MODEL PREDICTION · 2026-07-20

N. Podoroska vs J. Stusekprediction

Hamburg
✗ Missed
PODOROSKAWIN PROBABILITYSTUSEK
73%
model prob.
@1.26
odds · 79% impl.
🌡19° · 56% humRest 7d vs 5d📈Form 3/10 · 5✗
THE MODEL'S REASONING

Ranking: #533 vs #913 (better ranked)

Recent form: 4/10 in recent matches

Model 73% vs market 79% → the model sees it as less likely than the odds

WATCH FOR

!Coming off 5 losses in a row

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
−8.2%
expected value
HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Podoroska●●
Podoroska is ranked #533 vs #913, but Elo is nearly even (1473 vs 1463); her ranking trend of -437 tempers the gap.
Form▸ Podoroska●●
Podoroska went 4/10 with 5 straight losses; Stusek's visible record is 0/4 (LLLL) — both cold, but she has more recent wins.
Rest▸ Podoroska
Podoroska has 7 days of rest vs Stusek's 5, but she also played 2 matches in 14 days vs Stusek's 1 — roughly offsetting.
Weather= Even
Mild, dry conditions (20°C, 44% humidity, 14 km/h wind) with no serve/return data available to link them to either player.
LEVEL AND RANKING

Podoroska sits at world No. 533 against Stusek's No. 913, a gap wide enough to make her the clear favorite on paper. Yet the Elo ratings tell a closer story: 1473 versus 1463, only 10 points apart, suggesting the ranking distance overstates the actual quality difference between the two.

Her ranking trend also shows a drop of 437 places, meaning she has fallen sharply from a much higher position. This decline is worth noting alongside the ranking gap — it points to instability rather than a player rising in form.

FORM AND MOMENTUM

Podoroska's last 10 matches read WWLLWLLLLL: four wins scattered early, followed by a current 5-match losing streak. Stusek's available sample is just four matches, all losses (LLLL), with a 4-match losing streak of her own and no recent win logged.

Neither player arrives with real momentum, but Podoroska's log at least contains wins in the recent sample, giving her a marginal edge over an opponent whose visible form shows nothing but defeats.

REST AND SCHEDULE

Podoroska has had 7 days since her last match compared to Stusek's 5, a slightly longer recovery window. But she has also played 2 matches in the last 14 days versus Stusek's 1, meaning somewhat more accumulated match load heading in.

These two figures largely cancel out — extra rest days on one side, extra match volume on the other — so scheduling does not clearly tilt the match toward either player.

WEATHER

Conditions are mild and dry: 20°C, 44% humidity, and wind at 14 km/h. Without surface or serve/return data for either player, there is no concrete mechanism to link these conditions to a specific advantage.

Weather is therefore treated as a neutral factor in this match rather than something shaping the outcome.

VALUE READ

The model assigns Podoroska a 73% win probability, close to the market's implied 75% at odds of 1.34. That gap produces an expected value of -2.4%, meaning the model does not find value in backing the favorite at this price.

Being the favorite is not the same as being a good bet here — the market is, if anything, slightly more confident than the model itself. Given the negative EV, this is a case for caution rather than a recommended play.

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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