E. Kalieva vs E. Perez — prediction
Consistent bounce, medium-fast: neutral conditions, no style favored.
Mild: neutral conditions.
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: #117 vs #456 (better ranked)
›Hard specialist: performs +10% above baseline (36% career on the surface)
›Model 65% vs market 99% → the model sees it as less likely than the odds
›Recent form: 5/10 in recent matches
›On a streak: 2 wins in a row
The model makes E. Kalieva the favorite with a 65% win probability, against E. Perez's 35% — a solid favorite, though Perez keeps real chances. Converted to odds, that probability is worth about @1.55; the offered odds are around @1.01 (a 99% implied), slightly below the market, so the model is a touch more cautious.
Several factors explain the number: #117 vs #456 (better ranked); performs +10% above baseline (36% career on the surface); model 65% vs market 99% → the model sees it as less likely than the odds; 5/10 in recent matches.
Read it with perspective. Our probability is calibrated — when the model says 65%, 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 35 out of every 100 times Perez 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.