HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Rublev●●●
Rublev's #16 ranking and 2010 Elo dwarf van Assche's #86/1909, supporting Rublev's 60% baseline win rate.
Serve/return▸ Rublev●●
Rublev's 70% serve rate tops the data, but van Assche's 46% return could offset it in longer rallies.
Form▸ Rublev●●
Rublev's 5-match streak and wins over Darderi (1963) and Tabilo (1905) outweigh van Assche's less-tested 8/10 run.
Head-to-head▸ Rublev●
Rublev won the only prior meeting in 2024 at ATP level, a small psychological edge.
Rest▸ Assche●
Both had one day off, but Rublev's 5 matches in 14 days vs van Assche's 4 adds marginal fatigue risk.
CLASS GAP
Rublev's ranking (16) and Elo (2010) sit well above van Assche's (86, 1909), and the model's 60% baseline win rate for Rublev reflects that gap before any situational adjustments are applied.
The overall model probability of 75% builds on this foundation, treating Rublev as a clear, though not overwhelming, favorite going into the match.
SERVE BATTLE
Rublev's 70% serve-points-won rate is the largest single number in the data set, well above van Assche's 61%, suggesting Rublev's serve is the more reliable weapon on paper.
Van Assche's 46% return rate is notably stronger than Rublev's own 34%, meaning van Assche is better equipped to attack Rublev's service games than Rublev is to attack his. Expect a match where breaks are scarce, with Rublev's edge coming from raw serve firepower rather than return quality.
FORM AND HISTORY
Rublev arrives on a 5-match winning streak with notable wins over Darderi (Elo 1963) and Tabilo (Elo 1905), both stronger results than van Assche's best win over Carreno-Busta (Elo 1928).
Van Assche's 8-win-in-10 stretch is marginally better by raw count, but his shorter 2-match streak and lighter quality wins suggest less momentum against a top-20 opponent. The single prior meeting, won by Rublev in 2024, adds a small additional edge.
SCHEDULE LOAD
Both players are working with just one day of rest, so recovery time is essentially even.
Rublev has played one more match in the last two weeks (5 vs 4), a marginal difference that could matter only if the contest runs long, but it is not large enough to be a deciding factor on its own.
VALUE CHECK
The model prices Rublev at 75%, clearly below the market's implied 84% (odds of 1.19), producing a projected expected value of -11%. That gap means the market is more confident in Rublev than the model's own factor-based read.
Being the statistical favorite is not the same as being a value bet: at these odds, the data does not support a wagering edge on Rublev, even though he remains the more likely winner of the match.
Impact and analysis from real match data (Elo, form, head-to-head, rest, surface vs baseline, weather, altitude). The model ≈ the market on average; the odds already capture almost all the edge. 18+ · gamble responsibly.