Consistent bounce, medium-fast: neutral conditions, no style favored.
Mild: neutral conditions.
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: #3 vs #72 (better ranked)
›Recent form: 7/10 in recent matches
›Solid on Hard: 78% career on the surface
›More rested: 141d vs opponent's 13d
!Returning from a long layoff (141d) — possible rustiness
The model makes Carlos Alcaraz the favorite with a 91% win probability, against Jaime Faria's 9% — a conviction read: the model sees the match clearly leaning one way. Converted to odds, that probability is worth about @1.10; the offered odds are around @1.11 (a 90% implied), virtually the same as what the market prices in.
Several factors explain the number: #3 vs #72 (better ranked); 7/10 in recent matches; 78% career on the surface; 141d vs opponent's 13d.
Read it with perspective. Our probability is calibrated — when the model says 91%, 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 9 out of every 100 times Faria 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 (141d) — possible rustiness. This is informational analysis, not a betting recommendation. 18+ · play responsibly.