C. Norrie vs J. Duckworth — prediction
Consistent bounce, medium-fast: neutral conditions, no style favored.
Strong heat: warm air speeds the ball up and physical wear tells in long matches.
Dry air: the ball travels normally.
Some wind: makes baseline control harder.
Surface feeds the model (surface specialization is one of its factors). Weather and altitude are context we publish for you — they do NOT move the probability.
›Ranking: #29 vs #79 (better ranked)
›Model 65% vs market 75% → the model sees it as less likely than the odds
›Recent form: 4/10 in recent matches
The ranking and Elo numbers tell a consistent story: Norrie sits 50 spots higher (#29 vs #79) and carries a 96-point Elo advantage (1913 vs 1817). That gap is reflected directly in the model's baseline split of 52% to 32%, before any adjustment for form or conditions — a solid structural edge for Norrie built on sustained tour-level results rather than a single data point.
On paper, Duckworth's 69% serve-points-won rate is the standout number in this match, higher than Norrie's own 62%. But tennis is a two-way street: Norrie's 37% return rate is well above Duckworth's 29%, meaning Norrie is statistically more likely to break than Duckworth is. That return gap is the clearest mechanism working against Duckworth's raw serving strength, since his own return numbers give him fewer tools to pressure Norrie's service games.
Neither player arrives in great form — Norrie is 4-6 in his last 10 (WLWWLLLLLW) and Duckworth is 3-7 (LLLWLLLWLW) — but Norrie's résumé includes wins over players rated 1979 and 1907 Elo, quality Duckworth cannot match. Both enter off a single-match win streak, but Norrie's file also flags a five-match losing skid just before his current uptick, and a reported 31-day layoff that could mean some early-match rustiness despite the favorable underlying numbers.
Conditions are hot (35°C), dry, and moderately windy (19 km/h). Heat and dry air generally speed up the ball and can help the more effective server, but the wind cuts the other way, penalizing whoever depends more heavily on serve precision. With Duckworth's game leaning more on his 69% serve number than Norrie's, the wind is a mild complicating factor for him, though not decisive on its own.
The model rates Norrie a 65% favorite, but the market prices him even higher, at an implied 75% (odds of 1.33). That's a meaningful gap, and it means the calculated expected value on backing Norrie here is -13% — the market is not just agreeing with the model's lean toward Norrie, it's overshooting it.
Being the favorite is not the same as offering value: Norrie is more likely than not to win this match based on the underlying factors, but at these odds there is no statistical edge to exploit. On the numbers presented, this is a fair skip for value-based decision-making, regardless of the expected outcome on court.
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.