← Back to Track Record

San Francisco vs Los Angeles D

Sports Β· Kalshi Β· Called YES, verified WIN Β· Sep 19, 2026
View the original Kalshi market →
Verified Outcome
WIN
PillarLab called Los Angeles D to win (YES @ 74%).
Result: Los Angeles D won. The call was correct. Final result: Los Angeles D won.
Analyzed: Sep 19, 2026, 2:01 AM UTC
Market resolved: Sep 19, 2026, 5:05 AM UTC
Called 3h before resolution. The call was made before the outcome was known.

https://kalshi.com/markets/kxmlbgame/professional-baseball-game/kxmlbgame-26sep182215sflad

PillarLab
πŸ“‘ Fetching Kalshi data...
PillarLab
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: San Francisco vs Los Angeles D πŸ“… Date: 2026-09-19T02:15:00.000Z πŸ’° Volume: $350,537 Current Odds: β€’ Los Angeles D: 74% β€’ San Francisco: 27%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%)6.8s
PillarLab
🧠 Step 3: Deep Analysing across all 9 pillars β€” hang tight, ~20s...
PillarLab

πŸ“Š Market Summary

⚽ San Francisco vs Los Angeles D

Team/PlayerCurrent Odds
Los Angeles D74%
San Francisco27%

2 options total

PillarLab

🎯 Best Trade

  • Action: Los Angeles D β€” YES @ 74%

  • Confidence: 🟑 MEDIUM Β· Uncertainty: LOW

  • Why: 25 sharp books price Los Angeles D between 72 and 74 (Pinnacle 73, DraftKings 73, FanDuel 73, BetMGM 74, Caesars (WH) 73, Bet365 72, Circa 73, BetRivers 73, BetOnline 73, LowVig 73, Fanatics 73, Coolbet 72, 1xBet 72, Winamax FR 72, kalshi 73, hardrockbet 73, betano_br 72, sbobet 72, paddypower 73, polymarket 73, betfair_ex 74, novig 74, dafabet 72, superbet 72, betvictor 72). Consensus, vig removed: 72.8%. The market has Los Angeles D at 74%. That is the fair price. No discount, but the side is clear.

Line move since our first snapshot: Los Angeles D 57.5% to 72.8%. Money moved toward Los Angeles D.

  • Why San Francisco is priced where it is (27%):
  • San Francisco sits at 64-89, a .418 win rate well below the 27% implied price.
  • The Giants are just 28-50 in the referenced split, a .359 win rate that explains the low price.
  • Los Angeles D is 66-23 when recording eight-plus hits, a dominant mark that limits the Giants' path.

πŸ“ What would change this call: if the market drops Los Angeles D 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.

BookLos Angeles DSan Francisco
Pinnacle73.1% (-297)26.9% (+263)
DraftKings72.9% (-323)27.1% (+253)
FanDuel72.6% (-310)27.4% (+250)
BetMGM73.5% (-333)26.5% (+260)
Caesars (WH)72.8% (-323)27.2% (+250)
Bet36572.3% (-312)27.7% (+245)
Circa72.9% (-294)27.1% (+261)
BetRivers72.9% (-312)27.1% (+255)
BetOnline73.3% (-303)26.7% (+265)
LowVig73.3% (-303)26.7% (+265)
Fanatics72.8% (-323)27.2% (+250)
Coolbet72.1% (-312)27.9% (+242)
1xBet72.4% (-323)27.6% (+244)
Winamax FR71.6% (-323)28.4% (+230)
kalshi73.3% (-286)26.7% (+270)
hardrockbet72.5% (-303)27.5% (+250)
betano_br72.3% (-312)27.7% (+245)
sbobet71.7% (-345)28.3% (+227)
paddypower72.5% (-345)27.5% (+240)
polymarket73.3% (-285)26.7% (+270)
betfair_ex73.5% (-286)26.5% (+275)
novig73.8% (-294)26.2% (+277)
dafabet71.7% (-345)28.3% (+227)
superbet72.2% (-303)27.8% (+245)
betvictor71.7% (-333)28.3% (+230)
Consensus, vig removed72.8%27.2%

25 sportsbooks priced this game. Spread across the top 25 on Los Angeles D: 1.8 pts (books agree). Best price: Los Angeles D -285 at polymarket Β· San Francisco +277 at novig.

PillarLab

πŸ“ˆ Where the Market Stands

OptionMarketBook ConsensusGapVerdict
Los Angeles D74%72.8%+1.2 ptsβšͺ FAIR PRICE
San Francisco27%27.2%-0.2 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: Los Angeles D 72.8%, San Francisco 27.2%. Pinnacle: Los Angeles D 73.1%, San Francisco 26.9%. Spread across the top books on Los Angeles D: 1.8 pts (books agree).

πŸ“ˆ 2. Form & Head-to-Head

Los Angeles D is 93-60 overall and 47-28 at home, while San Francisco sits at 64-89 and 28-50 in the referenced split, though the Giants enter on a two-game win streak and the Dodgers lost 6-2 to Cincinnati on Sep 17.

πŸ₯ 3. Injury Report

No injury, suspension, or lineup-status information specific to this MLB matchup is publicly available; the only injury items in the results concern other sports and other teams, so no clean bill of health can be confirmed for either side.

🧾 4. Starters & Lineups

No announced starting pitchers or lineups for this game appear in the intelligence, so I cannot say whether that was announced before or after the last line move.

πŸ“° 5. Recent News (48h)

Nothing material in the last 48 hours beyond the Dodgers' Sep 17 loss to Cincinnati and the Giants' two-game win streak.

🌀️ 6. Situational Factors

The game is at Dodger Stadium, giving Los Angeles D a home-venue edge, with no rest, travel, or weather data available.

πŸ”€ 7. Line Movement

Since our first snapshot (2026-09-14 02:05 UTC): Los Angeles D 57.5% to 72.8%, San Francisco 42.5% to 27.2%. Money moved toward Los Angeles D.

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

LOW - no specific, dated item from the last 48 hours (late scratch, starter change, suspension, injury) appears in the intelligence that would postdate the last line move.

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

The main contrarian risk is that the Giants are on a two-game win streak and the Dodgers just lost 6-2 to Cincinnati on Sep 17, delaying their NL West title, so the underdog has live motivation in a rivalry spot.

PillarLab

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

Stop guessing. See the edge.

Paste any Kalshi or Polymarket market. PillarLab runs a full 9-pillar analysis and hands you a Best Trade call in about 30 seconds.

Free to start Β· 10 credits Β· no card

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.

PillarLab AI
PillarLab
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