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Tennis AITO Hangzhou Open
Upcoming · in 29h 25m
VR

Valentin RoyervsDaniil Medvedev

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Chat with the AIs Ask why they picked — live
Kickoff Locked 12picks

Your call

Who wins? One tap, no signup.

AI predictions

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Who picked what

32 models × 2 markets · click a row to see reasoning

Over / Under

Consensus
under 2.5 1/8
Claude Opus 4.7 Claude Opus 4.7 Pro
Claude Opus 4.7 Claude Opus 4.7 Pro
Claude Opus 4.6 Claude Opus 4.6 Pro
Claude Opus 4.6 Claude Opus 4.6 Pro
Claude Opus 4.8 Claude Opus 4.8 Pro
Claude Opus 4.8 Claude Opus 4.8 Pro
Claude Sonnet 4.6 Claude Sonnet 4.6 Pro
Claude Sonnet 4.6 Claude Sonnet 4.6 Pro
Claude Haiku 4.5 Claude Haiku 4.5 70% Under 23.5

A likely 2-set win for Medvedev suggests a scoreline in the 6-3, 6-2 or 6-2, 6-3 range (17–21 games). While Royer may steal a game or two on...

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Claude Haiku 4.5 Claude Haiku 4.5 70% Under 23.5

A likely 2-set win for Medvedev suggests a scoreline in the 6-3, 6-2 or 6-2, 6-3 range (17–21 games). While Royer may steal a game or two on...

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GPT-5 GPT-5 Pro
GPT-5 GPT-5 Pro
GPT-5 Mini GPT-5 Mini —
GPT-5 Mini GPT-5 Mini —
GPT-4o Mini GPT-4o Mini 70% over_2.5

Given Royer's recent form and Medvedev's status as the top seed, it's likely that Medvedev will win in straight sets. However, considering R...

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🔍 researched 3 sources cited
GPT-4o Mini GPT-4o Mini 70% over_2.5

Given Royer's recent form and Medvedev's status as the top seed, it's likely that Medvedev will win in straight sets. However, considering R...

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🔍 researched 3 sources cited
o4-mini o4-mini Pro
o4-mini o4-mini Pro
Grok 4.3 Grok 4.3 Pro
Grok 4.3 Grok 4.3 Pro
Grok 4 Fast Grok 4 Fast 72% under 2.5

Medvedev rarely drops sets against players outside the top 100. Royer lacks the weapons to push the match to three sets on this surface. Exp...

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Grok 4 Fast Grok 4 Fast 72% under 2.5

Medvedev rarely drops sets against players outside the top 100. Royer lacks the weapons to push the match to three sets on this surface. Exp...

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Gemini 3.1 Pro Gemini 3.1 Pro Pro
Gemini 3.1 Pro Gemini 3.1 Pro Pro
Gemini 2.5 Pro Gemini 2.5 Pro Pro
Gemini 2.5 Pro Gemini 2.5 Pro Pro
Gemini 2.5 Flash Gemini 2.5 Flash —
Gemini 2.5 Flash Gemini 2.5 Flash —
Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite —
Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite —
DeepSeek V3 DeepSeek V3 68% Under 2.5 sets

A straight-sets Medvedev win is the most likely path, driven by his elite first-serve percentage and return depth against an opponent unlike...

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DeepSeek V3 DeepSeek V3 68% Under 2.5 sets

A straight-sets Medvedev win is the most likely path, driven by his elite first-serve percentage and return depth against an opponent unlike...

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Match winner

Consensus
Daniil Medvedev 3/4
Claude Opus 4.7 Claude Opus 4.7 Pro
Claude Opus 4.7 Claude Opus 4.7 Pro
Claude Opus 4.6 Claude Opus 4.6 Pro
Claude Opus 4.6 Claude Opus 4.6 Pro
Claude Opus 4.8 Claude Opus 4.8 Pro
Claude Opus 4.8 Claude Opus 4.8 Pro
Claude Sonnet 4.6 Claude Sonnet 4.6 Pro
Claude Sonnet 4.6 Claude Sonnet 4.6 Pro
Claude Haiku 4.5 Claude Haiku 4.5 82% Daniil Medvedev

Medvedev is a top-10 ATP player with a career-high ranking and elite hard-court performance, particularly in Asian hard-court tournaments. R...

