F. Auger-Aliassime vs R. Hijikata — prediction
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.
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: #4 vs #85 (better ranked)
›Solid on Hard: 64% career on the surface
›Model 84% vs market 90% → the model sees it as less likely than the odds
›Recent form: 7/10 in recent matches
›Match-sharp: 4 matches in the last 2 weeks
›More rested: 10d vs opponent's 4d
The model makes F. Auger-Aliassime the favorite with a 84% win probability, against R. Hijikata's 16% — a conviction read: the model sees the match clearly leaning one way. Converted to odds, that probability is worth about @1.18; the offered odds are around @1.11 (a 90% implied), slightly below the market, so the model is a touch more cautious.
Several factors explain the number: #4 vs #85 (better ranked); 64% career on the surface; model 84% vs market 90% → the model sees it as less likely than the odds; 7/10 in recent matches.
Read it with perspective. Our probability is calibrated — when the model says 84%, 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 16 out of every 100 times Hijikata 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.