HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Thomson●●●
Thomson's 1432 Elo vs Brown's 1390 supports the model's 56% probability, a modest but real rating edge.
Form▸ Brown●
Brown's last 10 shows 6 wins to Thomson's 5, though both enter on identical 3-match win streaks.
Rest▸ Thomson●
Brown played 5 matches in the last 14 days vs Thomson's 4, a slightly heavier recent workload.
Context= Even●
Both players reached the QF of this same event just 1 day ago, so any fatigue effect is shared, not a Thomson-specific edge.
Value= Even●●●
Odds imply 65% for Thomson but the model gives only 56%, producing a -13.7% EV — no edge here.
RATING EDGE
Thomson's Elo of 1432 sits 42 points above Brown's 1390, which is the main basis for his 56% win probability in this model. That gap is real but not large in the context of a soft ITF-level market, where rating estimates carry more noise than on tour.
There is no ranking, surface, or serve/return data available to corroborate or challenge this Elo gap, so the level factor stands largely on its own as the model's primary signal.
FORM AND WORKLOAD
Recent form slightly favors Brown, who is 6-4 over his last 10 matches compared to Thomson's 5-5, even though both players carry identical 3-match winning streaks into this contest. Neither trend is dominant enough to override the Elo gap, but it tempers the read that Thomson is clearly playing better tennis right now.
On rest, both players are one day removed from their last match, but Brown has logged 5 matches in the past 14 days against Thomson's 4. That extra match adds a small amount of accumulated fatigue on Brown's side, a minor factor favoring Thomson.
SHARED FATIGUE CONTEXT
Both players reached the quarterfinals of this same Huamantla event just one day before this match, so any deep-run fatigue applies symmetrically. This is a contextual note rather than a probability driver — it does not tilt the match toward either player since both are carrying similar recent match loads at the same stage of the same tournament.
VALUE READ
The market prices Thomson at an implied 65% to win, but the model puts him at only 56%, yielding a -13.7% expected value at the quoted 1.54 odds. That is a clear gap between what the market is charging and what the model's Elo-based estimate supports.
Because this is an ITF/Challenger Elo estimate, treat the model number itself with caution — it is a softer, less-analyzed market and the edge is unproven. On balance, Thomson is a plausible favorite on rating and rest, but backing him at this price does not represent value; the honest read is a negative-EV bet, not a betting opportunity.
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.