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.
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: #171 vs #227 (better ranked)
›Recent form: 2/10 in recent matches
›Model 57% vs market 44% → the model sees it as MORE likely than the odds
!Coming off 4 losses in a row
!Returning from a long layoff (35d) — possible rustiness
The model makes L. Neumayer the favorite with a 57% win probability, against O. Crawford's 43% — a tight match, without a wide margin. Converted to odds, that probability is worth about @1.77; the offered odds are around @2.25 (a 44% implied), slightly above the market, so the model is a touch more optimistic.
Several factors explain the number: #171 vs #227 (better ranked); 2/10 in recent matches; model 57% vs market 44% → the model sees it as more likely than the odds.
Read it with perspective. Our probability is calibrated — when the model says 57%, 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 43 out of every 100 times Crawford 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; Returning from a long layoff (35d) — possible rustiness. This is informational analysis, not a betting recommendation. 18+ · play responsibly.