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MODEL PREDICTION · 2026-07-13

N. Borges vs M. Kouame — prediction

BORGESWIN PROBABILITYKOUAME
73%
model prob.
@1.27
odds · 79% impl.
🌡22° · 78% humRest 12d vs 7d🎾Serve 69%📈Form 5/10
THE MODEL'S REASONING

Ranking: #48 vs #318 (better ranked)

Recent form: 5/10 in recent matches

Model 73% vs market 79% → the model sees it as less likely than the odds

Calibrated model probability (~65% out-of-sample accuracy). Not a guarantee: the model ≈ the market on average, so the odds already capture almost all the edge. 18+ · gamble responsibly.
@1.37
fair odds
−7.2%
expected value
HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Borges●●●
Borges carries a clear class edge: Elo 1866 vs 1756 and rank #48 vs #318, a much deeper résumé than Kouame's.
Model vs Market= Even●●●
The model reads this as a 50-50 match while the market prices Borges at 79% (odds 1.26), producing a -37% EV on the favorite.
Form= Even●●
Both are mediocre lately: Borges 5/10 (streak -1) and Kouame 5/10 (streak -2), each with one notable quality win, no momentum edge.
Rest= Even
Borges has 12 days since his last match but played 2 in the last 14; Kouame has 7 days off and only 1 match, mixed freshness signals.
Serve/Return▸ Borges●●
Borges backs his ranking with strong own numbers - 69% serve points and 35% return points won - but no comparable data exists for Kouame.
Weather= Even
Mild 21°C, 82% humidity and a light 6 km/h wind slightly slow the ball, a modest test for Borges's 69% service rate with no return data on Kouame to compare.
CLASS AND RANKING GAP

Borges's numbers on paper are clearly superior: an Elo rating of 1866 against Kouame's 1756, and a ranking of #48 versus #318. This is the kind of gap that normally points to a comfortable favorite, and it explains why the market prices him so heavily.

However, the model's calibrated read does not fully endorse that gap as a reliable predictor of the match outcome here - it settles at a 50% probability for Borges, treating the ranking and Elo advantage as real but not decisive on its own for this specific matchup.

FORM WITHOUT MOMENTUM

Neither player is in strong form. Borges is 5-5 in his last ten with a one-match losing streak, his best recent scalp being a win over L. Darderi (Elo 1937). Kouame mirrors that record, also 5-5, but on a longer two-match skid, with his own quality win over D. Vallejo (Elo 1905).

Given the near-identical recent trajectories and comparable quality wins, form does not tilt the picture toward either player - it is a wash rather than a differentiator in this match.

CONDITIONS AND SERVE IMPACT

The weather is mild (21°C) but notably humid (82%) with only light wind (6 km/h). High humidity tends to slow the ball and can shave a bit off a big server's advantage by extending rallies, which is relevant given Borges's strong service numbers - 69% of service points won.

Without any serve or return percentages for Kouame, it is not possible to quantify how the conditions affect his side of the ball specifically. What is clear is that Borges brings a proven service weapon into a moderately slow, humid environment that could blunt it somewhat.

RECOVERY PICTURE

The rest data is mixed rather than one-sided. Borges has had 12 days since his last outing but logged two matches in the last 14 days, suggesting recent match play despite the longer gap since his most recent one. Kouame, by contrast, played more recently (7 days ago) but has only one match in the same 14-day window.

Neither pattern points to a clear fatigue or freshness advantage for either player based on the numbers given.

VALUE READ

This is the key takeaway: the model calibrates Borges at 50% to win, while the market - via odds of 1.26 - implies a 79% probability. That is a large gap, and it produces a -37% expected value on backing the favorite at this price.

Being the higher-ranked, higher-Elo player does not automatically make Borges a value bet here; the market is pricing in far more certainty than the model's factors support. On these numbers, there is no honest edge in backing the favorite at 1.26, and bettors should treat this as a case where the model and the market meaningfully disagree, not a green light for value.

Impact and analysis from real match data (Elo, form, head-to-head, rest, surface vs baseline, weather, altitude). The model ≈ the market on average; the odds already capture almost all the edge. 18+ · gamble responsibly.

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