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Challenger · ELO ESTIMATE · 2026-07-13

Z. Zhang vs J. Boulais — prediction

Granby
ZHANGWIN PROBABILITYBOULAIS
65%
Elo prob.
@1.36
odds · 74% impl.
Rest 21d vs 4d🎾Serve 71%📈Form 7/10 · 2✗
WHAT THE ESTIMATE IS BASED ON

Tour Elo: 1785 vs 1676 — favorite by rating

Challenger tier · 292 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.
@1.53
fair odds
−11.3%
expected value
HOW EACH FACTOR MATTERS
Level (Elo)▸ Zhang●●●
109-point Elo gap (1785 vs 1676) reflects a real quality edge for Zhang in this Challenger field.
Serve/return▸ Zhang●●
Zhang holds serve at 71% versus Boulais's 66%, a 5-point edge that should let him control more service games.
Form▸ Zhang●●
Zhang is 7-3 over his last 10 with wins over higher-Elo players (1949, 1915); Boulais is 4-6 with no quality wins.
Rest▸ Zhang●●
Zhang is fresh off 21 days of rest with zero matches in two weeks, while Boulais has played 4 matches in 14 days.
Value (model vs market)= Even●●●
Market implies 79% for Zhang versus the model's 65%; at odds of 1.26 that gap produces a -17.8% expected value.
RATING GAP

The core signal here is the 109-point Elo difference between Zhang (1785) and Boulais (1676). In Challenger tennis, a gap of this size typically points to a meaningful skill difference — enough that the model sets Zhang as a clear, though not overwhelming, favorite at 65% win probability.

This is a soft market read (Elo-based, not the full ATP factor model), so treat the edge as directional rather than precise. It tells us Zhang should be the stronger player on paper, not that the outcome is settled.

SERVE CONTROL

Zhang's 71% serve-points-won rate outpaces Boulais's 66%, a real 5-point gap that should translate into fewer break-point chances against him and more free holds. Both players return at an identical 35%, so neither has a return-game advantage to offset this — the edge sits squarely on Zhang's delivery.

Without surface or weather data to modify this, the serve gap stands as one of the cleaner, most concrete signals in this match: Zhang should generally have an easier path through his own service games.

FORM AND SCHEDULE

Zhang's last 10 matches (7-3) include wins over players rated 1949 and 1915 Elo — notably stronger than Boulais's own 1676 — showing he can raise his level against tougher competition. Boulais, by contrast, is 4-6 over his last 10 with no listed quality wins, a form profile that trails Zhang's on quality even though both are on short losing streaks (Zhang -2, Boulais -1).

Rest also splits in Zhang's favor: 21 days off with no matches in the last two weeks versus Boulais's four matches in 14 days. That workload could mean sharper match rhythm for Boulais, but it could equally mean accumulated fatigue — the data doesn't specify which, so this should be read as a mild tilt toward Zhang rather than a decisive factor.

VALUE CHECK

Even with the model favoring Zhang at 65%, the market is considerably more confident, implying 79% at odds of 1.26. That gap produces an expected value of -17.8% for a bet on Zhang — the market has already priced in more certainty than this data-driven estimate supports.

Being the favorite is not the same as being a value bet. Here, the numbers suggest Zhang is likely the better player, but backing him at these odds is not backed by positive expected value under this model. This is also a soft Challenger market, so the edge estimate itself carries extra uncertainty.

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.

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