HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Shin●●●
267-point Elo gap (1641 vs 1374) drives the model's 82% win probability for Shin, a soft ITF-market estimate.
Form▸ Shin●●
Shin is 6-4 over his last 10 matches; Chauhan is 1-9 with an active 3-match losing streak, a clear momentum gap.
Rest▸ Chauhan●
Chauhan rests 6 days and played once in 14 days; Shin rests 4 days, played 3 times, and reached a QF here just 4 days ago.
Value= Even●●●
Odds of 1.06 imply 94% for Shin, above the model's 82%; expected value is -12.8%, so there is no edge to back him.
ELO GAP
The Elo differential is the core driver of this projection: Shin's 1641 rating sits 267 points above Chauhan's 1374, a gap large enough on its own to generate an 82% model probability. This is a rating-based estimate from a thin ITF dataset, not a refined analytical model, so the magnitude should be read as directional rather than precise.
FORM DIVERGENCE
Recent form reinforces the rating gap rather than offsetting it. Shin has won 6 of his last 10 matches, including a string of four straight wins earlier in the sample, while Chauhan has managed just 1 win in his last 10 and is currently on a 3-match losing streak. This divergence supports the favorite's edge but does not by itself change the pricing question.
REST AND FATIGUE
Physical freshness slightly favors Chauhan on paper: he has had 6 days off and played only once in the last two weeks, versus Shin's 4 days of rest and 3 matches in the same window. Shin also reached the quarterfinals at this same M15 Bali event just 4 days ago, which the data flags as a fatigue risk working against him — a factor to note, though its size is not quantifiable from what's given.
VALUE CHECK
Being the favorite is not the same as being a value play. The market prices Shin at odds of 1.06, implying a 94% win probability — noticeably higher than the model's own 82% estimate. That gap produces a expected value of -12.8%, meaning that even trusting the model's edge, the current price does not compensate for the risk.
This is a soft, lightly-traded ITF market, so the model's probability itself carries more uncertainty than a Challenger or ATP-level Elo read. Combined with the negative EV, there is no indicated value here — the favorite remains the more likely winner, but backing him at this price is not supported by the numbers.
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.