Tennis
WTA Queen's Club Championships
Upcoming · in 14h 34m
ER
Elena Rybakina vs Tatjana Maria
TMKickoff · Thu, Jun 11 · 09:00 GMT+0000
Verifiable brief
Identical prompt sent to every AI · SHA-256 verified
hash:
f1eabff092185ffe…
- Sport
- Thu, Jun 11 · 09:00 GMT+0000
- Markets
- h2h · totals_sets · totals_games
- Source
- The Odds API · live
- 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.
- Pick exactly one outcome per requested market.
- `confidence` is YOUR probability for YOUR pick, expressed 0 to 1.
- Probabilities for the same market must sum to 1.0 (±0.02).
- `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.
Markets to predict (omit any you cannot pick from the brief): 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)
{
"version": "v1",
"built_at": "2026-06-10T18:25:23+00:00",
"event": {
"id": 478,
"sport": "tennis",
"league": "WTA Queen's Club Championships",
"starts_at": "2026-06-11T09:00:00+00:00",
"starts_at_human": "Thu, 11 Jun 2026 09:00:00 GMT",
"venue": null
},
"teams": {
"home": "Elena Rybakina",
"away": "Tatjana Maria"
},
"market_consensus": {
"h2h": {
"home": 1.24,
"away": 4.8
},
"extra_markets": {
"totals": [
{
"point": 20.5,
"outcome": "Under",
"price": 1.87
},
{
"point": 20.5,
"outcome": "Over",
"price": 1.87
},
{
"point": 20.5,
"outcome": "Under",
"price": 1.91
},
{
"point": 20.5,
"outcome": "Over",
"price": 1.91
},
{
"point": 20.5,
"outcome": "Under",
"price": 1.91
},
{
"point": 20.5,
"outcome": "Over",
"price": 1.91
},
{
"point": 20.5,
"outcome": "Under",
"price": 1.92
},
{
"point": 20.5,
"outcome": "Over",
"price": 1.93
},
{
"point": 20.5,
"outcome": "Under",
"price": 1.87
},
{
"point": 20.5,
"outcome": "Over",
"price": 1.87
},
{
"point": 20.5,
"outcome": "Under",
"price": 1.91
},
{
"point": 20.5,
"outcome": "Over",
"price": 1.91
},
{
"point": 20.5,
"outcome": "Under",
"price": 1.85
},
{
"point": 20.5,
"outcome": "Over",
"price": 1.91
},
{
"point": 20.5,
"outcome": "Under",
"price": 1.82
},
{
"point": 20.5,
"outcome": "Over",
"price": 1.88
},
{
"point": 20.5,
"outcome": "Under",
"price": 1.85
},
{
"point": 20.5,
"outcome": "Over",
"price": 1.91
},
{
"point": 20.5,
"outcome": "Under",
"price": 1.73
},
{
"point": 20.5,
"outcome": "Over",
"price": 1.79
},
{
"point": 20.5,
"outcome": "Under",
"price": 1.85
},
{
"point": 20.5,
"outcome": "Over",
"price": 1.91
},
{
"point": 20.5,
"outcome": "Under",
"price": 1.85
},
{
"point": 20.5,
"outcome": "Over",
"price": 1.91
}
],
"spreads": [
{
"point": 4.5,
"outcome": "Tatjana Maria",
"price": 1.91
},
{
"point": -4.5,
"outcome": "Elena Rybakina",
"price": 1.83
},
{
"point": 4.5,
"outcome": "Tatjana Maria",
"price": 2
},
{
"point": -4.5,
"outcome": "Elena Rybakina",
"price": 1.83
},
{
"point": 4.5,
"outcome": "Tatjana Maria",
"price": 2
},
{
"point": -4.5,
"outcome": "Elena Rybakina",
"price": 1.83
},
{
"point": 4.5,
"outcome": "Tatjana Maria",
"price": 1.93
},
{
"point": -4.5,
"outcome": "Elena Rybakina",
"price": 1.93
},
{
"point": 4.5,
"outcome": "Tatjana Maria",
"price": 1.87
},
{
"point": -4.5,
"outcome": "Elena Rybakina",
"price": 1.87
},
{
"point": 4.5,
"outcome": "Tatjana Maria",
"price": 1.98
},
{
"point": -4.5,
"outcome": "Elena Rybakina",
"price": 1.84
},
{
"point": 4.5,
"outcome": "Tatjana Maria",
"price": 2
},
{
"point": -4.5,
"outcome": "Elena Rybakina",
"price": 1.77
},
{
"point": 4.5,
"outcome": "Tatjana Maria",
"price": 2
},
{
"point": -4.5,
"outcome": "Elena Rybakina",
"price": 1.77
},
{
"point": 4.5,
"outcome": "Tatjana Maria",
"price": 1.87
},
{
"point": -4.5,
"outcome": "Elena Rybakina",
"price": 1.66
},
{
"point": 4.5,
"outcome": "Tatjana Maria",
"price": 2
},
{
"point": -4.5,
"outcome": "Elena Rybakina",
"price": 1.77
},
{
"point": 4.5,
"outcome": "Tatjana Maria",
"price": 2
},
{
"point": -4.5,
