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MODEL PREDICTION · 2026-07-12

J. Bouzas Maneiro vs Q. Zheng — prediction

Athens (Greece) - Qualification
✗ Missed
MANEIROWIN PROBABILITYZHENG
50%
model prob.
@2.90
odds · 34% impl.
Rest 9d vs 13d🎾Serve 55%📈Form 4/10
THE MODEL'S REASONING

Ranking: #52 vs #138 (better ranked)

Recent form: 4/10 in recent matches

Match-sharp: 3 matches in the last 2 weeks

Model 50% vs market 34% → the model sees it as MORE likely than the odds

Calibrated model probability (~64% out-of-sample accuracy, validated specifically on WTA). Not a guarantee: the model ≈ the market on average, so the odds already capture almost all the edge. 18+ · gamble responsibly.
@2.00
fair odds
+45.0%
expected value
HOW EACH FACTOR MATTERS
Elo Rating▸ Zheng●●●
Zheng's 1783 Elo is 169 points above Bouzas Maneiro's 1614, signaling a stronger underlying level than the ranking suggests.
Ranking▸ Maneiro●●
Bouzas Maneiro sits at #52 versus #138, and Zheng's ranking has fallen 106 spots recently versus a 1-spot dip for the favorite.
Serve/Return▸ Zheng●●●
Zheng holds serve at 67% versus Bouzas Maneiro's 55%, a 12-point edge that outweighs the favorite's 44% vs 32% return advantage.
Baseline Model▸ Zheng●●
Before contextual adjustments, the raw baseline gives Zheng 47% versus 39% for Bouzas Maneiro, reflecting the serve/Elo gap.
Form▸ Maneiro
Both are 4-6 in their last 10, but Zheng is mid a 2-match losing streak versus a shorter 1-match dip for Bouzas Maneiro.
Rest/Schedule= Even
Zheng has 13 days of rest with just 1 match played versus Bouzas Maneiro's 9 days and 3 matches, trading freshness for match rhythm.
LEVEL GAP

The two rating systems disagree sharply here. Zheng's Elo of 1783 versus Bouzas Maneiro's 1614 points to a meaningfully stronger player on current form-adjusted metrics, while the ATP-style ranking (#52 vs #138) tells the opposite story, reinforced by Zheng's steep 106-spot ranking decline against Bouzas Maneiro's near-flat -1 trend.

This divergence usually means the ranking gap is inflated by tournament participation or scheduling rather than head-to-head quality, which is exactly what Elo is built to capture. It is a genuine source of uncertainty in this match rather than a clean edge for either player.

SERVE AND RETURN

Zheng's serve is the single clearest statistical advantage in this match: she wins 67% of service points compared to 55% for Bouzas Maneiro, a 12-point gap that should let her control more service games outright.

Bouzas Maneiro partially offsets this with a return game that outperforms Zheng's, 44% to 32%. In practice this sets up a match where Zheng should hold more comfortably, but Bouzas Maneiro has more chances to disrupt Zheng's own service games than vice versa — a track that tends to produce close, break-heavy sets.

FORM AND FRESHNESS

Both players are middling on recent form (4-6 in their last 10 matches), but Zheng is currently on a 2-match losing streak versus a shallower 1-match dip for Bouzas Maneiro, a small tilt toward the favorite's side.

Rest cuts the other way: Zheng arrives with 13 days off and only 1 match in the last two weeks, while Bouzas Maneiro has played 3 matches in that span on 9 days' rest. That gives Zheng the fresher legs, but Bouzas Maneiro the sharper match rhythm — a wash rather than a clear factor.

VALUE READ

The model lands at an even 50/50 split, a meaningful jump from the 39%/47% baseline that, on its own, favored Zheng. That shift is driven mainly by ranking and match-sharpness factors, not by serve/return or Elo, both of which still point to Zheng as the stronger player.

The market prices Bouzas Maneiro at just 34% (odds of 2.90), well below the model's 50%, producing a stated +45% expected value. That gap is real on paper, but this is a WTA qualification match with no surface, weather, or head-to-head data available, and the model's own accuracy is only ~64% out-of-sample. Treat this as a live coinflip with a pricing discrepancy worth noting, not as a mispriced sure thing — Zheng remains the statistically stronger player on serve and Elo even if the market's price on Bouzas Maneiro looks generous.

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.

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