Consistent bounce, medium-fast: neutral conditions, no style favored.
Strong heat: warm air speeds the ball up and physical wear tells in long matches.
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: #111 vs #157 (better ranked)
›Recent form: 3/10 in recent matches
›Hard specialist: performs +8% above baseline (44% career on the surface)
The model makes D. Svrcina the favorite with a 58% win probability, against M. Lajal's 42% — a tight match, without a wide margin. Converted to odds, that probability is worth about @1.74; the offered odds are around @1.71 (a 58% implied), virtually the same as what the market prices in.
Several factors explain the number: #111 vs #157 (better ranked); 3/10 in recent matches; performs +8% above baseline (44% career on the surface).
Read it with perspective. Our probability is calibrated — when the model says 58%, that outcome happens roughly that percentage of the time, with ~65% out-of-sample accuracy — but being the favorite is not being the winner: roughly 42 out of every 100 times Lajal 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.