MODEL PREDICTION · 2026-07-08
GRASS

Flavio Cobolli vs Arthur Feryprediction

✗ Missed
COBOLLIWIN PROBABILITYFERY
77%
model prob.
@1.40
odds · 71% impl.
H2H 0–1 CobolliGrass 60%🎾Serve 60%📈Form 8/10 · 4✓
CONDITIONS OF THE MATCHin the modelcontext
Surface
Grass

Fast court, low bounce: rewards the serve and short points.

Temperature
31°C

Strong heat: warm air speeds the ball up and physical wear tells in long matches.

Humidity
34%

Very dry air: the ball travels faster.

Wind
3 km/h

Light wind: no noticeable effect.

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.

OUR MODEL'S REASONING

Ranking: #10 vs #118 (better ranked)

Recent form: 6/10 in recent matches

Head-to-head: 0-1 against

More rested: 23d vs opponent's 14d

Model 77% vs market 71% → the model sees it as MORE likely than the odds

WATCH FOR

!Returning from a long layoff (23d) — possible rustiness

!Unfavorable head-to-head record (0-1)

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.
@1.29
fair odds
+8.4%
expected value
HOW EACH FACTOR MATTERS
Level (Elo/ranking)▸ Cobolli●●●
Elo gap of 102 points (2043 vs 1941) and ranking #10 vs #118 give Cobolli a large structural edge.
Form▸ Cobolli●●
Cobolli beat Auger-Aliassime (Elo 2069) and De Minaur (2044), both above his own level; Fery's wins came below his 1941 Elo.
Head-to-head▸ Fery
Fery won the only prior meeting in 2026, but a single-match sample limits how much weight this carries.
Surface= Even●●
Grass lifts Fery further above his baseline (46%→57%, +11 pts) than it lifts Cobolli (58%→60%, +2 pts), narrowing the gap.
Serve/return▸ Fery●●
Fery's own serve (65%) and return (39%) rates both exceed Cobolli's (60%/36%), an underlying stat that cuts against the ranking gap.
Weather▸ Fery
Hot, dry air (31°C, 34% humidity) speeds the ball and helps the better server, which by the numbers is Fery at 65%.
Rest▸ Cobolli
Both rested 2 days, but Cobolli played fewer matches in the last 14 days (4 vs 5), a small fatigue edge.
RANKING AND ELO GAP

The headline gap here is structural: Cobolli sits at #10 with a 2043 Elo rating, while Fery is ranked #118 with a 1941 Elo. A 102-point Elo gap is significant and is the single biggest input pushing the model toward Cobolli at 77%. This is a case where the ranking differential is not just cosmetic — it reflects a real, sustained difference in level across a broad set of matches, not just recent form.

FORM QUALITY DIFFERS

Both players arrive on 4-match win streaks, so the raw streak numbers look similar. The difference shows up in opposition quality: Cobolli's recent wins came against Auger-Aliassime (Elo 2069) and De Minaur (2044), both rated above his own 2043 mark — a sign he's beating players at or above his level. Fery's best recent wins, over Dimitrov (1924) and Bergs (1912), came against players below his own 1941 Elo, which is a weaker signal of current form even though the streak length matches.

GRASS AND SERVE NUANCE

The surface numbers alone slightly favor Cobolli (60% vs 57% on grass), but the relative jump tells a different story: Fery's grass performance is 11 points above his own baseline (46%→57%), while Cobolli's is only 2 points above his (58%→60%). That means grass is disproportionately helping Fery's game relative to his general level, which softens Cobolli's edge on this specific surface.

This is reinforced by the serve/return split: Fery's own serve (65%) and return (39%) rates are both higher than Cobolli's (60%/36%). Combined with hot, dry conditions (31°C, 34% humidity, negligible wind) that speed up the ball and typically reward the better server, this creates a real mechanical risk for Cobolli even though he is the stronger player by ranking and Elo.

CONTEXT: H2H AND RECOVERY

The only previous meeting between these two went to Fery in 2026, though with just one match played this carries limited statistical weight against the much larger ranking and Elo gap. Rest is essentially even — both players are two days removed from their last match — with Cobolli having played one fewer match over the last two weeks (4 vs 5), a marginal freshness edge rather than a decisive one.

VALUE READ

The model puts Cobolli at 77% versus a market-implied 71% at odds of 1.40, producing a modeled edge of 8.4%. That gap is real but not enormous — the market is already pricing Cobolli as a clear favorite, and the model's disagreement is a matter of degree, not direction.

Given the serve/return and surface-relative numbers that lean toward Fery, and the H2H loss, this is not a case of the market missing something obvious. Being the favorite here does not guarantee a win, and the edge should be treated as modest rather than a strong mispricing.

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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