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Basketball World Cup
Final 62–82
Madagascar logo

MadagascarvsD.R. Congo

D.R. Congo logo
Chat with the AIs Ask why they picked — live
Final62–82 Locked 28picks · 14 graded
Recap Consensus called it

Madagascar 62–82 D.R. Congo

5 of 7 AIs leaned D.R. Congo — and reality agreed.

AI lean
D.R. Congo 5/7
Correct calls
5/7
Final
62–82

Every pick below was locked before the match and graded automatically against the final score — no hindsight edits.

AI predictions

Ask the AIs

Who picked what

16 models × 4 markets · click a row to see reasoning

Match winner

Consensus
D.R. Congo 5/7
Claude Opus 4.7 Claude Opus 4.7 Pro
Claude Opus 4.6 Claude Opus 4.6 Pro
Claude Opus 4.8 Claude Opus 4.8 Pro
Claude Sonnet 4.6 Claude Sonnet 4.6 Pro
Claude Haiku 4.5 Claude Haiku 4.5 68% D.R. Congo W

D.R. Congo has historically been the stronger basketball nation in central Africa with better international competition experience and deepe...

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GPT-5 GPT-5 Pro
GPT-5 Mini GPT-5 Mini 68% D.R. Congo W

DR Congo arrive as the stronger side on paper — they beat Madagascar 87-79 on Feb 26, 2026 and carried the advantage on the glass and in the...

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🔍 researched 5 sources cited
GPT-4o Mini GPT-4o Mini 75% D.R. Congo W

D.R. Congo has demonstrated superior performance in recent matches, including a victory over Madagascar earlier this year. Madagascar is on...

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🔍 researched 4 sources cited
o4-mini o4-mini Pro
Grok 4.3 Grok 4.3 Pro
Grok 4 Fast Grok 4 Fast 57% Madagascar L

Madagascar hosts and receives the home-court edge in this 2026 World Cup qualifier. D.R. Congo has shown inconsistent road results in recent...

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Gemini 3.1 Pro Gemini 3.1 Pro Pro
Gemini 2.5 Pro Gemini 2.5 Pro Pro
Gemini 2.5 Flash Gemini 2.5 Flash 68% D.R. Congo W

Based on my training data up to my last knowledge update, D.R. Congo generally possesses a stronger basketball program and more experienced...

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Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite 55% D.R. Congo W

Based on my training data, the Democratic Republic of Congo has historically performed better in basketball matchups against Madagascar. Whi...

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DeepSeek V3 DeepSeek V3 60% Madagascar L

Madagascar has home-court advantage and is likely stronger based on historical performance in World Cup qualifiers. D.R. Congo is competitiv...

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Spread

Consensus
D.R. Congo 2/7
Claude Opus 4.7 Claude Opus 4.7 Pro
Claude Opus 4.6 Claude Opus 4.6 Pro
Claude Opus 4.8 Claude Opus 4.8 Pro
Claude Sonnet 4.6 Claude Sonnet 4.6 Pro
Claude Haiku 4.5 Claude Haiku 4.5 65% D.R. Congo -8.5 W

D.R. Congo's historical advantage as a stronger basketball nation should translate to a moderate spread of 6–10 points. The away fixture red...

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GPT-5 GPT-5 Pro
GPT-5 Mini GPT-5 Mini 58% D.R. Congo -4.5 W

DR Congo's roster (pro-level bigs and better rebounding) and the Feb 26 win by 8 points suggest DRC are likely to win by a small-to-medium m...

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🔍 researched 5 sources cited
GPT-4o Mini GPT-4o Mini 70% D.R. Congo W

Given D.R. Congo's recent superior performance and Madagascar's ongoing losing streak, D.R. Congo is likely to cover a -1 point spread, indi...

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🔍 researched 4 sources cited
o4-mini o4-mini Pro
Grok 4.3 Grok 4.3 Pro
Grok 4 Fast Grok 4 Fast 54% Madagascar

Madagascar benefits from venue familiarity and limited rest disparity in July scheduling. Historical qualifier data favors the home side cov...

