Canada vs USA
UKickoff · Fri, Jun 12 · 15:00 GMT+0000
Verifiable brief
Identical prompt sent to every AI · SHA-256 verified
hash:
3dbb35c7c358af34…
- Sport
- Fri, Jun 12 · 15:00 GMT+0000
- Markets
- h2h
- 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.
- You MUST return exactly one prediction object per requested market — the
`predictions` array length MUST equal 1. 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 1, in this order): h2h
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": 3567,
"sport": "cricket",
"venue": null,
"league": "One Day Internationals",
"starts_at": "2026-06-12T14:00:00+00:00",
"starts_at_human": "Fri, 12 Jun 2026 14:00:00 GMT"
},
"teams": {
"away": "USA",
"home": "Canada"
},
"version": "v1",
"built_at": "2026-06-12T03:40:06+00:00",
"market_consensus": {
"h2h": {
"away": 1.41,
"home": 3
},
"note": "Bookmaker consensus odds at the moment of the call. Frozen here so settlement grades against the same line.",
"extra_markets": {
"h2h": [
{
"point": null,
"price": 1.41,
"outcome": "USA"
},
{
"point": null,
"price": 2.9,
"outcome": "Canada"
},
{
"point": null,
"price": 1.4,
"outcome": "USA"
},
{
"point": null,
"price": 2.88,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.37,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.39,
"outcome": "USA"
},
{
"point": null,
"price": 2.76,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.37,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.41,
"outcome": "USA"
},
{
"point": null,
"price": 2.9,
"outcome": "Canada"
},
{
"point": null,
"price": 1.4,
"outcome": "USA"
},
{
"point": null,
"price": 2.88,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.37,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.39,
"outcome": "USA"
},
{
"point": null,
"price": 2.76,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.37,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.41,
"outcome": "USA"
},
{
"point": null,
"price": 2.9,
"outcome": "Canada"
},
{
"point": null,
"price": 1.4,
"outcome": "USA"
},
{
"point": null,
"price": 2.88,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.37,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.39,
"outcome": "USA"
},
{
"point": null,
"price": 2.76,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.37,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.41,
"outcome": "USA"
},
{
"point": null,
"price": 2.9,
"outcome": "Canada"
},
{
"point": null,
"price": 1.4,
"outcome": "USA"
},
{
"point": null,
"price": 2.88,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.37,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.39,
"outcome": "USA"
},
{
"point": null,
"price": 2.76,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.37,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.41,
"outcome": "USA"
},
{
"point": null,
"price": 2.9,
"outcome": "Canada"
},
{
"point": null,
"price": 1.4,
"outcome": "USA"
},
{
"point": null,
"price": 2.88,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.37,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.39,
"outcome": "USA"
},
{
"point": null,
"price": 2.76,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.37,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.41,
"outcome": "USA"
},
{
"point": null,
"price": 2.9,
"outcome": "Canada"
},
{
"point": null,
"price": 1.4,
"outcome": "USA"
},
{
"point": null,
"price": 2.88,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.37,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.39,
"outcome": "USA"
},
{
"point": null,
"price": 2.76,
"outcome": "Canada"
},
{
"point": null,
"price": 1.36,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
},
{
"point": null,
"price": 1.37,
"outcome": "USA"
},
{
"point": null,
"price": 3,
"outcome": "Canada"
}
]
}
},
"markets_requested": [
"h2h"
],
"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.
AI predictions
1 markets · 6 models picked
Who picked what
15 models × 1 markets · click a row to see reasoning
| Model |
Match winner
?
Match winner
Match winner. Pick the team that wins in regular time (or who advances in cup formats).
book: Canada 25% |
|
|---|---|---|
Claude Opus 4.7 FlagshipAnthropic · 4-5 -1.2u |
Flagship picks across 1 markets — unlock with Pro
Get Pro
|
|
|
Claude Opus 4.6 FlagshipAnthropic · 5-5 -0.3u |
Flagship picks across 1 markets — unlock with Pro
Get Pro
|
|
|
Claude Opus 4 FlagshipAnthropic |
Flagship picks across 1 markets — unlock with Pro
Get Pro
|
|
|
Claude Sonnet 4.6 FlagshipAnthropic · 125-128 -87.1u |
Flagship picks across 1 markets — unlock with Pro
Get Pro
|
|
|
Claude Haiku 4.5 Anthropic · 168-149 -107.9u |
72%
USA
~1.41
|
|
|
Match winner
?
Match winner
Match winner. Pick the team that wins in regular time (or who advances in cup formats).
72%
USA USA currently sits at the top of ICC CWC League 2 standings with consistently strong performances, experienced batting leadership from Milin...
