Football
Second League - Group 3
Final
0–1
SKA Khabarovsk IIvsSalyut-Belgorod
Final0–1
No AI predictions on file.
This match has already kicked off (or finished). Audits can only be requested on future events.
Team news
ProInjuries and confirmed lineups — the same team news the AIs factored into their reads.
Team news is a Pro feature
see exactly who's out and the XIs the AIs reasoned on, before kickoff.
Bookmaker odds
4 books · sharp books pinned · best price highlighted
| Book | SKA Khabarovsk II | Draw | Salyut-Belgorod |
|---|---|---|---|
| 1xbet | — | 3.02 | — |
| Dafabet | — | 3.10 | — |
| Marathonbet | — | 3.02 | — |
| Superbet | — | 3.05 | — |
| Book | Line | Over | Under |
|---|---|---|---|
| 1xbet | — | — | — |
| Marathonbet | — | — | — |
| Superbet | — | — | — |
| Book | SKA Khabarovsk II | Salyut-Belgorod |
|---|---|---|
| 1xbet | — | — |
| Marathonbet | — | — |
Verifiable brief
Identical prompt sent to every AI · SHA-256 verified
hash:
dc70c3a397f5d48c…
- Kickoff
- Sat, Jun 13 · 04:00 GMT+0000
- Markets
- Match winner · Draw no bet · Over / Under 2.5 · Both teams to score · Spread -1 · Asian handicap · Half-time / Full-time · Correct score
- 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 8. 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 8, in this order): h2h | draw_no_bet | totals_2.5 | btts | spreads_-1 | asian_handicap | ht_ft | correct_score
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": "v2",
"event": {
"id": 940,
"sport": "football",
"league": "Second League - Group 3",
"starts_at": "2026-06-13T04:00:00+00:00",
"starts_at_human": "Sat, 13 Jun 2026 04:00:00 GMT",
"venue": null
},
"teams": {
"home": "SKA Khabarovsk II",
"away": "Salyut-Belgorod"
},
"market_consensus": {
"h2h": [],
"extra_markets": {
"h2h": [
{
"point": null,
"outcome": "Away",
"price": 2.27
},
{
"point": null,
"outcome": "Draw",
"price": 3.1
},
{
"point": null,
"outcome": "Home",
"price": 3
},
{
"point": null,
"outcome": "Away",
"price": 1.59
},
{
"point": null,
"outcome": "Home",
"price": 2.07
},
{
"point": null,
"outcome": "Away",
"price": 2.27
},
{
"point": null,
"outcome": "Draw",
"price": 3.05
},
{
"point": null,
"outcome": "Home",
"price": 2.95
},
{
"point": null,
"outcome": "Away",
"price": 2.34
},
{
"point": null,
"outcome": "Draw",
"price": 3.02
},
{
"point": null,
"outcome": "Home",
"price": 2.92
}
],
"totals": [
{
"point": null,
"outcome": "Under 3.5",
"price": 1.47
},
{
"point": null,
"outcome": "Over 3.5",
"price": 2.42
},
{
"point": null,
"outcome": "Under 2.5",
"price": 2.15
},
{
"point": null,
"outcome": "Over 2.5",
"price": 1.61
},
{
"point": null,
"outcome": "Under 1.5",
"price": 4.1
},
{
"point": null,
"outcome": "Over 1.5",
"price": 1.15
},
{
"point": null,
"outcome": "Under 1.25",
"price": 2.41
},
{
"point": null,
"outcome": "Over 1.25",
"price": 1.49
},
{
"point": null,
"outcome": "Under 1.0",
"price": 3.5
},
{
"point": null,
"outcome": "Over 1.0",
"price": 1.23
},
{
"point": null,
"outcome": "Under 0.5",
"price": 4.9
},
{
"point": null,
"outcome": "Over 0.5",
"price": 1.14
},
{
"point": null,
"outcome": "Under 2.5",
"price": 1.25
},
{
"point": null,
"outcome": "Over 2.5",
"price": 3.45
},
{
"point": null,
"outcome": "Under 2.0",
"price": 1.45
},
{
"point": null,
