HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Zakharova●●●
Zakharova ranks #85 (Elo 1619) vs #180 (Elo 1498); baseline model still only gives her 57% vs market's 63%.
Serve/return▸ Fruhvirtova●
Identical 56% serve rate, but Fruhvirtova returns slightly better (41% vs 40%), a marginal edge in exchanges.
Form▸ Zakharova●●
Zakharova's last 10 (LWWWLLWWWL) shows more wins than Fruhvirtova's (LWWWLLLWLL), despite both on current losing streaks.
Rest▸ Zakharova●
9 days since her last match vs Fruhvirtova's 6, giving Zakharova marginally more recovery time before this qualifier.
Head-to-head▸ Zakharova●
Only prior meeting (2026) went to Zakharova, a small but real precedent in her favor.
RANKING VS MODEL GAP
Zakharova's #85 ranking and 1619 Elo clearly outclass Fruhvirtova's #180 and 1498 Elo, a gap of over 100 rating points that normally signals a comfortable favorite. Yet the calibrated model only credits her with 57% win probability, well below what the ranking gap alone might suggest — a sign the model is weighing other factors (form, rest, style balance) as partial offsets.
This tempered read matters: the market prices her at 63%, six points higher than the model's own estimate. That gap is the crux of this preview — the ranking edge is real, but not as decisive as the raw numbers imply.
SERVE-RETURN BALANCE
Both players serve at an identical 56% rate, meaning neither has a clear advantage on their own delivery — this will likely be a rally-driven match rather than one decided by serve dominance. On return, Fruhvirtova (41%) edges out Zakharova (40%) by a single point, a marginal but real advantage in break-point creation.
With serve strength neutralized, this tiny return edge for the lower-ranked Fruhvirtova is one reason the model hesitates to inflate Zakharova's win probability much beyond 57%.
FORM AND RECOVERY
Zakharova's last 10 results (6 wins) outperform Fruhvirtova's (4 wins), even though both are currently on losing streaks (-1 and -2 respectively). This suggests Zakharova has been the more consistent competitor over the recent stretch, even if her immediate momentum has cooled.
On rest, Zakharova has had 9 days since her last match versus Fruhvirtova's 6, a modest scheduling advantage. The data also flags a risk of rustiness from a longer layoff, so this rest edge should not be read as a guaranteed freshness boost.
VALUE READ
The model sets Zakharova's win probability at 57%, while the market prices her at 63% (odds of 1.58). That gap translates to an expected value of -10.4%, meaning the market is already pricing in more certainty than the data supports.
Being the favorite here does not equate to being a value bet. The ranking and Elo edge are real, but with serve numbers even, form modestly in her favor, and no surface or altitude data to lean on, this looks like a case where the market has priced Zakharova richer than the model's own read of the match — a bet to approach with caution rather than confidence.
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.