Challenger · ELO ESTIMATE · 2026-07-26

N. Visker vs M. Mazzaprediction

San Marino
✗ Missed
VISKERWIN PROBABILITYMAZZA
62%
Elo prob.
@1.58
odds · 63% impl.
Rest 4d vs 28d🎾Serve 65%📈Form 5/10
WHAT THE ESTIMATE IS BASED ON

Tour Elo: 1687 vs 1599 — favorite by rating

Challenger tier · 233 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.
@1.60
fair odds
−1.4%
expected value
HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Visker●●●
Elo gap (1687 vs 1599) drives the 62% baseline model probability, making Visker the clear higher-rated player.
Serve/return▸ Visker●●
Visker's 65% serve-points-won tops Mazza's 55% by 10 points; Mazza's 37% return only slightly beats Visker's 34%.
Form▸ Visker●●
Visker's 5-5 last 10 (WLLLWLWWWL) is far sharper than Mazza's 2-8 skid (LWLWLWLLLL) with a 4-match losing streak.
Rest▸ Mazza●●
Visker has just 4 days rest after 6 matches in 14 days, versus Mazza's 28 days idle with zero matches.
Value= Even
Model's 62% nearly mirrors the market's 63% implied probability; EV is -1.4%, so no real pricing edge exists.
ELO AND FORM

Visker's Elo rating (1687) sits 88 points above Mazza's (1599), the core driver of the model's 62% probability for the favorite. That gap is reinforced by recent results: Visker's mixed but competitive 5-5 stretch (WLLLWLWWWL) contrasts with Mazza's four-match losing streak inside a 2-8 run (LWLWLWLLLL), suggesting Mazza is struggling to find any rhythm coming in.

Neither player shows a quality win in the data, so this read leans purely on rating and recent trend rather than any marquee result.

SERVE VS RETURN

Visker's serve is the single biggest technical edge here: he wins 65% of service points against Mazza's 55%, a 10-point gap that should let him hold more comfortably and dictate more service games. Mazza's return game is marginally better (37% vs Visker's 34%), meaning he converts break chances slightly more often, but that 3-point edge is dwarfed by Visker's serve advantage.

Net effect: the serve-return math points toward Visker controlling more free points overall, even though Mazza's return skill trims some of that gap on break points.

REST IMBALANCE

Visker arrives with only 4 days of rest after playing 6 matches in the last 14 days, a workload that can wear on legs and sharpness in a Challenger schedule. Mazza, on the other hand, has been off for 28 days with no matches in that span — full recovery, but also no recent match rhythm to draw on.

The data doesn't say which effect dominates, so this factor is a genuine unknown rather than a clean edge for either side, even though the schedule congestion flag is explicitly tagged against Visker.

VALUE READ

The model's 62% favorite probability is close to the market's own implied 63%, and the resulting expected value is -1.4% at odds of 1.58. That means backing Visker here is not a value play by this model's own math — the market has already priced him fairly, if not slightly generously.

Being the favorite is not the same as being a bet worth making. Given the soft nature of Challenger-level Elo markets, this is best read as a plausible-but-unproven edge, not an opportunity, and the honest takeaway is to treat the price as fair rather than mispriced.

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.

Analyze today's matches →