Emma Navarro vs Jessica Pegula: AI Prediction | Games, Spread, Aces & Double Faults

The model’s edge for Pegula comes mainly from overall strength, with additional weight from serve and return performance and better surface fit. Pegula’s superiority is visible in the numbers. She is ranked 3 versus Navarro at 28. Her Elo is 1984.9 compared with Navarro’s 1749.3. Pegula’s form index sits at 46.7, higher than Navarro’s 36.8. Those factors together move the prediction toward Pegula, reflecting the 10.2 and 7.2 percentage point contributions flagged by the model. Surface and workload also matter here. Pegula’s surface strength index on hard courts is 73.7, far above Navarro’s 24.1, which helps explain the surface fit advantage. Navarro has logged more minutes on court at this event, 136 minutes versus Pegula’s 91 minutes, so fatigue favors Pegula. Serve profiles are similar on paper, with mean serve indices of 96.9 for Pegula and 95.8 for Navarro, so neither player holds a massive edge in pure serve power. Navarro’s mean return index is 93.2, marginally higher than Pegula’s 88.3, but that gap is below a 5 point threshold so it is not treated as decisive. Over the last three matches Navarro is 1-2, with a recent Cincinnati win that lasted 136 minutes and two prior losses. Pegula is 2-1 in her last three matches, including a straight sets win here in Cincinnati and a shorter workload overall.