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New York Y vs Philadelphia

Sports Β· Kalshi Β· Called NO, verified LOSS Β· Jul 24, 2026
View the original Kalshi market →
Verified Outcome
LOSS
PillarLab called New York Y will NOT win (NO @ 45%).
Result: New York Y won. The call was wrong.
Analyzed: Jul 24, 2026, 3:15 PM UTC
Market resolved: Jul 25, 2026, 1:27 AM UTC
Called 10h before resolution. The call was made before the outcome was known.

https://kalshi.com/markets/kxmlbgame/professional-baseball-game/KXMLBGAME-26JUL241845NYYPHI?utm_source=kalshiapp_eventpage&referral=2a38f0ff-1533-42c5-ac0f-066efa9fde4b

PillarLab
πŸ“‘ Fetching Kalshi data...
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βœ… Got data from Kalshi API!0.5s
PillarLab
πŸ” Step 1: Detecting market type and category...
PillarLab
βœ… Category: ⚽ SPORTS βœ… Type: BINARY πŸ“Š Market: New York Y vs Philadelphia πŸ“… Date: 2026-07-24T22:45:00.000Z πŸ’° Volume: $158,578 Current Odds: β€’ Philadelphia: 56% β€’ New York Y: 45%2.9s
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%)23.2s
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🧠 Step 3: Deep Analysing across all 9 pillars β€” hang tight, ~20s...
PillarLab

πŸ“Š Market Summary

⚽ New York Y vs Philadelphia

Team/PlayerCurrent Odds
Philadelphia56%
New York Y45%

2 options total

PillarLab

🎯 Best Trade

  • Action: New York Y β€” NO @ 45%

  • Confidence: 🟑 MEDIUM Β· Uncertainty: LOW

  • Why:

  • Aaron Judge (fractured rib) and Carlos RodΓ³n (elbow inflammation) are both out, severely impacting offense and pitching.
  • Starting pitcher Will Warren lacks Luzardo's recent dominance, and the bullpen has struggled in one-run games (10-14).
  • Despite a 57-45 overall record, recent wins came against weaker opponents (Pirates, Royals, Tigers) and not elite competition.
  • Philadelphia's one-run game prowess suggests they can win tight games, which the Yankees have not done well this season.
PillarLab

πŸ“ˆ Where the Market Stands

OptionMarketRead
Philadelphia56%🟒 FAVORED
New York Y45%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 as a slight favorite at approximately 56%.

πŸ“ˆ 2. PillarScore

Philadelphia's last 14 games include wins over the Dodgers and Rays but also losses to the same teams and a series split with Pittsburgh; their 8-6 record is solid but comes against tougher opponents than New York's 7-3 run against mostly weaker teams.

πŸ₯ 3. Injury Report

Yankees are without Carlos RodΓ³n (elbow inflammation) and Aaron Judge (rib fracture, not yet cleared); Phillies have reliever Trivino and Brad Keller on the IL but those losses are less impactful.

πŸ“± 4. Reddit Sentiment

Reddit threads show routine fan discussion with no strong contrarian consensus or hype for either side.

πŸ”’ 5. Team Stats & Form

Despite a 57-45 record and 7-3 recent form, the Yankees are missing two key players and their starting pitcher (Will Warren) lacks the form of Philadelphia's JesΓΊs Luzardo, who has won each of his last 10 starts.

🌀️ 6. Situational Factors

Game is at Citizens Bank Park, giving Philadelphia home-field advantage; Philadelphia also has a strong 19-7 record in one-run games, while New York is 10-14 in such games.

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

No public handle split data is available for this market.

⏰ 8. Time Decay

LOW - no major injury updates or lineup changes are expected before game time; the market already prices in known absences.

⚑ 9. Contrarian Check

The main contrarian risk is that the Yankees' recent 7-3 run could be a sign of form recovery, but their injuries to Judge and RodΓ³n are hard to overcome and the market's pricing reflects that.

PillarLab

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

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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