Challenger · ELO ESTIMATE · 2026-07-27

T. Skatov vs T. Faurelprediction

San Marino
Result pending
SKATOVWIN PROBABILITYFAUREL
61%
Elo prob.
@1.61
odds · 62% impl.
H2H 0–1 SkatovRest 4d vs 7d🎾Serve 63%📈Form 5/10
WHAT THE ESTIMATE IS BASED ON

Tour Elo: 1755 vs 1676 — favorite by rating

Challenger tier · 339 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.
@1.63
fair odds
−1.4%
expected value
HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Skatov●●●
Skatov's 1755 Elo and No. 163 ranking (+39 trend) top Faurel's 1676 Elo and No. 378, backing the 61% model line.
Head-to-head▸ Faurel
Faurel won the only prior meeting (2025), a small but real data point against Skatov.
Form▸ Skatov
Skatov's 5-5 last10 beats Faurel's 3-7, though both carry losing streaks (-1 vs -2).
Rest▸ Faurel●●
Faurel has 7 days' rest and only 2 matches in 14 days vs Skatov's 4 days and 5 matches, less fatigue risk.
Serve/return▸ Faurel●●
Faurel's 41% return outpaces Skatov's 35%, offsetting Skatov's modest serve edge (63% vs 60%) and creating more break chances.
Value/EV= Even●●●
Model (61%) sits close to market (62%); EV is -1.4%, so no edge — this is a soft Challenger price, not a value bet.
LEVEL GAP

Skatov's Elo advantage (1755 vs 1676) and his much higher ranking (163 vs 378), reinforced by a +39 ranking trend, make him the structurally stronger player on paper. This gap is the single largest input behind the 61% model probability, reflecting a genuine quality difference built over a large sample (339 tracked matches for the favorite).

Still, Challenger-level Elo is a softer signal than tour-level data — useful for ordering the two players but not precise enough to treat the 61% as a hard ceiling on Faurel's chances.

H2H AND RECENT FORM

The two have met once, and Faurel won — a small sample, but it shows he has already solved Skatov's game in at least one match this year. Combined with Faurel's -2 streak (three wins in his last ten) against Skatov's -1 streak (five wins in his last ten), the form picture is mixed rather than a clear tailwind for the favorite.

Neither player is playing sharp tennis right now, which tempers how much weight the Elo/ranking gap should carry on the day.

REST AND SERVE BALANCE

Faurel arrives fresher: 7 days since his last match and only 2 in the last two weeks, versus Skatov's 4 days off and 5 matches in the same window. That workload difference could matter late in a tight match, favoring Faurel's legs over three or five sets.

On serve/return numbers, Skatov holds a slight edge in service points won (63% vs 60%), but Faurel's return game is notably better (41% vs 35%). That means Faurel is more likely to generate break points even while facing a marginally bigger server, a mechanism that narrows the practical gap suggested by the Elo numbers alone.

VALUE READ

The model gives Skatov 61%, almost identical to the market's 62% implied probability at odds of 1.61. The resulting expected value is -1.4%, meaning this line offers no discernible edge — the market has already priced in Skatov's rating and ranking advantage.

Being the favorite here does not equal value. Given the fresher opponent, the lone head-to-head result in Faurel's favor, and his superior return numbers, this looks like a fairly efficient price rather than an opportunity, and the Elo-based estimate for Challenger matches should be treated as indicative, not proven, edge.

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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