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New York Yankees vs. Philadelphia Phillies

Sports Β· Polymarket Β· Called NO, verified WIN Β· Jul 26, 2026
View the original Polymarket market →
Verified Outcome
WIN
PillarLab called New York Yankees will NOT win (NO @ 34.5%).
Result: New York Yankees did not win. The call was correct.
Analyzed: Jul 26, 2026, 11:02 PM UTC
Market resolved: Jul 27, 2026, 2:42 AM UTC
Called 4h before resolution. The call was made before the outcome was known.

https://polymarket.com/sports/mlb/mlb-nyy-phi-2026-07-26

PillarLab
πŸ“‘ Fetching Polymarket data...
PillarLab
βœ… Got data from Polymarket API!0.8s
PillarLab
πŸ” Step 1: Detecting market type and category...
PillarLab
βœ… Category: ⚽ SPORTS βœ… Type: BINARY πŸ“Š Market: New York Yankees vs. Philadelphia Phillies πŸ“… Date: 2026-08-02T23:20:00Z πŸ’° Volume: $1,337,414 Current Odds: β€’ Philadelphia Phillies: 65.5% β€’ New York Yankees: 34.5%2.6s
PillarLab
⏳ Step 2: Gathering intelligence (parallel)...
PillarLab
βœ… Intelligence gathered: Vegas Lines Β· Injury Report Β· Team Stats Β· Reddit Sentiment Β· Situational Factors Β· PillarScore Β· Handle Split (Public vs Sharp) Β· Candidate Dossiers (case for + case against, every candidate β‰₯2%)23.4s
PillarLab
🧠 Step 3: Deep Analysing across all 9 pillars β€” hang tight, ~20s...
PillarLab

πŸ“Š Market Summary

⚽ New York Yankees vs. Philadelphia Phillies

Team/PlayerCurrent Odds
Philadelphia Phillies65.5%
New York Yankees34.5%

2 options total

PillarLab

🎯 Best Trade

  • Action: New York Yankees β€” NO @ 34.5%

  • Confidence: 🟑 MEDIUM Β· Uncertainty: LOW

  • Why:

  • Despite a better overall record (59-45) and two consecutive road wins in this series, the market still favors the Phillies
  • Narrow wins (1-0, 3-1) may not be sustainable, and Phillies are expected to bounce back at home
  • No injury advantage to exploit, and public sentiment leans Phillies
PillarLab

πŸ“ˆ Where the Market Stands

OptionMarketRead
Philadelphia Phillies65.5%🟒 FAVORED
New York Yankees34.5%πŸ”΄ TRAILING

I price with the market β€” 🟒 favored Β· πŸ”΄ trailing. The analysis below is the why.

PillarLab

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

πŸ“Š 1. Vegas Line

My Vegas Line has Philadelphia Phillies at 60% implied probability, aligning closely with the prediction market's 65.5%.

πŸ“ˆ 2. PillarScore

The PillarScore sample (2 games per side) is too small for a confident form read, but the known head-to-head in this series shows Yankees won the first two games 1-0 and 3-1, contradicting the generic PillarScore numbers.

πŸ₯ 3. Injury Report

No injury absences reported for either side; neither team has a clear health advantage.

πŸ“± 4. Reddit Sentiment

Reddit game-thread chatter is mixed: some public lean toward the Phillies as favorites, but Yankees fans highlight their two road wins; no overwhelming hype for either side.

πŸ”’ 5. Team Stats & Form

Yankees hold a better overall record (59-45 vs. 56-49) and have won the first two games of this series, but the market still prices the Phillies as strong favorites, suggesting the recent head-to-head is seen as unsustainable.

🌀️ 6. Situational Factors

Phillies have home-field advantage at Citizens Bank Park; both teams are on equal rest with no travel issues, but being at home on a Sunday is a slight edge.

πŸ’° 7. Handle Split (Public vs Sharp)

Public money and handle lean Phillies, and the run-line also draws sharp action on Philadelphia; this aligns with the market price and suggests no contrarian signal.

⏰ 8. Time Decay

LOW - No fresh injury or lineup news appears stale; the market has absorbed the first two games of the series and still prices Phillies as favorites.

⚑ 9. Contrarian Check

Main contrarian risk: Yankees have already won twice on the road in this series and enter with a better overall record; if their pitching holds again, they could complete a sweep, making their 34.5% price potentially undervalued.

PillarLab

⚠️ Disclaimer: AI can make mistakes. This is not financial advice. Do your own research before placing any trades.

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9-Pillar Analysis ~30s

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Paste any market URL for a full 9-pillar analysis: Vegas lines, injury reports, weather forecasts, sentiment, edge vs market, and a Best Trade call.

How it works

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