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Oklahoma vs Michigan

Sports Β· Kalshi Β· Called YES, verified LOSS Β· Sep 7, 2026
View the original Kalshi market →
Verified Outcome
LOSS
PillarLab called Oklahoma to win (YES @ 70%).
Result: Oklahoma did not win. The call was wrong. Final result: Michigan won.
Analyzed: Sep 7, 2026, 6:24 AM UTC
Market resolved: Sep 12, 2026, 7:48 PM UTC
Called 133h before resolution. The call was made before the outcome was known.

https://kalshi.com/markets/kxncaafgame/oklahoma-vs-michigan/KXNCAAFGAME-26SEP12OKLAMICH?utm_source=kalshiapp_eventdetails

PillarLab
πŸ“‘ Fetching Kalshi data...
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βœ… Got data from Kalshi API!0.5s
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πŸ” Step 1: Detecting market type and category...
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βœ… Category: ⚽ SPORTS βœ… Type: MULTI_CANDIDATE πŸ“Š Market: Oklahoma vs Michigan πŸ“… Date: 2026-09-12T19:00:00.000Z πŸ’° Volume: $301,025 Current Odds: β€’ Oklahoma: 70% β€’ Michigan: 32%1.2s
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⏳ Step 2: Gathering intelligence (parallel)...
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βœ… Intelligence gathered: Sportsbook Consensus (50+ books, vig removed) Β· Injury Report Β· Team Stats Β· Candidate Dossiers (case for + case against, every candidate β‰₯2%)11.3s
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🧠 Step 3: Deep Analysing across all 9 pillars β€” hang tight, ~20s...
PillarLab

πŸ“Š Market Summary

⚽ Oklahoma vs Michigan

Team/PlayerCurrent Odds
Oklahoma70%
Michigan32%

2 options total

PillarLab

🎯 Best Trade

  • Action: Oklahoma β€” YES @ 70%

  • Confidence: 🟑 MEDIUM Β· Uncertainty: LOW

  • Why: 8 sharp books price Oklahoma between 68 and 69 (DraftKings 68, FanDuel 70, BetMGM 68, Caesars (WH) 68, BetRivers 68, Bovada 67, Fanatics 68, MyBookie 69). Consensus, vig removed: 68.1%. The market has Oklahoma at 70%. That is the fair price. No discount, but the side is clear.

Line move since our first snapshot: Oklahoma 48.4% to 68.1%. Money moved toward Oklahoma.

  • Why Michigan is priced where it is (32%):
  • Michigan needed a last-second Hail Mary and a controversial replay call to beat Western Michigan, exposing offensive issues.
  • QB Bryce Underwood had an uneven season debut with lingering offensive problems.
  • Michigan has lost 5 of its last 10 road games, averaging 18.9 points scored and 20.2 allowed in that stretch.

πŸ“ What would change this call: if the market drops Oklahoma 5+ points under the books it becomes a HIGH-confidence discount. If the top books split by more than 5 points, or a starter is scratched, it goes to HOLD.

PillarLab

🏦 What the Books Say

Percent is the number the call runs on. American odds in parentheses are the same price, shown the way a sportsbook shows it.

BookOklahomaMichigan
DraftKings67.5% (-238)32.5% (+195)
FanDuel69.6% (-265)30.4% (+215)
BetMGM68.2% (-250)31.8% (+200)
Caesars (WH)68.1% (-245)31.9% (+200)
BetRivers67.8% (-250)32.2% (+195)
Bovada67.4% (-235)32.6% (+195)
Fanatics68.1% (-245)31.9% (+200)
MyBookie69.4% (-280)30.6% (+208)
Consensus, vig removed68.1%31.9%

8 sportsbooks priced this game. Spread across the top 8 on Oklahoma: 1.9 pts (books agree). Best price: Oklahoma -235 at Bovada Β· Michigan +215 at FanDuel.

PillarLab

πŸ“ˆ Where the Market Stands

OptionMarketBook ConsensusGapVerdict
Oklahoma70%68.1%+1.9 ptsβšͺ FAIR PRICE
Michigan32%31.9%+0.1 ptsβšͺ FAIR PRICE

Gap is market minus book consensus. Negative means the market is cheaper than the books, that is the discount we look for. 5 or more points cheaper is where the edge lives. 5 or more points over is overpaying.

PillarLab

πŸ”¬ 9-Pillar Analysis (Sharp Trading Method)

🏦 1. Book Consensus

Consensus of 8 sportsbooks, vig removed: Oklahoma 68.1%, Michigan 31.9%. Spread across the top books on Oklahoma: 1.9 pts (books agree).

πŸ“ˆ 2. Form & Head-to-Head

Oklahoma is 1-0 after a 51-0 shutout of UTEP and carries a 4-game win streak, while Michigan is 1-0 but needed a Hail Mary to escape Western Michigan and has lost 5 of its last 10 road games.

