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San Diego FC vs Houston

Sports Β· Kalshi Β· Called YES, verified LOSS Β· Oct 15, 2026
View the original Kalshi market →
Verified Outcome
LOSS
PillarLab called Houston to win (YES @ 27%).
Result: Houston did not win. The call was wrong.
Analyzed: Oct 15, 2026, 2:51 AM UTC
Market resolved: Oct 15, 2026, 4:43 AM UTC
Called 2h before resolution. The call was made before the outcome was known.

https://kalshi.com/markets/kxmlsgame/san-diego-fc-vs-houston/KXMLSGAME-26OCT14SDHOU?utm_source=kalshiapp_eventdetails

PillarLab
πŸ“‘ Fetching Kalshi data...
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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: San Diego FC vs Houston πŸ“… Date: 2026-10-15T05:30:00.000Z πŸ’° Volume: $224,691 Current Odds: β€’ San Diego FC: 49% β€’ Houston: 27% β€’ Tie: 24%2.0s
PillarLab
⏳ Step 2: Gathering intelligence (parallel)...
PillarLab
βœ… Intelligence gathered: Team Stats Β· Injury Report Β· Sportsbook Consensus (50+ books, vig removed) Β· Candidate Dossiers (case for + case against, every candidate β‰₯2%)0.0s
PillarLab
🧠 Step 3: Deep Analysing across all 9 pillars β€” hang tight, ~20s...
PillarLab

πŸ“Š Market Summary

⚽ San Diego FC vs Houston

Team/PlayerCurrent Odds
San Diego FC49%
Houston27%
Tie24%

3 options total

PillarLab

🎯 My Call

Houston to win

  • Confidence: 🟑 MEDIUM

San Diego is getting paid for a name it hasn't earned in six games, and Houston is the side that can still win the points that matter.

OptionMy priceMarket
San Diego FC30Β’49Β’
Houston46Β’27Β’
Tie24Β’24Β’

I set my prices from the research alone, before I saw the market. These are pre-game prices. If the game is already live, the score beats my numbers.

  • The trade: Buy San Diego FC NO at 51Β’. My fair price is 70Β’, so that's 19Β’ of edge.

  • How I'd run it: Normal size, since the standings and head-to-head point the same way but the research is thin on injuries and form details. Add if Herrera's fitness is confirmed in the warm-up reports, and get out if Guilherme is listed as unavailable.

Why

  • San Diego has gone winless in six, with four losses, and just took a 4-1 beating from New York Red Bulls, so the form is ugly.
  • Houston sits 5th on 45 points against San Diego's 12th on 32, a 13-point gap that matters when one side is chasing a playoff spot.
  • Houston holds a 2-1-0 edge over San Diego all-time, including the 1-0 win earlier this season, and I trust that small sample more than San Diego's possession stats.
  • HΓ©ctor Herrera is back from suspension to feed Guilherme, who has 14 goals, which gives Houston a real finisher in the box.
  • What kills it: Houston's away form is poor, with one win in their last five road games, and San Diego's home crowd and Dreyer's 11 goals and 13 assists can turn a grind into a home win.

  • What flips me: Confirmation that Guilherme and Herrera are both out, which would leave Houston without its attack and make the tie or a San Diego result much more likely.

PillarLab

πŸ“ˆ Where the Market Stands

OptionMarketBook ConsensusGapVerdict
San Diego FC49%45.9%+3.1 ptsβšͺ FAIR PRICE
Houston27%28.2%-1.2 ptsβšͺ FAIR PRICE
Tie24%25.8%-1.8 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 6 sportsbooks found by live search, vig removed: San Diego FC 45.9%, Houston 28.2%, Tie 25.8%. Spread across the top books on San Diego FC: 2.3 pts (books agree).

πŸ“ˆ 2. Form & Head-to-Head

San Diego FC has not won since August 29 and has lost or drawn its recent matches, including a 4-1 defeat to NY Red Bulls, while Houston is 5th in the West on 45 points but has gone four matches without a win (0-2-2) and lost 2-0 at home to Sporting Kansas City. Houston holds a 2-1-0 all-time regular-season edge, including a 1-0 win earlier this season, and no head-to-head from this season is confirmed beyond that.

πŸ₯ 3. Injury Report

No confirmed injury or suspension report exists for either side in the results, though the candidate dossiers name Houston absences (Lawrence Ennali, Felipe Andrade, goalkeeper Jimmy Maurer with a concussion, and starting keeper Jonathan Bond) that are not verified against an official report.

🧾 4. Starters & Lineups

No announced starting lineups for this match are in the intelligence, so the starting XI cannot be confirmed before kickoff.

🧠 Off the Record

No framework. Just what I actually think.

The crowd is buying San Diego because of the name, the possession numbers and Ingvartsen and Dreyer. That's the trap. Those guys are real, but the team has gone six games without a win and lost 4-1 to New York in its last big outing. Houston is 5th, playing for a playoff spot, and they have the better table position, the better head-to-head and a striker on 14 goals. Their away record is bad and their keeper situation is shaky, and that's why I'm not pricing them as a lock. But I'm not paying for a draw here either. Both sides have reasons to push for three points, and the side that needs points more is Houston. I'm buying Houston at a normal size. If Guilherme or Herrera is out in the final team sheets, I'm getting out fast, because then the attack is gone and this becomes a coin flip with a tie in it.

πŸ“° 5. Recent News (48h)

Nothing material in the last 48 hours is confirmed in the intelligence, though the dossiers note HΓ©ctor Herrera returning from suspension for Houston.

🌀️ 6. Situational Factors

San Diego plays at home at Snapdragon Stadium, while Houston is on the road and has won only once in its last five away matches (1-2-2); rest and travel data are not available.

πŸ”€ 7. Line Movement

Line movement isn't available for this game: the prices came from live web search, not our snapshot feed.

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

LOW - No late scratch or starter change dated after the last price is confirmed, and the only unverified absence items are already reflected in the dossier context rather than a new dated report.

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

Houston's best case is its 5th-place table position, its unbeaten run of 11 of 14 since the break, and a head-to-head edge, which together could outweigh San Diego's home advantage if its recent winless slump is a short dip rather than a real decline.

PillarLab

⚠️ 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

Recent calls from the desk

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