ATP MASTERS · MONTE-CARLO · ALCARAZ 68% vs SINNER 32%WTA · MADRID · SWIATEK 71% vs SABALENKA 29%ATP · ROME R32 · MEDVEDEV 54% vs RUUD 46%WTA · ROME · GAUFF 58% vs PAOLINI 42%ATP · GENEVA · TSITSIPAS 61% vs FRITZ 39%WTA · STRASBOURG · KEYS 49% vs RYBAKINA 51%
ATP MASTERS · MONTE-CARLO · ALCARAZ 68% vs SINNER 32%WTA · MADRID · SWIATEK 71% vs SABALENKA 29%ATP · ROME R32 · MEDVEDEV 54% vs RUUD 46%WTA · ROME · GAUFF 58% vs PAOLINI 42%ATP · GENEVA · TSITSIPAS 61% vs FRITZ 39%WTA · STRASBOURG · KEYS 49% vs RYBAKINA 51%
Live · AI model v4.2ATP · WTA · Grand Slams

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PredictAI reads ranking, surface, recent form, H2H and injuries — then answers your question in plain language, with a probability card when it can support one. When the data isn't enough, it tells you.

84.3%
Accuracy · 2024
12,408
Predictions logged
1.4s
Avg. first token
ATP · Monte-Carlo · QF
Alcaraz vs Sinner
Clay
Who has the edge on clay between these two right now?
PredictAI · v4.2
On clay this season Alcaraz holds a clear edge: 14–2 win record, two finals reached, and his return depth is up 11% versus 2023. Sinner is strong but his clay sample is shallower (8–3) and his serve+1 conversion drops 6 points on the slower surface. Against this specific matchup, Alcaraz also leads the H2H 4–2, with all clay meetings going his way.
Probability · Match winnerConfidence 82%
C. Alcaraz
68%
J. Sinner
32%
Form
+0.8
Surface
+1.4
H2H
+0.6
Rank Δ
−0.1
Recent form comparisonInjury risk check5-year H2H trend
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Clay
Set 2 · 4-3
ATP Monte-Carlo · QF
C. Alcaraz
ATP #2 · 22y
68%
J. Sinner
ATP #1 · 23y
32%
FormWWWLW
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Clay
Today · 18:30 CET
WTA Madrid · SF
I. Swiatek
WTA #1 · 24y
71%
A. Sabalenka
WTA #2 · 26y
29%
FormWWWWL
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Grass
Thursday · 14:00 BST
ATP Wimbledon · R16
N. Djokovic
ATP #3 · 37y
61%
D. Medvedev
ATP #5 · 28y
39%
FormWLWWW
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AI Analyst · How it works

Three modes. One honest model.

Streamed, token-by-token
Avg. first token < 1.4s — feels alive, not loading.
📊
Adaptive output
Probability + factors card only when the question is quantifiable. Otherwise: enriched text.
🛡
Calibrated honesty
A dedicated "insufficient data" state — designed, not an error.
🕐
History per match
Every Q&A collapses into a card on the match page — revisit later.
Open AI Analyst
State 01 · Thinking
How does Sinner's serve hold up on hard court this season?
PredictAI
State 02 · Exploratory · text-only
Tell me about Djokovic's clay record over the last 5 years.
PredictAI · v4.2
Over 2020–2024, Djokovic has gone 82–14 on clay (85.4%). He reached three Roland-Garros finals in that span and won in 2021 and 2023. His weakest patch was clay 2022, where he dropped two early matches to younger players adapting their return position against him. Slower courts (Rome, Madrid altitude excluded) show his cleanest baseline numbers. No probability card here — your question is descriptive, not predictive.
State 03 · Insufficient data
Predict Van Assche vs Stricker tomorrow.
PredictAI
Not enough data to predict this confidently.
No prior H2H on record. Combined hard-court matches this year: 8 — below our minimum threshold of 24. I can still share their individual recent form if useful.

Surface-aware

Every probability is weighted by surface — clay rewards return depth, grass rewards serve+1. Generic models miss this.

Real form, not vibes

Last 10 matches, surface-filtered, with injury flags from official tour feeds. No invented metrics.

Transparent confidence

A confidence score every time. When it drops, you see it — and the model says less.

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