Nora Cornolle vs Klaudia Sygula

Each row splits one source's view of the fight. The dashed line is even odds. Where the models sit further from the market, they are claiming an edge.

Career UFC averages. Bars are scaled within each row, so compare left against right, not row against row. The stronger side is highlighted, and for strikes absorbed the lower number is the better one.

Each model's split across the ways this fight can finish, out of 100.

No market line was provided, so this leans on Elo (52-48 Sygula) and trajectory. The common-opponent signal actually favors Cornolle - she KO'd Melissa Mullins with a knee, while Sygula was TKO'd by Mullins in her debut - but that Sygula loss is nearly two years old and she has clearly rebuilt since, grinding out decisions over Alekseeva and Cachoeira with enormous volume (7.27 SLPM, +1.77 differential). Cornolle is trending the wrong way: two straight losses, submitted by Joselyne Edwards last time out - an opponent she'd already beaten in 2023 - and she turns 37 before this fight. Cornolle's 2.73 SLPM output is less than half of Sygula's, and while her 55% accuracy is sharp, she historically fades when opponents push pace (Rosa, Cavalcanti both outworked her). Sygula's suspect 40% takedown defense is largely irrelevant because Cornolle attempts only 0.22 takedowns per fight at 11% accuracy. The nine-year age gap, volume edge, and momentum point to Sygula outworking the Frenchwoman round by round, though the Paris crowd and small two-fight UFC sample for Sygula cap conviction. Sygula's durability question (the Mullins KO) is the live risk against Cornolle's counter-knee power.

Sygula's substantially higher striking output and stronger positive strike differential give her the clearer path to winning rounds in a matchup likely to remain primarily on the feet. Cornolle is more accurate and may be dangerous in the clinch, but her low volume and 47% takedown defense could allow Sygula to dictate activity and positioning. Sygula's defensive liabilities and limited UFC sample keep confidence moderate.