at 41% (vs Rakhimova 44%). Opponent edges on serve; Rakhimova's return edge marginal on hard.
Rest/Fatigue▸ Rakhimova●●
Rakhimova has 7 days since last match; Birrell 11 days. Rakhimova fresher, but returning from 42-day layoff risks rustiness despite better recent activity (2 matches in 14 days vs 1).
Form▸ Rakhimova●●
Rakhimova 4-6 (L1), Birrell 3-7 (L3). Both struggling; Rakhimova's record slightly better and streak shorter. Neither has quality wins. Minimal edge.
Head-to-head▸ Rakhimova●
3 meetings: Rakhimova 2-1. Recent (2024) split 1-1, with Rakhimova winning last. Thin sample, recent dead-even.
Weather= Igualado●
28°C, 78% humidity, 4 km/h wind. Warm and humid lengthens rallies slightly but no extreme conditions. Neutral impact.
SURFACE WEAKNESS
Hard court is Rakhimova's structural vulnerability. She wins only 26% of points on hard vs her 35% baseline—a 9-point deficit. Birrell, conversely, produces 51% on hard (+7 vs baseline 44%), indicating genuine comfort on the surface. This is not a small edge: a 16-point swing in surface suitability strongly favors the opponent in a match where both players are technically even on ranking alone.
HIERARCHY AND SERVE
Birrell holds a 67-point Elo advantage (1631 vs 1564) and ranks 14 places higher (#69 vs #83), undercutting the model's 50/50 calibration. Her serve is also measurably superior: 59% vs Rakhimova's 55%. On hard court—where serve speed and angle matter most—this serve advantage compounds the surface problem for Rakhimova. Rakhimova's return (44%) offers only a marginal reply to Birrell's return (41%), and on a surface where Rakhimova struggles fundamentally, her return strength cannot fully compensate for Birrell's serve edge.
REST AND FORM NOISE
Rakhimova arrives fresher (7 days vs Birrell's 11) and has played more recently (2 matches in 14 days vs 1). However, she is returning from a 42-day layoff—a flag for possible rustiness. Birrell, meanwhile, is in a 3-match losing streak and sits 3-7 over her last 10; Rakhimova is 4-6. Both are struggling, but Rakhimova's streak is at least only 1 loss. Form does not favor either player reliably, though Rakhimova's fresher active schedule might edge recovery over extended rest.
HEAD-TO-HEAD AND CONTEXT
Rakhimova leads 2-1 in three meetings and won the most recent encounter in 2024, but the sides split their 2024 contests. With only three matches, head-to-head has little predictive force and recent history is neutral. The tournament is Cincinnati (WTA tier, hard court), no contextual flags of note.
VALUE ASSESSMENT
The model prices Rakhimova at 50%, aligned with market odds (50%, 2.01). However, the underlying data—Birrell's 67-point Elo edge, hard-court surface suitability favoring Birrell (+7 vs −9), and serve advantage—suggest Birrell is the true favorite. Rakhimova's edge on rest and recent activity is real but modest and partially offset by rust risk. The EV is +1.5%, meaning the odds offer minimal margin. Favoring Rakhimova here requires confidence that her layoff will not hurt and that her form will stabilize faster than Birrell's; the data does not strongly support either assumption. The match is close, but the model's neutrality masks a structural lean toward Birrell.
Impacto y análisis a partir de datos reales del partido (Elo, forma, cara a cara, descanso, superficie vs base, clima, altitud). El modelo ≈ el mercado de media; la cuota ya captura casi toda la ventaja. +18 · juega con responsabilidad.