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MODEL PREDICTION · 2026-07-12

A. Ito vs Y. Mansouri — prediction

Athens (Greece) - Qualification
✓ Correct
ITOWIN PROBABILITYMANSOURI
73%
model prob.
@1.32
odds · 76% impl.
Rest 13d vs 72d🎾Serve 49%📈Form 3/10 · 5✗
THE MODEL'S REASONING

Ranking: #94 vs #380 (better ranked)

Recent form: 4/10 in recent matches

More rested: 334d vs opponent's 306d

WATCH FOR

!Returning from a long layoff (334d) — possible rustiness

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.
@1.37
fair odds
−3.8%
expected value
HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Ito●●●
Ito sits at #94 versus Mansouri's #380, a 286-spot gap reflecting a much deeper tour resume.
Level (Elo/ranking)▸ Ito●●
Elo gap of 61 points (1546 vs 1485) confirms the ranking edge, though margin is modest, not overwhelming.
Form▸ Mansouri●●●
Ito is on a 5-match losing streak, 4-6 over her last 10; Mansouri's slump is milder at 3-5, streak of just 1.
Rest▸ Ito●●
Ito played 13 days ago and has 1 match in the last 14 days; Mansouri hasn't competed in 72 days, risking rust.
Serve/return▸ Ito
Ito's own return rate of 43% is strong for tour average, though no comparable opponent serve/return data exists to confirm the edge.
Betting value= Even●●●
Model gives Ito 73% versus the market's 76% implied probability at 1.32 odds, producing a -3.8% expected value.
CLASS GAP

The core case for Ito is straightforward: a #94 ranking against a #380 opponent is a wide gulf in tour-level competition, and the Elo figures (1546 vs 1485) back this up with a 61-point edge. This kind of ranking separation typically translates into a clear favorite on paper, since players ranked outside the top 350 face limited exposure to the pace and consistency found at Ito's level.

That said, the Elo gap itself is only moderate in absolute terms — not the type of blowout differential that would suggest an easy night. The ranking disparity is doing most of the heavy lifting here, more than the Elo numbers alone would indicate.

FORM WARNING

Ito's recent form is a legitimate concern that cuts against her ranking advantage. She has lost 5 straight matches and is just 4-6 over her last 10, a run of results that raises questions about her current game state heading into this qualifier.

Mansouri, by contrast, is in a milder funk — 3 wins in her last 8 with only a 1-match losing streak, meaning her recent trajectory is actually less negative than the higher-ranked favorite's. This form split is the main factor working against Ito's position as the clear pick.

RUST FACTOR

The rest data favors Ito on activity grounds: she played as recently as 13 days ago and logged a match within the last 14 days, indicating match sharpness. Mansouri, meanwhile, has been out for 72 days with zero matches in the past two weeks — a layoff long enough to introduce timing and rhythm issues against an active opponent.

This rust risk for Mansouri is a real, data-supported factor, separate from the ranking gap, and adds a second reason to lean toward Ito beyond raw class.

SERVE SIGNS

The only serve/return numbers available belong to Ito: 49% points won on serve and 43% on return. The return figure is notably high by tour standards, suggesting she can generate pressure on return games. However, without any comparable serve or return data for Mansouri, this can only be read as a mild positive signal for Ito rather than a confirmed tactical advantage.

VALUE READ

The model rates Ito's win probability at 73%, slightly below the market's implied 76% at odds of 1.32. That gap produces a -3.8% expected value, meaning the market is pricing Ito marginally shorter than the model's own calibrated estimate.

Being the favorite here does not equal value: the ranking gap, activity edge, and return numbers support Ito's status as the more likely winner, but her 5-match losing streak tempers confidence, and the negative EV means this line offers no discernible edge over the market at current odds.

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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