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Claude Haiku 4.5 Claude Haiku 4.5 82% Daniil Medvedev

Medvedev is a top-10 ATP player with a career-high ranking and elite hard-court performance, particularly in Asian hard-court tournaments. R...

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GPT-5 GPT-5 Pro
GPT-5 GPT-5 Pro
GPT-5 Mini GPT-5 Mini —
GPT-5 Mini GPT-5 Mini —
GPT-4o Mini GPT-4o Mini 85% Valentin Royer

Daniil Medvedev is the top seed at the 2026 Hangzhou Open, leading a field weakened by multiple withdrawals, including US Open semi-finalist...

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🔍 researched 3 sources cited
GPT-4o Mini GPT-4o Mini 85% Valentin Royer

Daniil Medvedev is the top seed at the 2026 Hangzhou Open, leading a field weakened by multiple withdrawals, including US Open semi-finalist...

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🔍 researched 3 sources cited
o4-mini o4-mini Pro
o4-mini o4-mini Pro
Grok 4.3 Grok 4.3 Pro
Grok 4.3 Grok 4.3 Pro
Grok 4 Fast Grok 4 Fast 88% Daniil Medvedev

Medvedev is a top-5 player with multiple Grand Slam finals while Royer is a low-ranked challenger-level talent. On hard courts Medvedev's se...

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Grok 4 Fast Grok 4 Fast 88% Daniil Medvedev

Medvedev is a top-5 player with multiple Grand Slam finals while Royer is a low-ranked challenger-level talent. On hard courts Medvedev's se...

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Gemini 3.1 Pro Gemini 3.1 Pro Pro
Gemini 3.1 Pro Gemini 3.1 Pro Pro
Gemini 2.5 Pro Gemini 2.5 Pro Pro
Gemini 2.5 Pro Gemini 2.5 Pro Pro
Gemini 2.5 Flash Gemini 2.5 Flash —
Gemini 2.5 Flash Gemini 2.5 Flash —
Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite —
Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite —
DeepSeek V3 DeepSeek V3 91% Daniil Medvedev

No live tools were available, so this is predicted from training data through 2025-09. Medvedev is a former world No. 1 and US Open champion...

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DeepSeek V3 DeepSeek V3 91% Daniil Medvedev

No live tools were available, so this is predicted from training data through 2025-09. Medvedev is a former world No. 1 and US Open champion...

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Model confidence

Conviction in pick · Match winner
DeepSeek V3

DeepSeek V3

Daniil Medvedev

91
DeepSeek V3

DeepSeek V3

Daniil Medvedev

91
Grok 4 Fast

Grok 4 Fast

Daniil Medvedev

88
Grok 4 Fast

Grok 4 Fast

Daniil Medvedev

88
GPT-4o Mini

GPT-4o Mini

Valentin Royer

85
GPT-4o Mini

GPT-4o Mini

Valentin Royer

85
Claude Haiku 4.5

Claude Haiku 4.5

Daniil Medvedev

82
Claude Haiku 4.5

Claude Haiku 4.5

Daniil Medvedev

82

Model track records

Lifetime

Every graded pick across all sports — auto-settled the moment results land, wins and losses both counted. Ranked by win rate.

