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.
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: #120 vs #166 (better ranked)
›Recent form: 3/10 in recent matches
›Model 64% vs market 78% → the model sees it as less likely than the odds
!Coming off 5 losses in a row
!Returning from a long layoff (35d) — possible rustiness
The model makes V. Gaubas the favorite with a 64% win probability, against M. Cecchinato's 36% — a solid favorite, though Cecchinato keeps real chances. Converted to odds, that probability is worth about @1.57; the offered odds are around @1.28 (a 78% implied), slightly below the market, so the model is a touch more cautious.
Several factors explain the number: #120 vs #166 (better ranked); 3/10 in recent matches; model 64% vs market 78% → the model sees it as less likely than the odds.
Read it with perspective. Our probability is calibrated — when the model says 64%, 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 36 out of every 100 times Cecchinato 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: Coming off 5 losses in a row; Returning from a long layoff (35d) — possible rustiness. This is informational analysis, not a betting recommendation. 18+ · play responsibly.