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ITF · ELO ESTIMATE · 2026-07-10

S. Pankin vs S. Cocola — prediction

M15 Kursumlijska Banja 8
✗ Missed
PANKINWIN PROBABILITYCOCOLA
83%
Elo prob.
@1.20
odds · 83% impl.
Rest 1d vs 3d📈Form 7/10
WHAT THE ESTIMATE IS BASED ON

Tour Elo: 1731 vs 1455 — favorite by rating

ITF tier · 122 matches in the favorite's track record

Elo estimate (not the ATP factor model): these are softer, less-analyzed markets

WATCH FOR

!Soft market: the value edge in Challenger/ITF is NOT proven live — treat it as an estimate, not an opportunity.

Tour Elo estimate (Challenger/ITF markets, not covered by the factor model). The value edge here is unproven live — it's a reference, not a recommendation. 18+ · gamble responsibly.
@1.20
fair odds
−0.3%
expected value
HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Pankin●●●
276-point Elo gap (1731 vs 1455) underlies Pankin's 83% win probability, though ITF ratings are less reliable.
Form▸ Pankin●●
Pankin arrives in better form: 7 wins in his last 10 versus Cocola's 3, reflecting sharper recent results.
Rest▸ Cocola●●
Pankin played 5 matches in 14 days on just 1 day rest; Cocola rested 3 days, fresher entering this match.
Value/Market= Even
Odds of 1.20 imply 83% probability, matching the model exactly; the -0.3% edge signals no real value.
ELO GAP

The 276-point Elo gap (1731 vs 1455) is the single largest input here, translating directly into the model's 83% win probability for Pankin. That said, this is a Challenger/ITF Elo estimate rather than the more rigorous ATP-level factor model — the underlying track record (122 matches for the favorite) gives it some substance, but Elo alone in these thinner, less-analyzed markets should be read as a rating gap, not a guaranteed outcome.

In practical terms, a gap this size usually reflects a real quality difference in points won on serve and return, but without surface, serve, or return splits available for this match, the rating itself is doing all the work in the projection.

FORM MOMENTUM

Recent form reinforces the rating gap rather than contradicting it. Pankin's last 10 (WWLWLWWWLW) shows 7 wins against 3 losses, a pattern of a player winning more than he's losing heading into this match. Cocola's last 10 (LLLWLLWLLW) is essentially the inverse — 3 wins and 7 losses — indicating he's been struggling to string together results.

Neither player is on an extended hot or cold streak right now (both show a streak value of 1), so this isn't about momentum swings, but the baseline level of recent play clearly sits with Pankin.

REST AND WORKLOAD

Workload cuts the other way. Pankin has played 5 matches in the last 14 days and enters with just 1 day of rest, a compressed schedule that can accumulate physical fatigue over the course of a match. Cocola, by contrast, has played only 1 match in the same span and had 3 days to recover — he arrives fresher physically, even though his results have been weaker.

This is a real, quantifiable factor working against the favorite, though it's a schedule/fatigue consideration rather than a form or class indicator — it doesn't offset the Elo and form gaps, but it does add a note of caution for Pankin holding up over a full match.

VALUE READ

The odds of 1.20 imply an 83% win probability for Pankin, and the model's own estimate is also 83% — they match almost exactly, producing an expected value of -0.3%. In other words, this is priced efficiently: Pankin is very likely favored to win, but there is no market inefficiency to exploit at this price.

Given the soft nature of Challenger/ITF markets, any perceived edge here is unproven and should be treated as descriptive information about the matchup, not as a betting opportunity. Being the favorite is not the same as offering value, and on the numbers provided, this is a fair-priced favorite rather than a mispriced one.

Impact and analysis from real match data (Elo, form, head-to-head, rest, surface vs baseline, weather, altitude). Soft-market estimate: the value is unproven live. 18+ · gamble responsibly.

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