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GB Packers vs NY Jets

Sports Β· Kalshi Β· Called YES, verified WIN Β· Sep 18, 2026
View the original Kalshi market →
Verified Outcome
WIN
PillarLab called Green Bay to win (YES @ 63%).
Result: Green Bay won. The call was correct. Final result: Green Bay won.
Analyzed: Sep 18, 2026, 11:37 AM UTC
Market resolved: Sep 20, 2026, 8:39 PM UTC
Called 57h before resolution. The call was made before the outcome was known.

https://kalshi.com/markets/kxnflgame/professional-football-game/kxnflgame-26sep20gbnyj

PillarLab
πŸ“‘ Fetching Kalshi data...
PillarLab
βœ… Got data from Kalshi API!0.4s
PillarLab
πŸ” Step 1: Detecting market type and category...
PillarLab
βœ… Category: ⚽ SPORTS βœ… Type: MULTI_CANDIDATE πŸ“Š Market: GB Packers vs NY Jets πŸ“… Date: 2026-09-20T20:00:00.000Z πŸ’° Volume: $258,971 Current Odds: β€’ Green Bay: 63% β€’ New York J: 39%0.9s
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%)5.4s
PillarLab
🧠 Step 3: Deep Analysing across all 9 pillars β€” hang tight, ~20s...
PillarLab

πŸ“Š Market Summary

⚽ GB Packers vs NY Jets

Team/PlayerCurrent Odds
Green Bay63%
New York J39%

2 options total

PillarLab

🎯 Best Trade

  • Action: Green Bay β€” YES @ 63%

  • Confidence: 🟑 MEDIUM Β· Uncertainty: LOW

  • Why: 25 sharp books price Green Bay between 61 and 64 (Pinnacle 61, DraftKings 64, FanDuel 63, BetMGM 62, Caesars (WH) 62, Bet365 63, Circa 61, BetRivers 64, Bovada 61, BetOnline 61, LowVig 61, Fanatics 62, Betsson 63, 1xBet 63, Winamax FR 62, hardrockbet 62, betano_br 63, paddypower 62, polymarket 61, betfair_sb 62, betfair_ex 62, novig 62, dafabet 63, superbet 63, betvictor 62). Consensus, vig removed: 62%. The market has Green Bay at 63%. That is the fair price. No discount, but the side is clear.

Line move since our first snapshot: Green Bay 68.5% to 62%. Money moved toward New York J.

  • Why New York J is priced where it is (39%):
  • The Jets' injury report names Minkah Fitzpatrick, Joseph Ossai, D'Angelo Ponds, Kene Nwangu, Omar Cooper Jr., David Onyemata, Jarvis Brownlee Jr. and Jamien Sherwood, thinning the roster for this game.
  • Their 23-10 Week 1 win came over Tennessee, and Geno Smith threw zero touchdowns in that game despite an efficient 19-of-24, 215-yard, no-interception line.
  • Green Bay is a 4-point favorite at -210 on the moneyline with a 44.5 total, and the model line is Packers by 3.5, so the Jets remain the clear underdog at home.

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

BookGreen BayNew York J
Pinnacle61% (-169)39% (+149)
DraftKings63.8% (-200)36.2% (+164)
FanDuel63.4% (-194)36.6% (+162)
BetMGM62.2% (-182)37.8% (+155)
Caesars (WH)62% (-182)38% (+153)
Bet36563.1% (-192)36.9% (+160)
Circa61.1% (-169)38.9% (+150)
BetRivers63.7% (-200)36.3% (+163)
Bovada60.6% (-169)39.4% (+145)
BetOnline61.4% (-172)38.6% (+152)
LowVig61.4% (-172)38.6% (+152)
Fanatics61.6% (-179)38.4% (+150)
Betsson62.9% (-196)37.1% (+156)
1xBet63% (-196)37% (+157)
Winamax FR62% (-200)38% (+145)
hardrockbet62.3% (-185)37.7% (+155)
betano_br62.8% (-192)37.2% (+157)
paddypower62% (-189)38% (+150)
polymarket61.3% (-163)38.7% (+156)
betfair_sb62% (-189)38% (+150)
betfair_ex61.6% (-164)38.4% (+158)
novig62.2% (-167)37.8% (+163)
dafabet63% (-192)37% (+159)
superbet63% (-189)37% (+160)
betvictor62% (-200)38% (+145)
Consensus, vig removed62%38%

25 sportsbooks priced this game. Spread across the top 25 on Green Bay: 2.7 pts (books agree). Best price: Green Bay -163 at polymarket Β· New York J +164 at DraftKings.

PillarLab

πŸ“ˆ Where the Market Stands

OptionMarketBook ConsensusGapVerdict
Green Bay63%62%+1 ptsβšͺ FAIR PRICE
New York J39%38%+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 25 sportsbooks, vig removed: Green Bay 62%, New York J 38%. Pinnacle: Green Bay 61%, New York J 39%. Spread across the top books on Green Bay: 2.7 pts (books agree).

πŸ“ˆ 2. Form & Head-to-Head

Green Bay is 0-1 and on a six-game skid dating to last season after blowing a 22-10 lead and conceding 29 straight to Minnesota, while the Jets are 1-0 following a 23-10 win at Tennessee and lead the all-time series 9-5 including a 27-10 win in the most recent meeting.

πŸ₯ 3. Injury Report

The Jets' Week 2 preview lists Minkah Fitzpatrick, Joseph Ossai, D'Angelo Ponds, Kene Nwangu, Omar Cooper Jr., David Onyemata, Jarvis Brownlee Jr. and Jamien Sherwood as injuries heading into this game, while no Packers injuries or suspensions are named anywhere in the results.

🧾 4. Starters & Lineups

No starting lineups or inactives for this game have been announced in the gathered intelligence, and no announcement timing relative to the last line move is available.

πŸ“° 5. Recent News (48h)

Nothing material in the last 48 hours beyond the Week 2 injury preview naming the Jets' eight banged-up players.

🌀️ 6. Situational Factors

The game is at MetLife Stadium, where the Jets get their home opener and could face inclement weather, while Green Bay travels on the road carrying a six-game losing streak.

πŸ”€ 7. Line Movement

Since our first snapshot (2026-09-04 12:05 UTC): Green Bay 68.5% to 62%, New York J 31.5% to 38%. Money moved toward New York J.

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

LOW - the Jets' injury list is a preview-video report rather than a dated post-line-move transaction, and no Packers injury or lineup change has surfaced after the last move.

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

The main contrarian risk is that Green Bay's six-game skid and fourth-quarter collapse against Minnesota are being treated as noise by a price that still leans heavily on the Packers' roster reputation, while the Jets' 1-0 start and home opener are live.

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

#1 AI-Powered Prediction Market Analyzer Tool for Kalshi & Polymarket

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