Caroline Rohde-Moe vs Madeleine Saari-Bystrom Important H2H Prediction Stats:

Head-to-head: Rohde-Moe 0 - 0 Saari-Bystrom

• Second serve performance recent form: In recent form (last 6 months), Rohde-Moe has won 0% of points on their second serve, while Saari-Bystrom has won 0%. There is a high correlation between this stat and match prediction accuracy.
• Return game stats recent form: Return stats show Rohde-Moe, in recent form, has won 0% of their opponent's second serve points, while Saari-Bystrom has won 0%. The same stats for first serve returns are 0% and 0% respectively and this has a high correlation to pick who is favored in this H2H matchup.
• Under pressure analysis: Rohde-Moe has saved 0% of breakpoints in recent form, whereas Saari-Bystrom has saved 0% which is a useful statistic for in-game betting predictions.
• Performance overview: Over the last year Rohde-Moe has won 0% of matches played (W/L 0/ 0), with Saari-Bystrom winning 0% (W/L 0/ 0) that gives us an overall head-to head prediction overview.
• Best surface: Rohde-Moe has their best career surface win % on Hard, winning 48% (W/L 24/ 26), and worse career win % on I.hard, winning 27% (W/L 3/ 8). Saari-Bystrom has their best career surface win % on Clay, winning 33% (W/L 7/ 14), and worse career win % on Hard, winning 25% (W/L 1/ 3).
• Opponent quality stats: Over the last 12 months, Rohde-Moe has played against opponents with an average rank of while Saari-Bystrom has played against players with an average rank of .
• Deciding set performance vs all players: If you are interested in live predictions and betting, if this match goes into a deciding set, Rohde-Moe has won 0% of deciding sets over the last 12 months, while Saari-Bystrom has won 0% in all matches played on tour.
• Break point conversion: In recent form, Rohde-Moe has converted 0% of breakpoint opportunities, and Saari-Bystrom has converted 0% of their chances to break their opponents serve. A telling stat for in-game live betting tips when either player has a breakpoint opportunity.
• If you are interested in models that predict tennis matches, this article is a good start (Warning: Stats geeks only)