"outcome": "Over 2.0",
"price": 2.44
},
{
"point": null,
"outcome": "Under 1.75",
"price": 1.7
},
{
"point": null,
"outcome": "Over 1.75",
"price": 1.96
},
{
"point": null,
"outcome": "Under 1.5",
"price": 1.95
},
{
"point": null,
"outcome": "Over 1.5",
"price": 1.74
},
{
"point": null,
"outcome": "Under 1.25",
"price": 1.68
},
{
"point": null,
"outcome": "Over 1.25",
"price": 1.99
},
{
"point": null,
"outcome": "Under 1.0",
"price": 2.06
},
{
"point": null,
"outcome": "Over 1.0",
"price": 1.66
},
{
"point": null,
"outcome": "Under 0.75",
"price": 2.49
},
{
"point": null,
"outcome": "Over 0.75",
"price": 1.46
},
{
"point": null,
"outcome": "Under 0.5",
"price": 2.88
},
{
"point": null,
"outcome": "Over 0.5",
"price": 1.33
},
{
"point": null,
"outcome": "Under 2.5",
"price": 1.13
},
{
"point": null,
"outcome": "Over 2.5",
"price": 5
},
{
"point": null,
"outcome": "Under 2.0",
"price": 1.2
},
{
"point": null,
"outcome": "Over 2.0",
"price": 4.05
},
{
"point": null,
"outcome": "Under 1.5",
"price": 1.49
},
{
"point": null,
"outcome": "Over 1.5",
"price": 2.34
},
{
"point": null,
"outcome": "Under 4.0",
"price": 1.23
},
{
"point": null,
"outcome": "Over 4.0",
"price": 3.42
},
{
"point": null,
"outcome": "Under 3.75",
"price": 1.36
},
{
"point": null,
"outcome": "Over 3.75",
"price": 2.7
},
{
"point": null,
"outcome": "Under 3.25",
"price": 1.59
},
{
"point": null,
"outcome": "Over 3.25",
"price": 2.1
},
{
"point": null,
"outcome": "Under 4.5",
"price": 1.16
},
{
"point": null,
"outcome": "Over 4.5",
"price": 4.15
},
{
"point": null,
"outcome": "Under 3.0",
"price": 1.74
},
{
"point": null,
"outcome": "Over 3.0",
"price": 1.89
},
{
"point": null,
"outcome": "Under 1.0",
"price": 7.4
},
{
"point": null,
"outcome": "Over 1.0",
"price": 1.06
},
{
"point": null,
"outcome": "Under 0.5",
"price": 8.5
},
{
"point": null,
"outcome": "Over 0.5",
"price": 1.04
},
{
"point": null,
"outcome": "Under 3.5",
"price": 1.48
},
{
"point": null,
"outcome": "Over 3.5",
"price": 2.33
},
{
"point": null,
"outcome": "Under 2.75",
"price": 1.98
},
{
"point": null,
"outcome": "Over 2.75",
"price": 1.72
},
{
"point": null,
"outcome": "Under 2.5",
"price": 2.19
},
{
"point": null,
"outcome": "Over 2.5",
"price": 1.59
},
{
"point": null,
"outcome": "Under 2.25",
"price": 2.61
},
{
"point": null,
"outcome": "Over 2.25",
"price": 1.42
},
{
"point": null,
"outcome": "Under 2.0",
"price": 3.48
},
{
"point": null,
"outcome": "Over 2.0",
"price": 1.22
},
{
"point": null,
"outcome": "Under 1.75",
"price": 3.92
},
{
"point": null,
"outcome": "Over 1.75",
"price": 1.18
},
{
"point": null,
"outcome": "Under 1.5",
"price": 4.4
},
{
"point": null,
"outcome": "Over 1.5",
"price": 1.14
}
],
"spreads": [
{
"point": null,
"outcome": "Away +1",
"price": 5
},
{
"point": null,
"outcome": "Home +1",
"price": 1.1
},
{
"point": null,
"outcome": "Away +0.25",
"price": 2.09
},
{
"point": null,
"outcome": "Home +0.25",
"price": 1.61
},
{
"point": null,
"outcome": "Away +0",
"price": 1.69
},
{
"point": null,
"outcome": "Home +0",
"price": 1.97
},
{
"point": null,
"outcome": "Away -0.25",
"price": 1.44
},
{
"point": null,
"outcome": "Home -0.25",
"price": 2.47
},
{
"point": null,
"outcome": "Away +1",
"price": 7
},
{
"point": null,
"outcome": "Home +1",
