Consistent bounce, medium-fast: neutral conditions, no style favored.
Warm: the ball flies a little more and fitness counts.
Very humid air: the ball gets heavy and points stretch out.
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: #62 vs #123 (better ranked)
›Model 58% vs market 76% → the model sees it as less likely than the odds
›Recent form: 3/10 in recent matches
›More rested: 26d vs opponent's 13d
!Returning from a long layoff (26d) — possible rustiness
The model makes C. Moutet the favorite with a 58% win probability, against D. Sweeny's 42% — a tight match, without a wide margin. Converted to odds, that probability is worth about @1.73; the offered odds are around @1.32 (a 76% implied), slightly below the market, so the model is a touch more cautious.
Several factors explain the number: #62 vs #123 (better ranked); model 58% vs market 76% → the model sees it as less likely than the odds; 3/10 in recent matches; 26d vs opponent's 13d.
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 Sweeny 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 (26d) — possible rustiness. This is informational analysis, not a betting recommendation. 18+ · play responsibly.