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.
›Tour Elo: 1890 vs 1614 — favorite by rating
›ATP qualifying / early round · 449 matches in the favorite's track record
›Elo estimate (not the ATP factor model): qualifying draws have no clean main-tour history
!Qualifying/soft context: Elo estimate only — read the round context (already-through, lucky loser, dead rubber) from the dossier; it is not a proven edge.
The model makes T. Daniel the favorite with a 83% win probability, against A. Johnson's 17% — a conviction read: the model sees the match clearly leaning one way. Converted to odds, that probability is worth about @1.20; the offered odds are around @1.07 (a 93% implied), slightly below the market, so the model is a touch more cautious.
Several factors explain the number: 1890 vs 1614 — favorite by rating; atp qualifying / early round · 449 matches in the favorite's track record; qualifying draws have no clean main-tour history.
Read it with caution. This number does NOT come from the ATP factor model, but from the tour's real Elo: it ranks who is the favorite well, but it is a coarser estimate. Being the favorite is not being the winner: roughly 17 out of every 100 times Johnson wins. And above all, in Challenger/ITF the value edge is not proven live, so treat it as a reference, not an opportunity. Watch out for: Qualifying/soft context: Elo estimate only — read the round context (already-through, lucky loser, dead rubber) from the dossier; it is not a proven edge.. This is informational analysis, not a betting recommendation. 18+ · play responsibly.