Consistent bounce, medium-fast: neutral conditions, no style favored.
Warm: the ball flies a little more and fitness counts.
Dry air: the ball travels normally.
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: #168 vs #174 (better ranked)
›Recent form: 3/10 in recent matches
›Hard specialist: performs +6% above baseline (33% career on the surface)
›More rested: 109d vs opponent's 35d
›Model 55% vs market 40% → the model sees it as MORE likely than the odds
!Coming off 3 losses in a row
!Returning from a long layoff (109d) — possible rustiness
The model makes L. Nardi the favorite with a 55% win probability, against F. Cina's 45% — a tight match, without a wide margin. Converted to odds, that probability is worth about @1.83; the offered odds are around @2.49 (a 40% implied), slightly above the market, so the model is a touch more optimistic.
Several factors explain the number: #168 vs #174 (better ranked); 3/10 in recent matches; performs +6% above baseline (33% career on the surface); 109d vs opponent's 35d.
Read it with perspective. Our probability is calibrated — when the model says 55%, 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 45 out of every 100 times Cina 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 (109d) — possible rustiness. This is informational analysis, not a betting recommendation. 18+ · play responsibly.