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Al-Faisaly vs Al-Kholood

Sports Β· Kalshi Β· Called YES, verified LOSS Β· Oct 15, 2026
View the original Kalshi market →
Verified Outcome
LOSS
PillarLab called Al-Kholood to win (YES @ 42%).
Result: Al-Kholood did not win. The call was wrong.
Analyzed: Oct 15, 2026, 2:10 PM UTC
Market resolved: Oct 15, 2026, 3:45 PM UTC
Called 2h before resolution. The call was made before the outcome was known.

https://kalshi.com/markets/kxsaudiplgame/alfaisaly-vs-alkholood/KXSAUDIPLGAME-26OCT15FAIAKH?utm_source=kalshiapp_eventdetails

PillarLab
πŸ“‘ Fetching Kalshi data...
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βœ… Got data from Kalshi API!0.3s
PillarLab
πŸ” Step 1: Detecting market type and category...
PillarLab
βœ… Category: ⚽ SPORTS βœ… Type: MULTI_CANDIDATE πŸ“Š Market: Al-Faisaly vs Al-Kholood πŸ“… Date: 2026-10-15T16:40:00.000Z πŸ’° Volume: $200,822 Current Odds: β€’ Al-Kholood: 42% β€’ Al-Faisaly: 30% β€’ Tie: 30%1.7s
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%)25.8s
PillarLab
🧠 Step 3: Deep Analysing across all 9 pillars β€” hang tight, ~20s...
PillarLab

πŸ“Š Market Summary

⚽ Al-Faisaly vs Al-Kholood

Team/PlayerCurrent Odds
Al-Kholood42%
Al-Faisaly30%
Tie30%

3 options total

PillarLab

🎯 My Call

Al-Kholood to win

  • Confidence: πŸ”΄ LOW

Al-Faisaly are playing at home and still can't score, so I'm buying Al-Kholood to win.

OptionMy priceMarket
Al-Kholood52Β’42Β’
Al-Faisaly22Β’30Β’
Tie26Β’30Β’

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 Al-Faisaly NO at 70Β’. My fair price is 78Β’, so that's 8Β’ of edge.

Why NO? A draw kills a Al-Kholood YES bet. Al-Faisaly NO pays if Al-Kholood wins AND if it's a draw. Two ways to cash instead of one.

  • How I'd run it: Normal size, since the sourcing is thin and the head-to-head is a blank. I'd add if Al-Kholood's lineup is confirmed clean, and get out if Al-Faisaly's home form turns into a goal-scoring run before kickoff.

Why

  • Al-Faisaly sit 16th on 3 points from 7 league games with no wins, and they average just 0.5 goals a game.
  • Al-Kholood have 12 points from 7 and a 1.71 points-per-game pace, with 3 points per game at home and away.
  • Al-Faisaly have not won any of their 4 home games, which takes the usual home edge off the board.
  • Al-Kholood's 15 goals conceded and 0% clean-sheet rate are why I'm not paying a huge number for them.
  • What kills it: Al-Faisaly grind out a 0-0 or 1-1 because Al-Kholood have never kept a clean sheet and the home side draws a lot.

  • What flips me: Confirmed news that Al-Kholood's main attacking creator is out and Al-Faisaly get a fit scorer back.

PillarLab

πŸ“ˆ Where the Market Stands

OptionMarketRead
Al-Kholood42%βšͺ FAIR
Al-Faisaly30%πŸ”΄ OVERPRICED
Tie30%βšͺ FAIR

Verdicts compare my own read against the market price, 🟒 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 no direct price for this fixture; the only prices in the intelligence are for an adjacent Al-Qadisiyah match, so I am not using them as a reference for this game.

πŸ“ˆ 2. PillarScore

Al-Kholood's recent results (2 wins, 2 draws, 1 loss in their last 5, 12 points from 7) came against mid-table sides, while Al-Faisaly's 3 points from 7 came against a mix of strong and weak opponents: losses to Al-Ittihad, Al-Qadisiyah, NEOM and Al-Hilal, and draws with Al-Ettifaq, Al-Hazm and Al-Fateh. On opponent-adjusted form, Al-Kholood look modestly stronger, which agrees with the market's lean.

πŸ₯ 3. Injury Report

No injury, suspension or lineup information was found for either side, so this pillar neither disqualifies nor adjusts either candidate.

πŸ“± 4. Reddit Sentiment

No Reddit sentiment data was found for this fixture, so there is no crowd hype signal to fade.

🧠 Off the Record

No framework. Just what I actually think.

Nobody on this one has real data for this game. The standings are the only thing I trust, and the rest is borrowed from an Abha preview and an Al-Qadisiyah preview. That's enough for me to have a view, not enough to size it up. The crowd is looking at Al-Faisaly's name and home stadium. The name is the problem. This is a team that has scored 0.5 goals a game and hasn't won at home. Al-Kholood aren't a great side either, they've conceded 15 and never kept a clean sheet. But they're at 12 points against 3, and that gap is the number. The thing I don't trust is the Faisaly 14-match unbeaten streak floating around. It contradicts everything else on the page, so I threw it out. The tie is live because these two draw a lot, so I'm not pretending the draw is dead. I'm buying Al-Kholood at normal size, and I'd rather be right on the standings than right on a stat I can't verify.

πŸ”’ 5. Team Stats & Form

Al-Faisaly are winless in their last 6 to 7, have 0 home wins, average 0.5 goals scored per game and lost 0-2 to NEOM and 2-4 at Al-Hilal, while Al-Kholood conceded 0-5 at home to Al-Qadisiyah and have a 0% clean-sheet rate.

🌀️ 6. Situational Factors

Al-Faisaly are at home, which is a weak venue for them given 0 home wins this season, while Al-Kholood have 25.8 rest days and a home/away points-per-game of 3 in their league run.

πŸ”€ 7. Line Movement

No line movement history was reported for this fixture, so the line-movement pillar is neutral.

⏰ 8. Time Decay

LOW - no lineup or injury news is published yet and the form data comes from adjacent-fixture previews, so there is no identifiable pending news that would shift the price soon.

⚑ 9. Contrarian Check

The main contrarian risk is a draw: Al-Faisaly have drawn 3 of their last 5 and 2 of their last 4 home games, so a 0-0 or 1-1 result is a realistic outcome that would not resolve the Al-Kholood win contract in favour of the trade.

PillarLab

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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
  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

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