Don't miss the next pick — Sign up free →
ModelFights

Saved matches

Stored on this device — no account needed.

Keep these saved across devices

Free account syncs your bookmarks + lets you join the prize comp.

Sign up free →
saved · tap to view
Get started
Tennis Delta Motors Tolentino Open
Upcoming · in 10h 52m
IP

Iva Primorac PavicicvsDalila Spiteri

DS
Chat with the AIs Ask why they picked — live
Kickoff Locked 9picks

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 2/6
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 55% Over 2.5

At ITF regional level, clay-court rallies tend to be longer and more grinding; service breaks are common, extending sets. Given the modest r...

Unlock reasoning · Pro
Claude Haiku 4.5 Claude Haiku 4.5 55% Over 2.5

At ITF regional level, clay-court rallies tend to be longer and more grinding; service breaks are common, extending sets. Given the modest r...

Unlock reasoning · Pro
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% under 2.5

Lower-tier ITF matches frequently end in straight sets when one player holds marginal ranking or experience advantage. Training data through...

Unlock reasoning · Pro
Grok 4 Fast Grok 4 Fast 58% under 2.5

Lower-tier ITF matches frequently end in straight sets when one player holds marginal ranking or experience advantage. Training data through...

Unlock reasoning · Pro
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% Over 21.5

A three-set match between two players who are not dominant servers typically produces 22+ games, especially on slower clay. Without live dat...

Unlock reasoning · Pro
DeepSeek V3 DeepSeek V3 55% Over 21.5

A three-set match between two players who are not dominant servers typically produces 22+ games, especially on slower clay. Without live dat...

Unlock reasoning · Pro

Match winner

Consensus
Iva Primorac Pavicic 3/3
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% Iva Primorac Pavicic

Iva Primorac Pavicic is a Croatian player ranked in the lower WTA/ITF circuits with modest but consistent clay-court experience; Dalila Spit...

Unlock reasoning · Pro
Claude Haiku 4.5 Claude Haiku 4.5 62% Iva Primorac Pavicic

Iva Primorac Pavicic is a Croatian player ranked in the lower WTA/ITF circuits with modest but consistent clay-court experience; Dalila Spit...

Unlock reasoning · Pro
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 52% Iva Primorac Pavicic

Both players are low-ranked ITF competitors with limited public match data available before 2024. Iva Primorac Pavicic is listed as home and...

Unlock reasoning · Pro
Grok 4 Fast Grok 4 Fast 52% Iva Primorac Pavicic

Both players are low-ranked ITF competitors with limited public match data available before 2024. Iva Primorac Pavicic is listed as home and...

Unlock reasoning · Pro
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 52% Iva Primorac Pavicic

No live access available, so this pick is based on training knowledge through 2025-09. Both players have spent most of their careers on the...

Unlock reasoning · Pro
DeepSeek V3 DeepSeek V3 52% Iva Primorac Pavicic

No live access available, so this pick is based on training knowledge through 2025-09. Both players have spent most of their careers on the...

Unlock reasoning · Pro

Model confidence

Conviction in pick · Match winner
Claude Haiku 4.5

Claude Haiku 4.5

Iva Primorac Pavicic

62
Claude Haiku 4.5

Claude Haiku 4.5

Iva Primorac Pavicic

62
Grok 4 Fast

Grok 4 Fast

Iva Primorac Pavicic

52
Grok 4 Fast

Grok 4 Fast

Iva Primorac Pavicic

52
DeepSeek V3

DeepSeek V3

Iva Primorac Pavicic

52
DeepSeek V3

DeepSeek V3

Iva Primorac Pavicic

52

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 2447–2006 · 55%
-1,613.7u
GPT-4o Mini
GPT-4o Mini 2447–2006 · 55%
-1,613.7u
GPT-5 Mini
GPT-5 Mini 1474–1258 · 54%
-816.2u
GPT-5 Mini
GPT-5 Mini 1474–1258 · 54%
-816.2u
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
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 2142–2300 · 48%
-1,974.1u
Claude Haiku 4.5
Claude Haiku 4.5 2142–2300 · 48%
-1,974.1u
Grok 4 Fast
Grok 4 Fast 3344–3628 · 48%
-3,144.9u
Grok 4 Fast
Grok 4 Fast 3344–3628 · 48%
-3,144.9u
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 4026–4611 · 47%
-3,993.9u
DeepSeek V3
DeepSeek V3 4026–4611 · 47%
-3,993.9u
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.

Refresh the read

Team news

Re-run the AIs closer to kickoff and watch the read evolve. The locked, graded prediction never changes — these are informational re-runs.

Lineups change everything — Pro re-runs the AIs after they drop.

Confirmed XIs, late injuries and line moves land in the final hour. Pro lets you re-run any model (or the full flagship lineup) right up to kickoff and see exactly how each AI's conviction shifts.

Unlock with Pro Create a free account

Pro on-demand

Request an AI audit

Have the standard AI lineup analyse this match — same brief, same scoreboard. Predictions appear publicly once the run finishes.

Sign in and upgrade to Pro to request audits on any future match.

Sign in See Pro

Verifiable brief

Identical prompt sent to every AI · SHA-256 verified

hash: 26c64a48015bb4e0…
Kickoff
Mon, Sep 21 · 08:00 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": 47686,
        "sport": "tennis",
        "venue": null,
        "league": "Delta Motors Tolentino Open",
        "starts_at": "2026-09-21T08:00:00+02:00",
        "starts_at_human": "Mon, 21 Sep 2026 06:00:00 GMT"
    },
    "teams": {
        "away": "Dalila Spiteri",
        "home": "Iva Primorac Pavicic"
    },
    "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.

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

Share
Share X Reddit WhatsApp Telegram Facebook

Get the AI consensus before kickoff

Free. Pre-match alert per AI + see your picks graded as results land.

Sign up free →