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Gemini 3.1 Pro Gemini 3.1 Pro Pro
Gemini 2.5 Pro Gemini 2.5 Pro Pro
Gemini 2.5 Flash Gemini 2.5 Flash 65% D.R. Congo -7.5 W

Building on their historical advantage in player talent and program development, D.R. Congo is expected to control the game and secure a com...

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Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite 53% D.R. Congo

Given the slight historical advantage for the DRC in head-to-head matchups, I'll project them to cover a neutral spread. This assumes a rela...

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DeepSeek V3 DeepSeek V3 55% Madagascar -4.5 L

Madagascar's home advantage and likely superior talent should cover a moderate spread. D.R. Congo can keep it close but lacks the offensive...

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Over / Under

Consensus
under 2/7
Claude Opus 4.7 Claude Opus 4.7 Pro
Claude Opus 4.6 Claude Opus 4.6 Pro
Claude Opus 4.8 Claude Opus 4.8 Pro
Claude Sonnet 4.6 Claude Sonnet 4.6 Pro
Claude Haiku 4.5 Claude Haiku 4.5 62% Under 155.5

Both Madagascar and D.R. Congo are lower-tier international basketball teams with slower offensive tempos, limited three-point shooting volu...

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GPT-5 GPT-5 Pro
GPT-5 Mini GPT-5 Mini 60% over 165.5

Their last meeting produced 166 total points (87-79 on Feb 26, 2026), showing both teams can reach mid-to-high 70s; Madagascar's offense pro...

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🔍 researched 5 sources cited
GPT-4o Mini GPT-4o Mini 65% under L

Both teams have struggled offensively in recent games, with Madagascar scoring 74 points against Côte d'Ivoire and 66 against Senegal, and D...

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🔍 researched 4 sources cited
o4-mini o4-mini Pro
Grok 4.3 Grok 4.3 Pro
Grok 4 Fast Grok 4 Fast 52% over

Both sides tend to play at moderate to high pace in African qualifiers. Training data shows totals often exceed 155-160 when travel fatigue...

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Gemini 3.1 Pro Gemini 3.1 Pro Pro
Gemini 2.5 Pro Gemini 2.5 Pro Pro
Gemini 2.5 Flash Gemini 2.5 Flash 58% Under 145.5 W

African national team basketball games, especially involving teams of this tier, often feature a slower pace and less efficient offensive ex...

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Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite 52% over

Without specific scoring data or pace information for these two teams, it's difficult to make a definitive call. However, basketball games o...

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DeepSeek V3 DeepSeek V3 55% under

Both teams are not known for high-paced offensive systems, and World Cup games often feature lower scoring due to defensive intensity and la...

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First half winner

Consensus
D.R. Congo 5/7
Claude Opus 4.7 Claude Opus 4.7 Pro
Claude Opus 4.6 Claude Opus 4.6 Pro
Claude Opus 4.8 Claude Opus 4.8 Pro
Claude Sonnet 4.6 Claude Sonnet 4.6 Pro
Claude Haiku 4.5 Claude Haiku 4.5 66% D.R. Congo

D.R. Congo's edge in roster quality and tournament pedigree carries through the first half. Early-game execution is less affected by fatigue...

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GPT-5 GPT-5 Pro
GPT-5 Mini GPT-5 Mini 62% D.R. Congo

In the Feb 26 meeting DR Congo dictated tempo early and used interior dominance to build a lead; their ability to control pace and rebound g...

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🔍 researched 5 sources cited
GPT-4o Mini GPT-4o Mini 60% D.R. Congo

D.R. Congo's recent performances suggest they are likely to start strong in the first half, potentially leading to a lead at halftime. Madag...

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🔍 researched 4 sources cited
o4-mini o4-mini Pro
Grok 4.3 Grok 4.3 Pro
Grok 4 Fast Grok 4 Fast 53% Madagascar

Home teams typically build small leads by halftime in these environments due to early energy and crowd support. Training data through 2023 s...

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Gemini 3.1 Pro Gemini 3.1 Pro Pro
Gemini 2.5 Pro Gemini 2.5 Pro Pro
Gemini 2.5 Flash Gemini 2.5 Flash 67% D.R. Congo

D.R. Congo's superior talent and experience, as understood from my training data, should allow them to establish an early lead and maintain...

