E. Rybakina vs C. Gauff — prediction
Consistent bounce, medium-fast: neutral conditions, no style favored.
Warm: the ball flies a little more and fitness counts.
Very dry air: the ball travels faster.
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 #4 (better ranked)
›Head-to-head: 1-1 even
›Solid on Hard: 73% career on the surface
›Recent form: 10/10 in recent matches
›On a streak: 18 wins in a row
›Match-sharp: 10 matches in the last 2 weeks
The model makes E. Rybakina the favorite with a 52% win probability, against C. Gauff's 48% — a tight match, without a wide margin. Converted to odds, that probability is worth about @1.94; the offered odds are around @1.92 (a 52% implied), virtually the same as what the market prices in.
Several factors explain the number: #2 vs #4 (better ranked); 1-1 even; 73% career on the surface; 10/10 in recent matches.
Read it with perspective. Our probability is calibrated — when the model says 52%, 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 48 out of every 100 times Gauff 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.