Consistent bounce, medium-fast: neutral conditions, no style favored.
Warm: the ball flies a little more and fitness counts.
Dry air: the ball travels normally.
Some wind: makes baseline control harder.
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: #182 vs #240 (better ranked)
›Model 56% vs market 42% → the model sees it as MORE likely than the odds
!Returning from a long layoff (308d) — possible rustiness
The model makes R. Bertola the favorite with a 56% win probability, against A. Moro Canas's 44% — a tight match, without a wide margin. Converted to odds, that probability is worth about @1.80; the offered odds are around @2.37 (a 42% implied), slightly above the market, so the model is a touch more optimistic.
Several factors explain the number: #182 vs #240 (better ranked); model 56% vs market 42% → the model sees it as more likely than the odds.
Read it with perspective. Our probability is calibrated — when the model says 56%, 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 44 out of every 100 times Canas 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. Watch out for: Returning from a long layoff (308d) — possible rustiness. This is informational analysis, not a betting recommendation. 18+ · play responsibly.