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: #126 vs #90
›Recent form: 3/10 in recent matches
›Model 52% vs market 58% → the model sees it as less likely than the odds
!Coming off 3 losses in a row
!Returning from a long layoff (21d) — possible rustiness
The model makes S. Ofner the favorite with a 52% win probability, against M. Trungelliti's 48% — a tight match, without a wide margin. Converted to odds, that probability is worth about @1.93; the offered odds are around @1.72 (a 58% implied), slightly below the market, so the model is a touch more cautious.
Several factors explain the number: #126 vs #90; 3/10 in recent matches; model 52% vs market 58% → the model sees it as less likely than the odds.
Read it with perspective. Our probability is calibrated — when the model says 52%, 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 48 out of every 100 times Trungelliti 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 3 losses in a row; Returning from a long layoff (21d) — possible rustiness. This is informational analysis, not a betting recommendation. 18+ · play responsibly.