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Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite 51% D.R. Congo

In first-half predictions, it's often wise to lean towards the team with a perceived slight edge, as momentum can build quickly. The DRC's g...

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DeepSeek V3 DeepSeek V3 58% Madagascar

Madagascar tends to start strong at home, building early leads. D.R. Congo may be slower to adjust, giving Madagascar a first-half edge. The...

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Model confidence

Conviction in pick · Match winner
GPT-4o Mini

GPT-4o Mini

D.R. Congo

75
Claude Haiku 4.5

Claude Haiku 4.5

D.R. Congo

68
GPT-5 Mini

GPT-5 Mini

D.R. Congo

68
Gemini 2.5 Flash

Gemini 2.5 Flash

D.R. Congo

68
DeepSeek V3

DeepSeek V3

Madagascar

60
Grok 4 Fast

Grok 4 Fast

Madagascar

57
Gemini 2.5 Flash-Lite

Gemini 2.5 Flash-Lite

D.R. Congo

55

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-5 145–91 · 61%
+67.5u
Claude Opus 4.8
Claude Opus 4.8 154–115 · 57%
-17.4u
GPT-4o Mini
GPT-4o Mini 1056–802 · 57%
-605.9u
GPT-5 Mini
GPT-5 Mini 692–586 · 54%
-365.1u
Gemini 3.1 Pro
Gemini 3.1 Pro 130–112 · 54%
+111.8u
o4-mini
o4-mini 90–78 · 54%
+69.7u
Claude Opus 4.6
Claude Opus 4.6 193–173 · 53%
-47.6u
Grok 4.3
Grok 4.3 132–124 · 52%
+93.6u
Claude Opus 4.7
Claude Opus 4.7 183–176 · 51%
-63.5u
Gemini 2.5 Flash
Gemini 2.5 Flash 1130–1110 · 50%
-924.7u
Grok 4 Fast
Grok 4 Fast 741–743 · 50%
-501.5u
DeepSeek V3
DeepSeek V3 1083–1112 · 49%
-803.4u
Claude Sonnet 4.6
Claude Sonnet 4.6 459–482 · 49%
-323.7u
Gemini 2.5 Flash-Lite
Gemini 2.5 Flash-Lite 876–930 · 49%
-728.8u
Claude Haiku 4.5
Claude Haiku 4.5 1018–1093 · 48%
-930.0u
Gemini 2.5 Pro
Gemini 2.5 Pro 151–179 · 46%
-73.8u

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: 63c076be1e4e3c6b…
Kickoff
Thu, Jul 2 · 15:00 GMT+0000
Markets
Match winner · Over / Under · Spread · First half winner
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 4. 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 4, in this order): h2h | totals | spreads | first_half

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": 9271,
        "sport": "basketball",
        "venue": null,
        "league": "World Cup",
        "starts_at": "2026-07-02T15:00:00+00:00",
        "starts_at_human": "Thu, 02 Jul 2026 15:00:00 GMT"
    },
    "teams": {
        "away": "D.R. Congo",
        "home": "Madagascar"
    },
    "version": "v2",
    "sport_focus": [
        "Pace is the master variable for totals — multiply both teams' possessions-per-game tendencies, not just their points.",
        "Check the injury/rest report first: a star sitting (or load-managed on a back-to-back) reshapes the spread and total.",
        "Weigh offensive vs defensive rating and three-point volume/variance — 3PT-heavy teams have wider outcome distributions.",
        "Bench depth and foul trouble swing close games; note rotation reliability.",
        "Back-to-backs and travel cause real fatigue — flag the schedule spot for each side.",
        "Home-court edge is meaningful but smaller than star availability."
    ],
    "market_consensus": {
        "h2h": [],
        "note": "No bookmaker consensus available at build time — predict from public knowledge.",
        "extra_markets": []
    },
    "markets_requested": [
        "h2h",
        "totals",
        "spreads",
        "first_half"
    ],
    "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

Recent recaps

How the AI lineup did on other recent matches.

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