E. Rybakina vs M. Frech — prediction
Consistent bounce, medium-fast: neutral conditions, no style favored.
Warm: the ball flies a little more and fitness counts.
Humid air: the ball loses some speed.
Light wind: no noticeable effect.
Surface feeds the model (surface specialization is one of its factors). Weather and altitude are context we publish for you — they do NOT move the probability.
›Ranking: #2 vs #41 (better ranked)
›Head-to-head: 2-0 in favor
›Solid on Hard: 73% career on the surface
›Recent form: 8/10 in recent matches
›Match-sharp: 7 matches in the last 2 weeks
The model makes E. Rybakina the favorite with a 84% win probability, against M. Frech's 16% — a conviction read: the model sees the match clearly leaning one way. Converted to odds, that probability is worth about @1.19; the offered odds are around @1.15 (a 87% implied), slightly below the market, so the model is a touch more cautious.
Several factors explain the number: #2 vs #41 (better ranked); 2-0 in favor; 73% career on the surface; 8/10 in recent matches.
Read it with perspective. Our probability is calibrated — when the model says 84%, that outcome happens roughly that percentage of the time, with ~64% out-of-sample accuracy — but being the favorite is not being the winner: roughly 16 out of every 100 times Frech wins. The model also tends to agree with the market, so the odds already capture almost all the edge: don't take it as a sure value. This is informational analysis, not a betting recommendation. 18+ · play responsibly.