"outcome": "Elena Rybakina",
"price": 1.77
}
],
"h2h": [
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.45
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.21
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.27
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.23
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.27
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.23
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.5
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.2
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.25
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.21
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.2
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.2
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.2
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.2
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.54
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.23
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.25
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.24
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.3
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.18
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.22
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.23
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.6
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.23
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.3
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.21
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.42
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.22
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.2
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.33
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.2
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.2
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.21
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.2
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.22
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.5
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.17
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.7
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.2
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.3
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.18
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.35
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.22
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.3
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.21
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.4
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.21
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.3
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.21
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.35
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.22
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.2
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.22
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.35
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.22
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.3
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.21
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.1
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.19
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.2
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.21
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.35
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.22
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.35
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.22
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.35
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.22
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.7
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.24
},
{
"point": null,
"outcome": "Tatjana Maria",
"price": 4.1
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.2
}
],
"h2h_lay": [
{
"point": null,
"outcome": "Tatjana Maria",
"price": 5.1
},
{
"point": null,
"outcome": "Elena Rybakina",
"price": 1.27
}
]
},
"note": "Bookmaker consensus odds at the moment of the call. Frozen here so settlement grades against the same line."
},
"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.
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Bookmaker odds
42 books · sharp books pinned · best price highlighted
| Book | Elena Rybakina | Draw | Tatjana Maria |
|---|---|---|---|
| Pinnacle | 1.23 | — | 4.54 |
| Draftkings | 1.23 | — | 4.22 |
| Fanduel | 1.20 | — | 4.70 |
| Betmgm | 1.21 | — | 4.25 |
| William Hill | 1.22 | — | 4.20 |
| Betfair Exchange UK | 1.24 | — | 4.70 |
| Betfair Exchange EU | 1.24 | — | 4.70 |
| Betanysports | 1.21 | — | 4.45 |
| Betfair UK | 1.20 | — | 4.50 |
| Betfred | 1.20 | — | 4.33 |
| BetOnline | 1.23 | — | 4.27 |
| Betrivers | 1.22 | — | 4.35 |
| Betsson | 1.21 | — | 4.30 |
| Betvictor | 1.20 | — | 4.00 |
| Betway | 1.22 | — | 4.25 |
| Bovada | 1.24 | — | 4.25 |
| Casumo | 1.22 | — | 4.35 |
| Coral | 1.20 | — | 4.20 |
| Everygame | 1.18 | — | 4.30 |
| Fanatics | 1.21 | — | 4.40 |
| Grosvenor | 1.22 | — | 4.35 |
| Ladbrokes | 1.20 | — | 4.20 |
| Leovegas | 1.22 | — | 4.35 |
| Leovegas Se | 1.22 | — | 4.35 |
| Livescorebet | 1.21 | — | 4.20 |
| LowVig | 1.23 | — | 4.27 |
| Matchbook | 1.24 | — | 4.70 |
| Nordicbet | 1.21 | — | 4.30 |
| Onexbet | 1.22 | — | 4.42 |
| Paddy Power | 1.17 | — | 4.50 |
| Pmu | 1.19 | — | 4.10 |
| Skybet | 1.20 | — | 4.33 |
| Smarkets | 1.23 | — | 4.80 |
| Sport888 | 1.22 | — | 4.20 |
| Tipico | 1.18 | — | 4.30 |
| Unibet | 1.20 | — | 4.10 |
| Unibet Nl | 1.22 | — | 4.35 |
| Unibet Se | 1.22 | — | 4.35 |
| Unibet | 1.21 | — | 4.30 |
| Virginbet | 1.21 | — | 4.20 |
| Winamax | 1.23 | — | 4.60 |
| Winamax | 1.21 | — | 4.30 |
| Book | Line | Over | Under |
|---|---|---|---|
| Pinnacle | 20.5 | 1.93 | 1.92 |
| Betanysports | 20.5 | 1.87 | 1.87 |
| BetOnline | 20.5 | 1.91 | 1.91 |
| Betrivers | 20.5 | 1.91 | 1.85 |
| Bovada | 20.5 | 1.87 | 1.87 |
| Casumo | 20.5 | 1.91 | 1.85 |
| Grosvenor | 20.5 | 1.91 | 1.85 |
| LowVig | 20.5 | 1.91 | 1.91 |
| Matchbook | 20.5 | 1.78 | 1.83 |
| Nordicbet | 20.5 | 1.88 | 1.82 |
| Onexbet | 20.5 | 1.91 | 1.91 |
| Pmu | 20.5 | 1.79 | 1.73 |
| Unibet Nl | 20.5 | 1.91 | 1.85 |
| Book | Elena Rybakina | Tatjana Maria |
|---|---|---|
| Pinnacle | -4.5 @ 1.93 | +4.5 @ 1.93 |
| Betanysports | -4.5 @ 1.83 | +4.5 @ 1.91 |
| BetOnline | -4.5 @ 1.83 | +4.5 @ 2.00 |
| Betrivers | -4.5 @ 1.77 | +4.5 @ 2.00 |
| Bovada | -4.5 @ 1.87 | +4.5 @ 1.87 |
| Casumo | -4.5 @ 1.77 | +4.5 @ 2.00 |
| Grosvenor | -4.5 @ 1.77 | +4.5 @ 2.00 |
| LowVig | -4.5 @ 1.83 | +4.5 @ 2.00 |
| Matchbook | -4.5 @ 1.73 | +4.5 @ 1.89 |
| Onexbet | -4.5 @ 1.84 | +4.5 @ 1.98 |
| Pmu | -4.5 @ 1.66 | +4.5 @ 1.87 |
| Unibet Nl | -4.5 @ 1.77 | +4.5 @ 2.00 |
Line movement (h2h)
Each line = one bookmaker · sharp books pinned first
Pinnacle
Betanysports
Betfair Ex
Betfair Ex
Betfair Sb
Betfred
Betmgm
Betonlineag
Betrivers
Betsson
Betvictor
Betway
Bovada
Casumo
Coral
Draftkings
Everygame
Fanatics
Fanduel
Grosvenor
Ladbrokes
Leovegas
Leovegas Se
Livescorebet
Lowvig
Matchbook
Nordicbet
Onexbet
Paddypower
Pmu
Skybet
Smarkets
Sport888
Tipico
Unibet
Unibet Nl
Unibet Se
Unibet
Virginbet
Williamhill
Winamax
Winamax
Elena Rybakina Tatjana Maria
Results settle automatically once the final score lands. Picks are permanent — no hindsight edits.