Consistent bounce, medium-fast: neutral conditions, no style favored.
Strong heat: warm air speeds the ball up and physical wear tells in long matches.
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: #118 vs #161 (better ranked)
›Recent form: 4/10 in recent matches
›Hard specialist: performs +7% above baseline (44% career on the surface)
›More rested: 204d vs opponent's 96d
›Model 60% vs market 78% → the model sees it as less likely than the odds
!Returning from a long layoff (204d) — possible rustiness
The model makes Y. Bu the favorite with a 60% win probability, against F. Maestrelli's 40% — a solid favorite, though Maestrelli keeps real chances. Converted to odds, that probability is worth about @1.67; 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: #118 vs #161 (better ranked); 4/10 in recent matches; performs +7% above baseline (44% career on the surface); 204d vs opponent's 96d.
Read it with perspective. Our probability is calibrated — when the model says 60%, 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 40 out of every 100 times Maestrelli 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 (204d) — possible rustiness. This is informational analysis, not a betting recommendation. 18+ · play responsibly.