MODEL PREDICTION · 2026-07-23

S. Bejlek vs M. Timofeevaprediction

Livesport Prague Open
✓ Correct
BEJLEKWIN PROBABILITYTIMOFEEVA
61%
model prob.
@1.65
odds · 61% impl.
🎾Serve 54%📈Form 5/10
THE MODEL'S REASONING

Ranking: #42 vs #79 (better ranked)

Recent form: 4/10 in recent matches

Match-sharp: 3 matches in the last 2 weeks

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.
@1.63
fair odds
+1.2%
expected value
HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Bejlek●●●
Elo 1662 vs 1538 and ranking #42 vs #79 drive the model's 61% baseline for Bejlek, the single biggest input.
Serve/return▸ Timofeeva●●
Timofeeva's 57% serve and 49% return points won both top Bejlek's 54%/45%, suggesting sharper ball-striking on both ends.
Form▸ Timofeeva●●
Timofeeva is 6-4 over her last 10 with a +74 ranking trend, while Bejlek is 4-6 and slipping 7 spots.
Rest▸ Timofeeva
Both rested 2 days, but Bejlek logged 5 matches in 14 days versus Timofeeva's 2, raising her fatigue load.
Market value= Even
Odds of 1.65 imply 61%, exactly matching the model's 61%; EV is just 1.2%, essentially fair pricing.
LEVEL GAP

The clearest edge for Bejlek comes from the level metrics: an Elo advantage of 1662 to 1538 and a ranking gap of #42 versus #79 push the model's baseline probability to 61%. This is a real, measurable quality difference built on sustained results over time, not a single recent trend.

Still, a 124-point Elo gap and a 37-spot ranking difference are moderate, not overwhelming. They explain why Bejlek is favored, but they don't imply dominance — the market prices her at the same 61%, meaning this level gap is already fully absorbed into the odds.

SERVE AND RETURN SPLIT

On the surface-neutral serve/return numbers, Timofeeva actually looks sharper: she wins 57% of her service points and 49% of return points, both ahead of Bejlek's 54% and 45%. That's a meaningful efficiency edge in the actual point-by-point mechanics of the match, independent of ranking pedigree.

This creates a tension: Bejlek is favored by the broader level model, but Timofeeva's shot-for-shot numbers this season are better on both serve and return. In practice, this suggests closer points than the 61-39 split implies, especially if Timofeeva can hold at her own higher rate.

MOMENTUM AND SCHEDULE

Recent form tilts toward Timofeeva: she is 6-4 in her last 10 matches with a striking +74 ranking-trend improvement, while Bejlek is just 4-6 over the same span and has dropped 7 places. This kind of momentum divergence often narrows gaps that look larger on paper.

Workload adds another small factor in Timofeeva's favor. Both players had 2 days of rest, but Bejlek played 5 matches in the last 14 days compared to Timofeeva's 2 — more matches in a short window can mean more accumulated physical load, even without an obvious injury signal.

VALUE READ

The model's 61% probability for Bejlek matches the market's implied 61% almost exactly, and the expected value comes out to just 1.2%. That is not a meaningful edge — it's essentially the market's own assessment of the match, reflected back.

Bejlek is the more probable winner on level metrics, but Timofeeva's better serve/return numbers and superior recent form are legitimate counterweights. This is a fair-priced favorite situation, not a value bet: back her only with the understanding that the odds already reflect the balance of these factors.

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.

Analyze today's matches →