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: #58 vs #110 (better ranked)
›Model 63% vs market 45% → the model sees it as MORE likely than the odds
›Recent form: 4/10 in recent matches
!Coming off 4 losses in a row
The model makes T. Machac the favorite with a 63% win probability, against T. Samuel's 37% — a solid favorite, though Samuel keeps real chances. Converted to odds, that probability is worth about @1.59; the offered odds are around @2.20 (a 45% implied), slightly above the market, so the model is a touch more optimistic.
Several factors explain the number: #58 vs #110 (better ranked); model 63% vs market 45% → the model sees it as more likely than the odds; 4/10 in recent matches.
Read it with perspective. Our probability is calibrated — when the model says 63%, 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 37 out of every 100 times Samuel 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 4 losses in a row. This is informational analysis, not a betting recommendation. 18+ · play responsibly.