"price": 1.04
},
{
"point": null,
"outcome": "Away +0.25",
"price": 2.34
},
{
"point": null,
"outcome": "Home +0.25",
"price": 1.49
},
{
"point": null,
"outcome": "Away +0",
"price": 1.69
},
{
"point": null,
"outcome": "Home +0",
"price": 1.97
},
{
"point": null,
"outcome": "Away -0.25",
"price": 1.36
},
{
"point": null,
"outcome": "Home -0.25",
"price": 2.75
},
{
"point": null,
"outcome": "Away +2.5",
"price": 8.8
},
{
"point": null,
"outcome": "Home +2.5",
"price": 1.01
},
{
"point": null,
"outcome": "Away +1.5",
"price": 4.3
},
{
"point": null,
"outcome": "Home +1.5",
"price": 1.15
},
{
"point": null,
"outcome": "Away +1.25",
"price": 3.9
},
{
"point": null,
"outcome": "Home +1.25",
"price": 1.18
},
{
"point": null,
"outcome": "Away -1.5",
"price": 1.08
},
{
"point": null,
"outcome": "Home -1.5",
"price": 5.7
},
{
"point": null,
"outcome": "Away +2",
"price": 8
},
{
"point": null,
"outcome": "Home +2",
"price": 1.02
},
{
"point": null,
"outcome": "Away +1",
"price": 3.5
},
{
"point": null,
"outcome": "Home +1",
"price": 1.22
},
{
"point": null,
"outcome": "Away -2",
"price": 1
},
{
"point": null,
"outcome": "Home -2",
"price": 9.1
},
{
"point": null,
"outcome": "Away +0.75",
"price": 2.7
},
{
"point": null,
"outcome": "Home +0.75",
"price": 1.36
},
{
"point": null,
"outcome": "Away +0.25",
"price": 1.96
},
{
"point": null,
"outcome": "Home +0.25",
"price": 1.68
},
{
"point": null,
"outcome": "Away +0",
"price": 1.67
},
{
"point": null,
"outcome": "Home +0",
"price": 2.05
},
{
"point": null,
"outcome": "Away -0.25",
"price": 1.47
},
{
"point": null,
"outcome": "Home -0.25",
"price": 2.46
},
{
"point": null,
"outcome": "Away -0.75",
"price": 1.23
},
{
"point": null,
"outcome": "Home -0.75",
"price": 3.42
},
{
"point": null,
"outcome": "Away -1",
"price": 1.11
},
{
"point": null,
"outcome": "Home -1",
"price": 4.8
},
{
"point": null,
"outcome": "Away +1",
"price": 6.25
}
],
"btts": [
{
"point": null,
"outcome": "No",
"price": 1.45
},
{
"point": null,
"outcome": "Yes",
"price": 2.5
},
{
"point": null,
"outcome": "No",
"price": 1.01
},
{
"point": null,
"outcome": "Yes",
"price": 8.8
}
]
},
"note": "No bookmaker consensus available at build time — predict from public knowledge."
},
"markets_requested": [
"h2h",
"draw_no_bet",
"totals_2.5",
"btts",
"spreads_-1",
"asian_handicap",
"ht_ft",
"correct_score"
],
"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`."
],
"sport_focus": [
"Weight CONFIRMED team news heavily: a missing first-choice striker, creator, or centre-back swings a match more than season-long form.",
"Compare attacking vs defensive quality directly — clean-sheet rate and goals-conceded trend often predict unders/BTTS better than the win line.",
"Set pieces decide tight games: note corner/free-kick threat and aerial mismatches.",
"Account for fixture congestion + likely rotation (midweek European or cup games before this one) and the home/away form split.",
"For outdoor venues, factor heavy rain or strong wind — both suppress goals and favour the under.",
"Tactical style matters: a high-press side vs a possession side, or two defensive setups, shapes the goals expectation."
]
}
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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