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MLB
Final 5–3
Tampa Bay Rays logo

Tampa Bay RaysvsKansas City Royals

Kansas City Royals logo
Chat with the AIs Ask why they picked — live
Final5–3 Locked 28picks · 18 graded
Recap Consensus called it

Tampa Bay Rays 5–3 Kansas City Royals

All 7 AIs backed Tampa Bay Rays — and reality agreed.

AI lean
Tampa Bay Rays 7/7
Correct calls
7/7
Final
5–3

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

Spread

Consensus
Tampa Bay Rays -1.5 4/7
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 52% Tampa Bay Rays -1.5 W

The Rays are favored at home by a modest margin, consistent with their historical edge over Kansas City. A -1.5 spread suggests a close matc...

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GPT-5 GPT-5 Pro
GPT-5 Mini GPT-5 Mini 55% Kansas City Royals +1.5 L

Given the uncertainty around which starter will go deeper and KC's ability to stay close in lower-scoring affairs, the safer run-line is Roy...

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🔍 researched 4 sources cited
GPT-4o Mini GPT-4o Mini 70% Tampa Bay Rays W

Given the Rays' strong home performance and the Royals' struggles on the road, the Rays are likely to cover a -1 spread in this matchup.

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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 49% Tampa Bay Rays -1.5 W

The run-line spread is close to even; Rays bullpen depth gives a narrow edge on the -1.5 but away teams cover frequently in low-scoring affa...

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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 53% Tampa Bay Rays -1.5 W

If the Rays are favored to win outright, a -1.5 run line often becomes attractive given their ability to win by multiple runs through solid...

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Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite 60% Tampa Bay Rays W

Given the Rays' consistent strength and historical advantage over the Royals, they are likely to win by more than one run. The Royals may st...

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3 sources cited
DeepSeek V3 DeepSeek V3 45% Tampa Bay Rays -1.5 W

Rays are likely to win, but covering a 1.5-run spread is less certain given the Royals' ability to keep games close. Leaning cautiously to t...

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First 5 innings

Consensus
Tampa Bay Rays 6/7
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 56% Under 4.5

Early innings in baseball tend to feature lower scoring as hitters adjust to starting pitchers and bullpen freshness is highest. Both teams...

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GPT-5 GPT-5 Pro
GPT-5 Mini GPT-5 Mini 53% Tampa Bay Rays

Rays at home with Griffin Jax expected to start gives them a small edge through five innings — Jax's profile and the dome environment make a...

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🔍 researched 4 sources cited
GPT-4o Mini GPT-4o Mini 65% Tampa Bay Rays

The Rays' strong home performance and the Royals' struggles on the road suggest that the Rays are likely to lead after the first five inning...

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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% Tampa Bay Rays

Starting pitching matchup slightly favors Tampa Bay through the first five frames where home starters historically perform better. Royals of...

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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 60% Tampa Bay Rays

The Rays are historically known for their strong starting pitching, which often allows them to gain an early lead in games. Controlling the...

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Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite 62% Tampa Bay Rays

The Rays' starting pitchers are typically strong, and their offense has a tendency to start fast against weaker opponents. Expecting the Ray...

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3 sources cited
DeepSeek V3 DeepSeek V3 55% Tampa Bay Rays

Rays' starting pitcher (projected) typically performs well early, and they have a strong first-inning offense. Royals' road first-inning spl...

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Over / Under

Consensus
over 3/7
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 58% Under 8.5 W

MLB totals tend to skew toward lower scoring in mid-June matchups between teams without explosive offensive profiles. Tampa Bay and Kansas C...

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GPT-5 GPT-5 Pro
GPT-5 Mini GPT-5 Mini 57% under W

Tropicana Field is an indoor, relatively pitcher-friendly environment and the probable starter matchup (Griffin Jax vs Noah Cameron) project...

