Consistent bounce, medium-fast: neutral conditions, no style favored.
Warm: the ball flies a little more and fitness counts.
Humid air: the ball loses some speed.
Light wind: no noticeable effect.
Moderate altitude: the ball flies a little more than at sea level.
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: #32 vs #78 (better ranked)
›Model 62% vs market 68% → the model sees it as less likely than the odds
›Recent form: 5/10 in recent matches
›More rested: 6d vs opponent's 1d
The model makes A. Tabilo the favorite with a 62% win probability, against A. Mannarino's 38% — a solid favorite, though Mannarino keeps real chances. Converted to odds, that probability is worth about @1.60; the offered odds are around @1.47 (a 68% implied), slightly below the market, so the model is a touch more cautious.
Several factors explain the number: #32 vs #78 (better ranked); model 62% vs market 68% → the model sees it as less likely than the odds; 5/10 in recent matches; 6d vs opponent's 1d.
Read it with perspective. Our probability is calibrated — when the model says 62%, 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 38 out of every 100 times Mannarino 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. This is informational analysis, not a betting recommendation. 18+ · play responsibly.