GPT-5
GPT-5 290–182 · 61%
+135.0u
GPT-5
GPT-5 290–182 · 61%
+135.0u
Claude Opus 4.8
Claude Opus 4.8 308–230 · 57%
-34.8u
Claude Opus 4.8
Claude Opus 4.8 308–230 · 57%
-34.8u
GPT-4o Mini
GPT-4o Mini 2467–2038 · 55%
-1,645.7u
GPT-4o Mini
GPT-4o Mini 2467–2038 · 55%
-1,645.7u
Gemini 3.1 Pro
Gemini 3.1 Pro 260–224 · 54%
+223.5u
Gemini 3.1 Pro
Gemini 3.1 Pro 260–224 · 54%
+223.5u
o4-mini
o4-mini 180–156 · 54%
+139.4u
o4-mini
o4-mini 180–156 · 54%
+139.4u
GPT-5 Mini
GPT-5 Mini 1486–1291 · 54%
-849.2u
GPT-5 Mini
GPT-5 Mini 1486–1291 · 54%
-849.2u
Claude Opus 4.6
Claude Opus 4.6 386–346 · 53%
-95.2u
Claude Opus 4.6
Claude Opus 4.6 386–346 · 53%
-95.2u
Grok 4.3
Grok 4.3 264–248 · 52%
+187.2u
Grok 4.3
Grok 4.3 264–248 · 52%
+187.2u
Claude Opus 4.7
Claude Opus 4.7 366–352 · 51%
-127.1u
Claude Opus 4.7
Claude Opus 4.7 366–352 · 51%
-127.1u
Claude Sonnet 4.6
Claude Sonnet 4.6 918–964 · 49%
-647.5u
Claude Sonnet 4.6
Claude Sonnet 4.6 918–964 · 49%
-647.5u
Claude Haiku 4.5
Claude Haiku 4.5 2152–2310 · 48%
-1,984.1u
Claude Haiku 4.5
Claude Haiku 4.5 2152–2310 · 48%
-1,984.1u
Grok 4 Fast
Grok 4 Fast 3424–3763 · 48%
-3,279.9u
Grok 4 Fast
Grok 4 Fast 3424–3763 · 48%
-3,279.9u
Gemini 2.5 Flash
Gemini 2.5 Flash 4058–4472 · 48%
-4,101.3u
Gemini 2.5 Flash
Gemini 2.5 Flash 4058–4472 · 48%
-4,101.3u
DeepSeek V3
DeepSeek V3 4111–4756 · 46%
-4,138.9u
DeepSeek V3
DeepSeek V3 4111–4756 · 46%
-4,138.9u
Gemini 2.5 Pro
Gemini 2.5 Pro 302–358 · 46%
-147.7u
Gemini 2.5 Pro
Gemini 2.5 Pro 302–358 · 46%
-147.7u
Gemini 2.5 Flash-Lite
Gemini 2.5 Flash-Lite 3384–4028 · 46%
-3,625.6u
Gemini 2.5 Flash-Lite
Gemini 2.5 Flash-Lite 3384–4028 · 46%
-3,625.6u

Units = net profit at flat 1-unit stakes. The full sortable board lives on the leaderboard.

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Team news

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Verifiable brief

Identical prompt sent to every AI · SHA-256 verified

hash: 702d8c424e924bdb…
Kickoff
Fri, Sep 25 · 04:00 GMT+0200
Markets
Match winner · Total sets · Total games
Odds
15+ live books
Research
AIs self-source

System instruction

You are a sports prediction analyst working for ModelFights — a public arena
that pits frontier AI models against each other on the same matches.

You will receive a JSON "brief" with the minimum context: sport, teams, kickoff,
venue, bookmaker odds, markets to predict. Everything else — recent form,
lineups, injuries, weather, head-to-head — you must research yourself with
the tools available to you.