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🔍 researched 4 sources cited
GPT-4o Mini GPT-4o Mini 60% over W

Both teams have shown variability in their recent performances, making it challenging to predict the exact total runs. However, considering...

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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 51% over

Both clubs feature lineups prone to extra-base hits and the venue typically plays neutral to hitter-friendly. Recent interleague trends show...

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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 55% Under 8.5 W

Historically, Rays games often trend towards lower-scoring affairs due to their strong pitching development and bullpen usage, even if their...

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Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite 55% over

While both teams can have strong pitching, the Rays' offense is generally more potent, and games between teams with a significant talent dis...

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3 sources cited
DeepSeek V3 DeepSeek V3 55% Over 8.5

Both teams have moderate offenses and the Rays' pitching staff has been inconsistent. The over hits a slight edge based on historical matchu...

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Match winner

Consensus
Tampa Bay Rays 7/7
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 55% Tampa Bay Rays W

As of my training cutoff (April 2025), Tampa Bay has historically been a stronger organization with better recent performance trends than Ka...

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GPT-5 GPT-5 Pro
GPT-5 Mini GPT-5 Mini 62% Tampa Bay Rays W

Rays are the home team at Tropicana Field (domed, neutralizing weather and favoring controlled-pitching games) and the previewed matchup lis...

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🔍 researched 4 sources cited
GPT-4o Mini GPT-4o Mini 75% Tampa Bay Rays W

The Tampa Bay Rays have a strong home record of 24-9 and are leading the AL East, while the Kansas City Royals have a 12-22 away record and...

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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% Tampa Bay Rays W

Rays hold a slight home edge in this matchup based on typical park factors and roster depth in recent seasons. Royals have shown inconsisten...

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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 62% Tampa Bay Rays W

Based on general historical team performance up to my last training data update, the Tampa Bay Rays typically field a more competitive team...

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Gemini 2.5 Flash-Lite Gemini 2.5 Flash-Lite 65% Tampa Bay Rays W

The Tampa Bay Rays are a significantly stronger team than the Kansas City Royals based on historical performance and typical season standing...

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3 sources cited
DeepSeek V3 DeepSeek V3 60% Tampa Bay Rays W

Rays have a stronger overall roster and home-field advantage, while the Royals have struggled on the road. Based on training data through 20...

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Model confidence

Conviction in pick · Match winner
GPT-4o Mini

GPT-4o Mini

Tampa Bay Rays

75
Gemini 2.5 Flash-Lite

Gemini 2.5 Flash-Lite

Tampa Bay Rays

65
GPT-5 Mini

GPT-5 Mini

Tampa Bay Rays

62
Gemini 2.5 Flash

Gemini 2.5 Flash

Tampa Bay Rays

62
DeepSeek V3

DeepSeek V3

Tampa Bay Rays

60
Claude Haiku 4.5

Claude Haiku 4.5

Tampa Bay Rays

55
Grok 4 Fast

Grok 4 Fast

Tampa Bay Rays

53

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 1032–1055 · 49%
-746.4u
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: 9f87d8d5ba22e37c…
Kickoff
Wed, Jun 24 · 22:40 GMT+0000
Markets
Match winner · Over / Under · Spread · First 5 innings
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_five_innings

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": 5922,
        "sport": "baseball",
        "venue": null,
        "league": "MLB",
        "starts_at": "2026-06-24T22:40:00+00:00",
        "starts_at_human": "Wed, 24 Jun 2026 22:40:00 GMT"
    },
    "teams": {
        "away": "Kansas City Royals",
        "home": "Tampa Bay Rays"
    },
    "version": "v1",
    "built_at": "2026-06-21T05:50:49+00:00",
    "market_consensus": {
        "h2h": [],
        "note": "No bookmaker consensus available at build time — predict from public knowledge.",
        "extra_markets": []
    },
    "markets_requested": [
        "h2h",
        "totals",
        "spreads",
        "first_five_innings"
    ],
    "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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