Katarzyna Kawa vs Valentina Mediorreal Arias Head-to-Head Stats, Results & Performance Comparison

Analyzing second serve performance over the past six months, Kawa has won 38.56% of points on their second serve, while Arias has won 29.27%. This statistic is highly relevant for predicting match outcomes. Additionally, Kawa has demonstrated superior ability in saving breakpoints, with a recent success rate of 46.55%, compared to Arias's 22.73%. This is a critical factor for in-game betting predictions.

When it comes to return game stats, Kawa has won 53.34% of their opponent's second serve points, whereas Arias has captured 47.92%. For first serve returns, Arias has been more effective, winning 48.42% of the points compared to Kawa's 37.14%. Such figures play a significant role in identifying who might be favored in a head-to-head matchup.

The performance overview from the last year shows Kawa winning 49.02% of their matches, reflecting a record of 25 wins to 26 losses. Meanwhile, Arias holds a slightly better record, winning 52.94% of their matches, marked by 9 wins and 8 losses. In terms of player level, Kawa has competed mostly in Challengers/ITF tournaments over $10K, winning 50% of these matches. In contrast, Arias has won 56.25% of matches in similar tournaments.

When assessing opponent quality, Kawa has faced competitors with an average rank of 258 over the past year, whereas Arias’s opponents averaged a rank of 498.41. Meanwhile, in deciding sets, Kawa has won 48% over the last 12 months, while Arias has a higher win rate of 75% in these crucial moments. It’s also noteworthy that Kawa has their best career surface win percentage on grass, at 62%, while Arias's best surface is clay, with a 45% win rate in both their best and worst performances.

Finally, regarding breakpoint opportunities, Kawa has recently converted 44.84% of them, while Arias has been more successful, with a conversion rate of 60%. Considering these statistics, it appears that Arias possesses a slight advantage in this upcoming match, based on their superior breakpoint conversion and performance in deciding sets.