M. Frech vs E. Jacquemot — 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: #48 vs #165 (better ranked)
›Head-to-head: 1-0 in favor
›Model 63% vs market 69% → the model sees it as less likely than the odds
›Recent form: 5/10 in recent matches
›More rested: 12d vs opponent's 1d
The model makes M. Frech the favorite with a 63% win probability, against E. Jacquemot's 37% — a solid favorite, though Jacquemot keeps real chances. Converted to odds, that probability is worth about @1.58; the offered odds are around @1.45 (a 69% implied), slightly below the market, so the model is a touch more cautious.
Several factors explain the number: #48 vs #165 (better ranked); 1-0 in favor; model 63% vs market 69% → the model sees it as less likely than the odds; 5/10 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 ~64% out-of-sample accuracy — but being the favorite is not being the winner: roughly 37 out of every 100 times Jacquemot 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.