Bote regular y velocidad media-alta: condiciones neutras, sin favorecer un estilo.
Ambiente cálido: la bola vuela algo más y el físico cuenta.
Aire húmedo: la bola pierde algo de velocidad.
Algo de viento: dificulta el control desde el fondo.
La superficie sí entra en el modelo (la especialización por superficie es uno de sus factores). El clima y la altitud son contexto que publicamos para ti — NO mueven la probabilidad.
›Ranking: #100 vs #143 (mejor clasificado)
›Forma reciente: 3/10 en los últimos partidos
›Modelo 51% vs mercado 75% → el modelo lo ve menos probable que la cuota
!Vuelve tras un parón largo (22d) — posible falta de ritmo
Fearnley holds a clear ranking edge (#100 vs #143) and Elo advantage (+85 points: 1913 vs 1828). His ranking trajectory is also steeper (+59 trend vs +15). These metrics align and form the primary structural advantage for the favorite, grounding the model's 51% probability. However, the gap is neither enormous nor decisive—both are upper-mid ATP players—and ranking alone does not overcome other match dynamics.
Both players arrive with identical recent form: two-match winning streaks and 5 wins in their last 10 matches, with no standout quality wins. This neutrality is notable—neither is hot or cold. However, the fatigue picture diverges sharply. Fearnley has played 5 matches in 14 days (including the US Open semifinal reached 1 day ago), accumulating match stress, while Rodionov has played only 3 matches in the same window. At this intensity level, cumulative fatigue compounds. Rodionov enters with fresher legs and a lower match load.
On hard courts, Fearnley's win rate is 32%, a 7-point deficit versus his 39% baseline—a minor penalty but present. Rodionov has no hard-court baseline published, so no comparison. Serve is neutral (both 64%), but Fearnley's return (42%) edges Rodionov's (38%), a small advantage in break-point conversion. The warm, humid, windy conditions (27°C, 75% humidity, 24 km/h) will lengthen rallies and dampen pace, but neither player has a documented weakness that the weather would expose decisively.
Both players reached the US Open semifinals 1 day ago and are competing again immediately, magnifying fatigue risk. This is not a neutral or early-round context; it is a grind. For Fearnley, who entered as higher-ranked favorite and has already logged more recent matches, the toll is asymmetric. Rodionov, despite lower ranking, may carry less cumulative strain and recover faster from the semifinal effort. The schedule congestion and deep-run fatigue flag both players but operates against the fresher opponent.
The model assigns 51% to Fearnley; the market (odds 1.31) implies 76%. This 25-point gap signals overpricing. At 1.31 odds, Fearnley's fair value would require ~65–70% true win probability to justify a -33.3% expected value. The model does not see that edge—ranking and Elo provide a modest 51% lean, while form is neutral, surface slightly negative, and fatigue favors the underdog. The odds overweight Fearnley's rank and undervalue Rodionov's fresher state and recent form parity. Betting Fearnley at 1.31 is a poor proposition.
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.