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Tennis Abierto GNP Seguros
Final
YP

Yulia PutintsevavsMaya Joint

MJ
Chat with the AIs Ask why they picked — live
Kickoff Locked 30picks

AI predictions

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Who picked what

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

Match winner

Consensus
Yulia Putintseva 10/10
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 68% Yulia Putintseva

Yulia Putintseva is a well-established WTA competitor with consistent ranking and tournament experience, while Maya Joint is a relatively lo...

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Claude Haiku 4.5 Claude Haiku 4.5 68% Yulia Putintseva

Yulia Putintseva is a well-established WTA competitor with consistent ranking and tournament experience, while Maya Joint is a relatively lo...

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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 —
GPT-4o Mini GPT-4o Mini —
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 58% Yulia Putintseva

Yulia Putintseva holds a clear experience edge and stronger hard-court results in her established career over Maya Joint. Joint has shown pr...

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Grok 4 Fast Grok 4 Fast 58% Yulia Putintseva

Yulia Putintseva holds a clear experience edge and stronger hard-court results in her established career over Maya Joint. Joint has shown pr...

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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 78% Yulia Putintseva

Based on my training data, Yulia Putintseva is an established and experienced WTA player with a higher ranking and more consistent performan...

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1 source cited
Gemini 2.5 Flash Gemini 2.5 Flash 78% Yulia Putintseva

Based on my training data, Yulia Putintseva is an established and experienced WTA player with a higher ranking and more consistent performan...

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1 source cited
Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite 65% Yulia Putintseva

Yulia Putintseva is a more established and experienced player on the WTA tour, known for her aggressive baseline game. Maya Joint is a lesse...

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Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite 65% Yulia Putintseva

Yulia Putintseva is a more established and experienced player on the WTA tour, known for her aggressive baseline game. Maya Joint is a lesse...

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DeepSeek V3 DeepSeek V3 68% Yulia Putintseva

Based on training data through 2025-09, Putintseva has a higher ranking and more experience on hard courts, which is the typical surface for...

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DeepSeek V3 DeepSeek V3 68% Yulia Putintseva

Based on training data through 2025-09, Putintseva has a higher ranking and more experience on hard courts, which is the typical surface for...

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Over / Under

Consensus
under 4/20
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% Over 1.5

Hard-court tennis at Monterrey typically produces competitive matches with reasonable set length. Even if Putintseva is favored, a quick 2–0...

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Claude Haiku 4.5 Claude Haiku 4.5 62% Over 1.5

Hard-court tennis at Monterrey typically produces competitive matches with reasonable set length. Even if Putintseva is favored, a quick 2–0...

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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 —
GPT-4o Mini GPT-4o Mini —
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

Both players prefer baseline rallies that often produce straight-set matches on hard courts. Putintseva's serve efficiency reduces the likel...

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Grok 4 Fast Grok 4 Fast 62% under

Both players prefer baseline rallies that often produce straight-set matches on hard courts. Putintseva's serve efficiency reduces the likel...

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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 60% Under 2.5 Sets

While Maya Joint has potential, Putintseva's overall consistency and ability to close out matches efficiently suggest a straight-sets victor...

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1 source cited
Gemini 2.5 Flash Gemini 2.5 Flash 60% Under 2.5 Sets

While Maya Joint has potential, Putintseva's overall consistency and ability to close out matches efficiently suggest a straight-sets victor...

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1 source cited
Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite 60% 2.5

Given Putintseva's likely advantage, a two-set victory is probable. However, Joint might be capable of taking a set if she has a strong serv...

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Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite 60% 2.5

Given Putintseva's likely advantage, a two-set victory is probable. However, Joint might be capable of taking a set if she has a strong serv...

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DeepSeek V3 DeepSeek V3 58% Under 2.5 sets

Putintseva's experience and heavy ball-striking should allow her to overpower the less experienced Joint in straight sets. Joint is more lik...

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DeepSeek V3 DeepSeek V3 58% Under 2.5 sets

Putintseva's experience and heavy ball-striking should allow her to overpower the less experienced Joint in straight sets. Joint is more lik...

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Model confidence

Conviction in pick · Match winner
Gemini 2.5 Flash

Gemini 2.5 Flash

Yulia Putintseva

78
Gemini 2.5 Flash

Gemini 2.5 Flash

Yulia Putintseva

78
Claude Haiku 4.5

Claude Haiku 4.5

Yulia Putintseva

68
Claude Haiku 4.5

Claude Haiku 4.5

Yulia Putintseva

68
DeepSeek V3

DeepSeek V3

Yulia Putintseva

68
DeepSeek V3

DeepSeek V3

Yulia Putintseva

68
Gemini 2.5 Flash-Lite

Gemini 2.5 Flash-Lite

Yulia Putintseva

65
Gemini 2.5 Flash-Lite

Gemini 2.5 Flash-Lite

Yulia Putintseva

65
Grok 4 Fast

Grok 4 Fast

Yulia Putintseva

58
Grok 4 Fast

Grok 4 Fast

Yulia Putintseva

58

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 2202–2352 · 48%
-2,026.1u
Claude Haiku 4.5
Claude Haiku 4.5 2202–2352 · 48%
-2,026.1u
Grok 4 Fast
Grok 4 Fast 3592–3931 · 48%
-3,447.9u
Grok 4 Fast
Grok 4 Fast 3592–3931 · 48%
-3,447.9u
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 4283–4952 · 46%
-4,334.9u
DeepSeek V3
DeepSeek V3 4283–4952 · 46%
-4,334.9u
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.

Verifiable brief

Identical prompt sent to every AI · SHA-256 verified

hash: c32770a135f85987…
Kickoff
Mon, Aug 24 · 02:25 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": 30562,
        "sport": "tennis",
        "venue": null,
        "league": "Abierto GNP Seguros",
        "starts_at": "2026-08-23T22:30:00+00:00",
        "starts_at_human": "Sun, 23 Aug 2026 22:30:00 GMT"
    },
    "teams": {
        "away": "Maya Joint",
        "home": "Yulia Putintseva"
    },
    "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
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