Challenger · ELO ESTIMATE · 2026-07-24

H. Mayot vs D. Dietrichprediction

Zug
✗ Missed
MAYOTWIN PROBABILITYDIETRICH
55%
Elo prob.
@2.55
odds · 39% impl.
🎾Serve 61%📈Form 5/10 · 2✓
WHAT THE ESTIMATE IS BASED ON

Tour Elo: 1783 vs 1745 — favorite by rating

Challenger tier · 315 matches in the favorite's track record

Elo estimate (not the ATP factor model): these are softer, less-analyzed markets

WATCH FOR

!Soft market: the value edge in Challenger/ITF is NOT proven live — treat it as an estimate, not an opportunity.

Tour Elo estimate (Challenger/ITF markets, not covered by the factor model). The value edge here is unproven live — it's a reference, not a recommendation. 18+ · gamble responsibly.
@1.80
fair odds
+41.4%
expected value
HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Mayot●●●
Mayot leads by 38 Elo points (1783 vs 1745) and by 458 ranking spots (160 vs 618), a clear class gap.
Serve/return▸ Dietrich●●
Dietrich's serve (70%) and return (39%) both outpace Mayot's (61%/37%), suggesting sharper point-winning tools despite the ranking gap.
Form▸ Dietrich●●
Dietrich is 7-3 in his last 10 vs Mayot's 6-4; both are riding two-match win streaks.
Rest▸ Mayot
Both rested one day, but Dietrich played 5 matches in 14 days vs Mayot's 3, adding fatigue.
Value▸ Mayot
Model gives Mayot 55% vs a 39% market-implied price (odds 2.55), but this is a soft Elo market—edge unproven.
LEVEL GAP

Mayot's Elo advantage (1783 vs 1745) and especially his ranking edge (No. 160 vs No. 618) point to a meaningful quality gap between the two players. This 38-point Elo margin and the 458-spot ranking difference form the backbone of the model's 55% probability for Mayot, reflecting sustained level differences accumulated across far more matches at a higher tier of competition.

SERVE/RETURN MISMATCH

The individual serve and return marks tell a different story than the rankings. Dietrich's 70% serve-points-won rate is nine points higher than Mayot's 61%, and his 39% return rate also edges Mayot's 37%. On these raw numbers, Dietrich looks like the more efficient ball-striker on both sides of the ball.

This is a real tension in the data: the ranking and Elo gap says Mayot is the far stronger player, but the shot-quality numbers favor Dietrich. Since no head-to-head or surface data is available, it is impossible to know how much of Dietrich's serve/return edge came against weaker competition typical of a No. 618 ranking, versus reflecting genuine technical strength.

FORM AND WORKLOAD

Recent form slightly favors Dietrich, who is 7-3 in his last 10 matches compared with Mayot's 6-4; both are currently on two-match winning streaks, so neither has a momentum edge from that angle alone.

Workload adds a secondary wrinkle. Both players had just one day of rest before this match, but Dietrich has played 5 matches in the last 14 days against Mayot's 3. That extra volume of recent competition could translate into accumulated physical load over the course of the match, even without a difference in days off.

VALUE READ

The model prices Mayot at 55% to win, versus a 39% implied probability from the 2.55 odds, producing a notional 41.4% expected-value edge. That gap is worth taking seriously but not literally: this projection comes from an Elo-based estimate for a Challenger-level match, a softer and less-analyzed market where pricing inefficiencies are less proven in practice than in ATP-level models.

Being the favorite by rating and ranking is not the same as being undervalued by a reliable margin. Given the countervailing serve/return numbers and Dietrich's slightly better recent form and busier schedule, this reads as a plausible but unconfirmed edge rather than a clear value opportunity.

Impact and analysis from real match data (Elo, form, head-to-head, rest, surface vs baseline, weather, altitude). Soft-market estimate: the value is unproven live. 18+ · gamble responsibly.

Analyze today's matches →