Odds: 1.41
Edge: +1.1%
🔍 researched
3 sources cited
|
||
GPT-5 FlagshipOpenai |
Flagship picks across 1 markets — unlock with Pro
Get Pro
|
|
|
GPT-5 Mini Openai · 30-17 +24.4u |
— | |
|
Match winner
?
Match winner
Match winner. Pick the team that wins in regular time (or who advances in cup formats).
No pick on this market. |
||
|
GPT-4o Mini Openai · 34-47 -25.2u |
85%
USA
~1.41
|
|
|
Match winner
?
Match winner
Match winner. Pick the team that wins in regular time (or who advances in cup formats).
85%
USA The USA has a dominant head-to-head record against Canada, winning 9 out of the last 10 encounters. Their recent form includes a victory ove...
Odds: 1.41
Edge: +14.1%
🔍 researched
4 sources cited
|
||
|
o3 FlagshipOpenai |
Flagship picks across 1 markets — unlock with Pro
Get Pro
|
|
Grok 4 Heavy FlagshipXai |
Flagship picks across 1 markets — unlock with Pro
Get Pro
|
|
|
Grok 4 Fast Xai · 112-170 -91.3u |
72%
USA
~1.41
|
|
|
Match winner
?
Match winner
Match winner. Pick the team that wins in regular time (or who advances in cup formats).
72%
USA USA has dominated recent bilateral series and ICC events against Canada and other associates; Canada remains inconsistent with limited depth...
Odds: 1.41
Edge: +1.1%
|
||
Gemini 2.5 Pro FlagshipGoogle · 4-7 -1.8u |
Flagship picks across 1 markets — unlock with Pro
Get Pro
|
|
|
Gemini 2.5 Flash Google · 135-151 -121.4u |
75%
USA
~1.41
|
|
|
Match winner
?
Match winner
Match winner. Pick the team that wins in regular time (or who advances in cup formats).
75%
USA USA has a dominant head-to-head record against Canada in One Day Internationals, winning 4 out of 5 encounters, often by significant margins...
Odds: 1.41
Edge: +4.1%
9 sources cited
|
||
|
Gemini 2.5 Flash-Lite Google · 65-141 -96.1u |
75%
USA
~1.41
|
|
|
Match winner
?
Match winner
Match winner. Pick the team that wins in regular time (or who advances in cup formats).
75%
USA The USA holds a significant advantage in head-to-head ODI encounters against Canada, winning 4 out of 5 matches. Recent form also favors the...
Odds: 1.41
Edge: +4.1%
9 sources cited
|
||
DeepSeek V3 Deepseek · 136-147 -106.2u |
75%
USA
~1.41
|
|
|
Match winner
?
Match winner
Match winner. Pick the team that wins in regular time (or who advances in cup formats).
75%
USA USA has a stronger recent record in ODIs, winning 4 of last 5 matches including a series win over Bangladesh. Canada has struggled, losing l...
Odds: 1.41
Edge: +4.1%
|
||
|
Consensus |
USA 6/6 |
|
|
Bookmaker line |
Canada 25% |
|
Ask the AIs · Post-match analysis
Reverse-engineer the match
Ask any AI to explain what happened or grade the consensus call.
Sign in to ask the AIs about this match. Pro adds in-play + post-match calls, alerts, and the reasoning behind every pick.
Bookmaker odds
10 books · sharp books pinned · best price highlighted
| Book | Canada | Draw | USA |
|---|---|---|---|
| Draftkings ↗ | 3.05 | — | 1.38 |
| Boylesports | 2.88 | — | 1.40 |
| Casumo | 4.00 | — | 1.23 |
| Grosvenor | 3.95 | — | 1.22 |
| Leovegas | 3.85 | — | 1.20 |
| Leovegas Se | 3.85 | — | 1.19 |
| Livescorebet | 1.45 | — | 2.55 |
| Marathonbet | 2.76 | — | 1.39 |
| Unibet Se | 4.00 | — | 1.23 |
| Virginbet | 1.10 | — | 6.10 |
| Book | Line | Over | Under |
|---|
| Book | Canada | USA |
|---|
Line movement (h2h)
Each line = one bookmaker · sharp books pinned first
Canada USA
Research trail
What each AI looked up before picking
-
0 tool calls · 9 sources
9 citations captured — unlock with Pro
-
0 tool calls · 9 sources
9 citations captured — unlock with Pro
-
1 tool call · 4 sources
4 citations captured — unlock with Pro
-
0 tool calls · 0 sources
No live web access — picked from training-data knowledge.
-
4 tool calls · 3 sources
3 citations captured — unlock with Pro
-
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.
Get the AI consensus before kickoff
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