MODEL PREDICTION · 2026-07-26

I. Shymanovich vs A. Rainaprediction

Memphis (Usa) - Qualification
✓ Correct
SHYMANOVICHWIN PROBABILITYRAINA
66%
model prob.
@1.11
odds · 90% impl.
Rest 17d vs 1d🎾Serve 59%📈Form 6/10
THE MODEL'S REASONING

Ranking: #215 vs #200

Recent form: 4/10 in recent matches

Model 66% vs market 90% → the model sees it as less likely than the odds

WATCH FOR

!Returning from a long layoff (26d) — 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.
@1.51
fair odds
−26.5%
expected value
HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Shymanovich●●●
Shymanovich's Elo edge (1532 vs 1450, +82) is partly offset by a worse ranking, #215 vs #200 for Raina.
Form▸ Shymanovich●●
Shymanovich is 6-4 over her last 10 vs Raina's 2-8, though Shymanovich enters on a 1-match losing streak.
Rest▸ Shymanovich●●●
Raina has just 1 day of rest after 3 matches in 14 days and a semifinal run, raising fatigue risk against a rested Shymanovich (17 days off).
Layoff risk▸ Raina
Shymanovich's 17-day layoff with zero matches in that span brings a rustiness risk noted directly in the data.
Serve/return▸ Shymanovich
Shymanovich's 59% serve-points-won rate is a solid baseline, though no comparable serve/return numbers exist for Raina to size the gap.
Level (model vs market)= Even●●
The model gives Shymanovich 66% while the market implies 91%, a wide gap suggesting the market is pricing more certainty than the model supports.
ELO AND RANKING GAP

Shymanovich carries a clear Elo advantage (1532 vs 1450, +82 points), which typically reflects stronger recent competitive results across matches, not just this event. That gap is the single biggest quantitative tilt toward her in this matchup.

However, the ranking picture cuts the other way: Raina sits at #200 versus Shymanovich's #215, a modest but real edge in the official rankings. The two signals partially offset each other, which is one reason the model's own probability for Shymanovich (66%) is far more conservative than a simple Elo read alone might suggest.

FORM AND MOMENTUM

Over the last 10 matches, Shymanovich is 6-4 while Raina is just 2-8, a meaningful gap in recent competitive success that favors Shymanovich structurally. Win/loss record over 10 matches is a decent proxy for current playing level.

That said, the momentum snapshot is more nuanced: Shymanovich is on a 1-match losing streak, while Raina has just won her last match and sits on a positive streak of 1. Her long-run record is worse, but she is trending upward in the very short term.

REST AND FATIGUE

The rest disparity is stark: Raina has had just 1 day since her last match and has played 3 matches in the last 14 days, including a run to the Memphis Qualification semifinals just a day ago. Compressed schedules and deep tournament runs commonly sap movement and shot quality in the next match, which works against Raina here.

Shymanovich, by contrast, has had 17 days off with zero matches in that window. That is a clear rest advantage, though it comes with its own caveat covered next: extended time away from competition can also mean less match sharpness.

SERVE STRENGTH

The available numbers show Shymanovich winning 59% of service points and 45% of return points, a reasonably solid all-around service profile. No equivalent serve or return numbers exist for Raina in this data set, so a direct comparison isn't possible, but Shymanovich's marks stand on their own as a competent baseline.

Working against that is the flagged risk of her 17-day layoff with no recent match play — a real rustiness risk that could blunt any structural serve advantage early in the match.

VALUE READ

The model puts Shymanovich's win probability at 66%, while the market, via odds of 1.10, implies roughly 91%. That's a large gap, and it produces a substantially negative expected value of -27.2% for backing the favorite at this price.

Being the favorite here does not translate into value: the market is pricing in far more certainty than the model's factor-based read supports. On a pure EV basis, this is not a bet the model would recommend, regardless of which player ultimately wins 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.

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