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Philadelphia vs Montreal

Sports Β· Kalshi Β· Called YES, verified WIN Β· Sep 5, 2026
View the original Kalshi market →
Verified Outcome
WIN
PillarLab called Philadelphia to win (YES @ 69%).
Result: Philadelphia won. The call was correct. Final result: Philadelphia won.
Analyzed: Sep 5, 2026, 5:38 AM UTC
Market resolved: Sep 6, 2026, 2:04 AM UTC
Called 20h before resolution. The call was made before the outcome was known.

https://kalshi.com/markets/kxmlsgame/philadelphia-vs-montreal/KXMLSGAME-26SEP05PHIMTL?utm_source=kalshiapp_eventdetails

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: MULTI_CANDIDATE πŸ“Š Market: Philadelphia vs Montreal πŸ“… Date: 2026-09-06T02:30:00.000Z πŸ’° Volume: $15,093 Current Odds: β€’ Philadelphia: 69% β€’ Tie: 18% β€’ Montreal: 14%1.0s
PillarLab
⏳ Step 2: Gathering intelligence (parallel)...
PillarLab
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...
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πŸ“Š Market Summary

⚽ Philadelphia vs Montreal

Team/PlayerCurrent Odds
Philadelphia69%
Tie18%
Montreal14%

3 options total

PillarLab

🎯 Best Trade

  • Action: Philadelphia β€” YES @ 69%

  • Confidence: πŸ”΄ LOW Β· Uncertainty: LOW

  • Why: 11 sharp books price Philadelphia between 64 and 67 (DraftKings 65, FanDuel 65, BetMGM 64, Caesars (WH) 66, BetRivers 64, Bovada 67, BetOnline 67, LowVig 67, Fanatics 67, BetUS 67, MyBookie 67). Consensus, vig removed: 66.5%. The market has Philadelphia at 69%. The market is 2.5 points above the books, so you pay a little over fair. Still the right side.

Line move since our first snapshot: Philadelphia 63.6% to 66.5%. Money moved toward Philadelphia.

  • Why Montreal is priced where it is (14%):
  • Montreal conceded seven goals to Inter Miami on Aug 30, exposing severe defensive weaknesses.
  • Lost 7 of their last 10 games, indicating poor recent form.
  • Power rank of 75.3 is lower than Philadelphia's 67.7, suggesting they are the weaker side overall.

πŸ“ What would change this call: if the market drops Philadelphia 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.

BookPhiladelphiaMontrealTie
DraftKings65.4% (-245)15.4% (+500)19.2% (+380)
FanDuel65.3% (-240)15.4% (+500)19.3% (+380)
BetMGM64.4% (-225)16.2% (+475)19.4% (+380)
Caesars (WH)65.6% (-235)15% (+525)19.5% (+380)
BetRivers64.3% (-225)15.5% (+500)20.2% (+360)
Bovada66.7% (-245)14.5% (+550)18.8% (+400)
BetOnline67.3% (-230)14.5% (+565)18.1% (+433)
LowVig67.3% (-230)14.5% (+565)18.1% (+433)
Fanatics66.6% (-240)14.5% (+550)18.9% (+400)
BetUS67.3% (-230)14.5% (+565)18.1% (+433)
MyBookie66.5% (-238)15% (+530)18.5% (+410)
Consensus, vig removed66.5%15%18.9%

11 sportsbooks priced this game. Spread across the top 11 on Philadelphia: 2.9 pts (books agree). Best price: Philadelphia -225 at BetMGM Β· Montreal +565 at BetOnline Β· Tie +433 at BetOnline.

PillarLab

πŸ“ˆ Where the Market Stands

OptionMarketBook ConsensusGapVerdict
Philadelphia69%66.5%+2.5 ptsβšͺ FAIR PRICE
Tie18%18.9%-0.9 ptsβšͺ FAIR PRICE
Montreal14%15%-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 11 sportsbooks, vig removed: Philadelphia 66.5%, Montreal 15%, Tie 18.9%. Spread across the top books on Philadelphia: 2.9 pts (books agree).

πŸ“ˆ 2. Form & Head-to-Head

Philadelphia is unbeaten since the World Cup break (4W-2D), while Montreal has lost 7 of their last 10, including a 1-7 defeat at Inter Miami on Aug 30.

πŸ₯ 3. Injury Report

No injury or suspension information is publicly available for either side for this fixture.

🧾 4. Starters & Lineups

No confirmed starting lineups have been announced for this match.

πŸ“° 5. Recent News (48h)

Nothing material in the last 48 hours.

🌀️ 6. Situational Factors

Philadelphia hosts Montreal; no travel or rest concerns noted.

πŸ”€ 7. Line Movement

Since our first snapshot (2026-08-23 14:05 UTC): Philadelphia 63.6% to 66.5%, Montreal 16.5% to 15%, Tie 19.9% to 18.9%. Money moved toward Philadelphia.

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

LOW - No late injury or lineup news dated after the last line move is present in the intelligence.

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

Montreal's price reflects a defense that conceded seven goals to Inter Miami on Aug 30 and has lost 7 of its last 10, while Philadelphia's post-break unbeaten run and home advantage make an upset unlikely.

PillarLab

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

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PillarLab AI is an AI prediction-market analyzer that runs a 9-pillar analysis on Kalshi and Polymarket markets and publishes a public, settlement-verified track record of its decisive calls.

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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.

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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
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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