Coco Gauff vs Jessica Pegula Prediction – WTA Finals Picks 11-04-2023

Coco Gauff and Jessica Pegula will put friendship to one side and battle for a spot in the championship match of the 2023 WTA Finals. The match will be played on Saturday, November 4, 2023.

Gauff vs Pegula Preview

Coco Gauff was precariously close to group-stage elimination but staged a come-from-behind victory against Marketa Vondrousova to reach the semifinal. Momentum ebbed and flowed in that match due to intermittent rain. But she adjusted to the conditions and stole the second set in a tiebreak. She secured a couple of breaks in the decider to send the Czech packing. The young American finished the match with 31 winners, but her unforced error count was concerning (38) as was the ease with which Vondrousova broke her seven (seven times from 13).

By contrast, Jessica Pegula has progressed into her first semifinal without the loss a match or a set. Pegula topped a group containing World No. 1 Aryna Sabalenka, former Wimbledon champion Elena Rybakina and Greek star Maria Sakkari. Her final round-robin match was the most assured performance of her stay in Cancun so far, beating Sakkari 6-3, 6-2 (her 101st win across singles and doubles this year). 

Gauff vs Pegula Prediction

Jessica Pegula leads the head-to-head over Coco Gauff 2-1. Pegula was the only player to defeat her compatriot during the US swing, doing so in the quarterfinals of Montreal, and went on to win the title. Gauff has faced the most break points (26 to 16) between them at the WTA Finals. Her difficulties on serve were evident in her match against Vondrousova. Jessica Pegula has been returning very well at this tournament and the stats sheet proves this, having won at least 50% of second-serve points on her return. Gauff is not going to find comfort trying to outduel the consistent and disciplined World No. 5. Pegula has the momentum (unbeaten in eight matches) and has not lost in Mexico having won Guadalara last year. The older of the two Americans is certainly the most attractive pick in the ML.