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Tennis Singapore Tennis Open presented by BNP Paribas
Upcoming · in 9h 08m
TP

Tatiana ProzorovavsWang Xinyu

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

Your call

Who wins? One tap, no signup.

AI predictions

Ask the AIs

Who picked what

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

Over / Under

Consensus
over_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 56% Over 2.5

Best-of-three tennis at a lower-tier WTA event (250-level Singapore Open) typically features competitive matches lasting 2–3 sets. Prozorova...

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Claude Haiku 4.5 Claude Haiku 4.5 56% Over 2.5

Best-of-three tennis at a lower-tier WTA event (250-level Singapore Open) typically features competitive matches lasting 2–3 sets. Prozorova...

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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 65% over_2.5

Both players have shown resilience in their recent matches, with Prozorova's recent three-set matches indicating a tendency for extended con...

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🔍 researched 3 sources cited
GPT-4o Mini GPT-4o Mini 65% over_2.5

Both players have shown resilience in their recent matches, with Prozorova's recent three-set matches indicating a tendency for extended con...

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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 62% under_2.5

Wang Xinyu is expected to dominate on serve and limit break opportunities. Training knowledge indicates these ranking mismatches on hard cou...

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Grok 4 Fast Grok 4 Fast 62% under_2.5

Wang Xinyu is expected to dominate on serve and limit break opportunities. Training knowledge indicates these ranking mismatches on hard cou...

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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 55% Wang Xinyu

Wang Xinyu is the clear favourite and should be favoured to win in straight sets, but Prozorova's solid defensive baseline game can extend r...

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DeepSeek V3 DeepSeek V3 55% Wang Xinyu

Wang Xinyu is the clear favourite and should be favoured to win in straight sets, but Prozorova's solid defensive baseline game can extend r...

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Match winner

Consensus
Wang Xinyu 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 62% Wang Xinyu

Wang Xinyu is the higher-ranked player (around 40–50 range in 2026) with stronger hard-court credentials and superior depth compared to Proz...

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Claude Haiku 4.5 Claude Haiku 4.5 62% Wang Xinyu

Wang Xinyu is the higher-ranked player (around 40–50 range in 2026) with stronger hard-court credentials and superior depth compared to Proz...

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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 75% Tatiana Prozorova

Xinyu Wang has demonstrated strong performance on indoor hard courts, boasting a 4-1 record in 2026 and a 46-20 win-loss record on this surf...

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🔍 researched 3 sources cited
GPT-4o Mini GPT-4o Mini 75% Tatiana Prozorova

Xinyu Wang has demonstrated strong performance on indoor hard courts, boasting a 4-1 record in 2026 and a 46-20 win-loss record on this surf...

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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 68% Wang Xinyu

Wang Xinyu holds a significantly higher career ranking and more consistent results on hard courts than Prozorova. Training data through 2023...

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Grok 4 Fast Grok 4 Fast 68% Wang Xinyu

Wang Xinyu holds a significantly higher career ranking and more consistent results on hard courts than Prozorova. Training data through 2023...

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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 66% Wang Xinyu

No live access available, so this is predicted from training data through 2025-09. Wang Xinyu is the substantially more established player,...

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DeepSeek V3 DeepSeek V3 66% Wang Xinyu

No live access available, so this is predicted from training data through 2025-09. Wang Xinyu is the substantially more established player,...

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Model confidence

Conviction in pick · Match winner
GPT-4o Mini

GPT-4o Mini

Tatiana Prozorova

75
GPT-4o Mini

GPT-4o Mini

Tatiana Prozorova

75
Grok 4 Fast

Grok 4 Fast

Wang Xinyu

68
Grok 4 Fast

Grok 4 Fast

Wang Xinyu

68
DeepSeek V3

DeepSeek V3

Wang Xinyu

66
DeepSeek V3

DeepSeek V3

Wang Xinyu

66
Claude Haiku 4.5

Claude Haiku 4.5

Wang Xinyu

62
Claude Haiku 4.5

Claude Haiku 4.5

Wang Xinyu

62

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 2473–2043 · 55%
-1,650.7u
GPT-4o Mini
GPT-4o Mini 2473–2043 · 55%
-1,650.7u
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 1494–1296 · 54%
-854.2u
GPT-5 Mini
GPT-5 Mini 1494–1296 · 54%
-854.2u
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 2158–2311 · 48%
-1,985.1u
Claude Haiku 4.5
Claude Haiku 4.5 2158–2311 · 48%
-1,985.1u
Grok 4 Fast
Grok 4 Fast 3438–3775 · 48%
-3,291.9u
Grok 4 Fast
Grok 4 Fast 3438–3775 · 48%
-3,291.9u
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 4128–4766 · 46%
-4,148.9u
DeepSeek V3
DeepSeek V3 4128–4766 · 46%
-4,148.9u
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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Verifiable brief

Identical prompt sent to every AI · SHA-256 verified

hash: e70ee8575e4c278c…
Kickoff
Fri, Sep 25 · 06:30 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": 48457,
        "sport": "tennis",
        "venue": null,
        "league": "Singapore Tennis Open presented by BNP Paribas",
        "starts_at": "2026-09-25T06:30:00+02:00",
        "starts_at_human": "Fri, 25 Sep 2026 04:30:00 GMT"
    },
    "teams": {
        "away": "Wang Xinyu",
        "home": "Tatiana Prozorova"
    },
    "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
  • 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.

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

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

  • Grok 4 Fast Grok 4 Fast
    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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