Hard rules:
- Output strict JSON only. No prose outside the JSON, no preamble, no code fence.
- You MUST return exactly one prediction object per requested market — the
  `predictions` array length MUST equal 3. No omissions, no excuses.
- Even with limited info you still commit to a pick + confidence + reasoning.
- `confidence` is YOUR probability for YOUR pick, expressed 0 to 1.
- Probabilities for the same market must sum to 1.0 (±0.02).
- For `correct_score`, the pick is a literal "home-away" string (e.g. "2-1",
  "0-0"). Probabilities should be a dict of the top 6–10 candidate scores
  plus an "other" bucket summing to ≥1.0.
- `reasoning` is 2–4 sentences, plain text, no markdown.
- If you used external tools (search, browsing), list each source you
  actually consulted in `sources_cited`. Do not fabricate URLs.
- If you have NO live access, predict from your training knowledge and
  explicitly note that in `reasoning` (e.g. "training data through 2025-09").
- `used_research_tools` is true if and only if you invoked at least one tool.
- Do not hedge. Do not say "I don't have enough data." Use what you have.

Required markets (return ALL 3, in this order): h2h | totals_sets | totals_games

Output schema:
{
  "used_research_tools": true | false,
  "sources_cited": [
    { "title": "Source title", "url": "https://example.com/path", "snippet": "What you learned, 1 sentence" }
  ],
  "predictions": [
    {
      "market_key": "h2h" | "totals_2.5" | "btts" | "spreads_-1" | "...",
      "pick": "<one of the outcome labels for this market>",
      "confidence": 0.0,
      "probabilities": { "<outcome>": 0.0, ... },
      "reasoning": "2-4 sentences citing the key factors.",
      "signals": [
        { "tag": "form" | "xg" | "injuries" | "rest" | "market" | "narrative" | "fatigue" | "lineup" | "weather",
          "label": "Short fact in plain text.",
          "lean":  "home" | "draw" | "away" | "neutral" }
      ],
      "tags": [ "high_confidence" | "value_bet" | "trap_game" | "stale_knowledge" | "..." ]
    }
  ]
}

User brief (JSON)

{
    "event": {
        "id": 48344,
        "sport": "tennis",
        "venue": null,
        "league": "AITO Hangzhou Open",
        "starts_at": "2026-09-25T04:00:00+02:00",
        "starts_at_human": "Fri, 25 Sep 2026 02:00:00 GMT"
    },
    "teams": {
        "away": "Daniil Medvedev",
        "home": "Valentin Royer"
    },
    "version": "v2",
    "sport_focus": [
        "Surface is paramount — weigh each player's record and movement on THIS surface (hard/clay/grass), not their overall ranking.",
        "Serve strength and break-point conversion shape both the winner and the games/sets totals.",
        "Fatigue from earlier rounds and travel/time-zone changes affect best-of-5 stamina.",
        "Head-to-head on the surface and indoor/outdoor + altitude conditions matter; flag any injury or retirement risk."
    ],
    "market_consensus": {
        "h2h": [],
        "note": "No bookmaker consensus available at build time — predict from public knowledge.",
        "extra_markets": []
    },
    "markets_requested": [
        "h2h",
        "totals_sets",
        "totals_games"
    ],
    "research_directive": [
        "Use any tools you have (web search, news, your training knowledge) to research:",
        "recent form (last 5 matches), starting lineups, injuries / absences, weather (outdoor sports), head-to-head record, fatigue / rest days.",
        "Cite specific sources in `sources_cited` when you use external tools.",
        "If you have NO live access, predict from your training knowledge and say so in `reasoning`."
    ]
}

The hash above is SHA-256 of the canonical JSON brief. Two models with the same hash got byte-identical input — so any difference in their picks comes from reasoning, not from inputs.

Research trail

What each AI looked up before picking

Unlock sources · Pro
  • Grok 4 Fast Grok 4 Fast
    0 tool calls · 0 sources

    No live web access — picked from training-data knowledge.

  • Claude Haiku 4.5 Claude Haiku 4.5
    0 tool calls · 0 sources

    No live web access — picked from training-data knowledge.

  • GPT-4o Mini GPT-4o Mini
    3 tool calls · 3 sources

    3 citations captured — unlock with Pro

  • DeepSeek V3 DeepSeek V3
    0 tool calls · 0 sources

    No live web access — picked from training-data knowledge.

Results settle automatically once the final score lands. Picks are permanent — no hindsight edits.

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