πŸ₯ 3. Injury Report

No injury information is publicly available for either team in the provided intelligence.

🧾 4. Starters & Lineups

No announced starting lineups for this game were found in the intelligence.

πŸ“° 5. Recent News (48h)

Nothing material in the last 48 hours beyond the teams' Week 1 results and the line movement toward Oklahoma.

🌀️ 6. Situational Factors

Michigan is at home in Ann Arbor, while Oklahoma is on the road for the first time this season after a home opener against a weak opponent.

πŸ”€ 7. Line Movement

Since our first snapshot (2026-08-24 08:05 UTC): Oklahoma 48.4% to 68.1%, Michigan 51.6% to 31.9%. Money moved toward Oklahoma.

πŸ•’ 8. What the Books May Not Have Priced

LOW - No late scratches or starter changes are dated after the last line move; the only fresh news is the Week 1 results, which the market has already absorbed.

⚑ 9. Why the Other Side Is Priced Where It Is

Michigan's price reflects a shaky 1-0 start: they needed a controversial Hail Mary to beat Western Michigan, their offense looked disjointed, and they face a rested, higher-ranked Oklahoma team on the road.

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Paste a Kalshi or Polymarket URL β†’ AI fetches real-time API market data β†’ 4–5 parallel intelligence sources β†’ a deep 9-pillar analysis β†’ an actionable prediction with an edge estimate. 5 market categories: Politics, Sports, Weather, Finance and General.

⚽ Sports (9 Pillars)

  1. 1.Vegas Lines β†’ spread, moneyline, totals
  2. 2.Line Movement β†’ sharp money signals
  3. 3.Injury Reports β†’ player status tracking
  4. 4.Reddit Sentiment β†’ r/sportsbook consensus
  5. 5.Team Statistics β†’ form, H2H, splits
  6. 6.Situational Factors β†’ rest, travel, schedule
  7. 7.Handle Splits β†’ public vs sharp money
  8. 8.Time Decay β†’ late line movement
  9. 9.Contrarian Check β†’ fade-the-public value

🌦️ Weather (9 Pillars)

  1. 1.Forecast Consensus β†’ GFS / ECMWF / NWS agreement
  2. 2.Ensemble Spread β†’ GEFS uncertainty range
  3. 3.Forecast Skill Decay β†’ accuracy vs time horizon
  4. 4.Historical Base Rate β†’ NOAA climate frequency
  5. 5.Model Divergence β†’ where models disagree vs market
  6. 6.Micro-Climate Bias β†’ station-specific effects
  7. 7.Storm Track β†’ NHC cone / hurricane tracking
  8. 8.Market Pricing β†’ implied probability vs forecast
  9. 9.Contrarian Check β†’ overshoot / mean-reversion

πŸ’° Finance (9 Pillars)

  1. 1.Technical Analysis β†’ RSI, MACD, support levels
  2. 2.Fundamental Metrics β†’ P/E, revenue, earnings
  3. 3.Smart Money β†’ institutional flows, insider trades
  4. 4.Reddit Sentiment β†’ WSB, r/stocks analysis
  5. 5.Macro Indicators β†’ Fed rates, inflation, GDP
  6. 6.News Catalysts β†’ earnings, product launches
  7. 7.Social Velocity β†’ Twitter momentum tracking
  8. 8.Market Signals β†’ volume, bid-ask analysis
  9. 9.Contrarian Check β†’ overcrowded trade detection

πŸ“° General (9 Pillars)

  1. 1.Base Rate β†’ historical frequency analysis
  2. 2.Official Benchmarks β†’ expert forecasts
  3. 3.Reddit Sentiment β†’ subreddit consensus
  4. 4.Social Velocity β†’ viral momentum tracking
  5. 5.News Recency β†’ 24–72h breaking news
  6. 6.Source Quality β†’ credibility scoring
  7. 7.Time Decay β†’ resolution timeline
  8. 8.Contrarian Check β†’ hidden edge detection

πŸ›οΈ Politics (9 Pillars)

  1. 1.Polls Analysis β†’ polling vs market odds divergence
  2. 2.Economic Impact β†’ GDP, unemployment affecting votes
  3. 3.Approval Ratings β†’ candidate favorability tracking
  4. 4.Cross-Platform Markets β†’ Polymarket vs Kalshi arbitrage
  5. 5.Breaking News β†’ events shifting political odds
  6. 6.Regional Patterns β†’ swing state analysis
  7. 7.Social Sentiment β†’ Reddit, X political trends
  8. 8.Data Uncertainty β†’ confidence intervals
  9. 9.Contrarian Risk β†’ devil's advocate view