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Los Angeles A vs Baltimore

Sports Β· Kalshi Β· Called YES, verified LOSS Β· Aug 6, 2026
View the original Kalshi market →
Verified Outcome
LOSS
PillarLab called Baltimore to win (YES @ 66%).
Result: Baltimore did not win. The call was wrong.
Analyzed: Aug 6, 2026, 4:19 PM UTC
Market resolved: Aug 6, 2026, 7:37 PM UTC
Called 3h before resolution. The call was made before the outcome was known.

https://kalshi.com/markets/kxmlbgame/los-angeles-a-vs-baltimore/KXMLBGAME-26AUG061235LAABAL?utm_source=kalshiapp_eventdetails

PillarLab
πŸ“‘ Fetching Kalshi data...
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βœ… Got data from Kalshi API!0.8s
PillarLab
πŸ” Step 1: Detecting market type and category...
PillarLab
βœ… Category: ⚽ SPORTS βœ… Type: MULTI_CANDIDATE πŸ“Š Market: Los Angeles A vs Baltimore πŸ“… Date: 2026-08-06T16:35:00.000Z πŸ’° Volume: $2,171,634 Current Odds: β€’ Baltimore: 66% β€’ Los Angeles A: 36%1.5s
PillarLab
⏳ Step 2: Gathering intelligence (parallel)...
PillarLab
βœ… Intelligence gathered: Vegas Lines Β· Injury Report Β· Team Stats Β· Reddit Sentiment Β· Candidate Dossiers (case for + case against, every candidate β‰₯2%)30.8s
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🧠 Step 3: Deep Analysing across all 9 pillars β€” hang tight, ~20s...
PillarLab

πŸ“Š Market Summary

⚽ Los Angeles A vs Baltimore

Team/PlayerCurrent Odds
Baltimore66%
Los Angeles A36%

2 options total

PillarLab

🎯 Best Trade

  • Action: Baltimore β€” YES @ 66%

  • Confidence: 🟑 MEDIUM Β· Uncertainty: MEDIUM

  • Why β€” the case against Los Angeles A:

  • Los Angeles A lost the series opener 1-3 on August 4 despite Grayson Rodriguez's 'best start of the year', showing they cannot convert strong pitching into wins.
  • The Angels are 43-70, 5th in the AL West, a season-long record that reflects a fundamentally weak team.
  • They are on the road in Baltimore, having already lost the first game of the series, and their lineup failed to produce against Cade Povich early.
PillarLab

πŸ“ˆ Where the Market Stands

OptionMarketRead
Baltimore66%🟒 UNDERPRICED
Los Angeles A36%πŸ”΄ OVERPRICED

Verdicts compare my own read against the market price β€” 🟒 UNDERPRICED (market has it too low) Β· πŸ”΄ OVERPRICED (market has it too high). The analysis below is the why.

PillarLab

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

πŸ“Š 1. Vegas Line

My Vegas Line has Baltimore at 58% and Los Angeles A at 46% for the August 5 game, which is close to the prediction market's 66/36 split, though the market prices Baltimore higher.

πŸ“ˆ 2. PillarScore

Baltimore has won the first two games of this series (3-1 and 5-2) and is 17-6 in their last 27 games, while Los Angeles A lost the opener 1-3 and has a 43-70 record, so recent form against real competition favors Baltimore.

πŸ₯ 3. Injury Report

No specific injury information is available for either team in the provided intelligence, so no hard disqualifier can be named.

πŸ“± 4. Reddit Sentiment

Reddit sentiment is sparse and non-committal, with no clear crowd hype for either side, so no over-hyped candidate to fade.

πŸ”’ 5. Team Stats & Form

Los Angeles A's recent results are worse than their 36% price implies: they lost the series opener 1-3 despite a strong start from Grayson Rodriguez, and their 43-70 record shows a season-long struggle.

🌀️ 6. Situational Factors

Los Angeles A is on the road in Baltimore for a three-game series, having already lost the opener, giving them the worse situational path with no home advantage.

πŸ”€ 7. Line Movement

No line movement data is available for this market, so no sharp-money signal can be identified.

⏰ 8. Time Decay

MEDIUM - The market may soon price in Baltimore's series dominance and the Angels' continued struggles, but no pending injury news or lineup announcements are known to trigger a shift.

⚑ 9. Contrarian Check

The main contrarian risk is that Baltimore's roster was weakened at the trade deadline (dealing Adley Rutschman, Taylor Ward, Tyler Wells, Dean Kremer), which could catch up to them, but their recent 17-6 run and series wins mitigate this.

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⚠️ 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