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Shokichi Iwata vs Erick Badillo

Sports Β· Kalshi Β· Called NO, verified WIN Β· Jul 16, 2026
View the original Kalshi market →
Verified Outcome
WIN
PillarLab called Erick Badillo will NOT win (NO @ 38%).
Result: Erick Badillo did not win. The call was correct. Final result: Yera won.
Analyzed: Jul 16, 2026, 8:16 PM UTC
Market resolved: Jul 20, 2026, 2:13 PM UTC
Called 90h before resolution. The call was made before the outcome was known.

https://kalshi.com/markets/kxboxing/boxing-match-champion/kxboxing-26jul20iwatabadill

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: Shokichi Iwata vs Erick Badillo πŸ“… Date: 2026-07-20T14:00:00.000Z πŸ’° Volume: $1,853 Current Odds: β€’ Shokichi Iwata: 64% β€’ Erick Badillo: 38%4.7s
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%)11.5s
PillarLab
🧠 Step 3: Deep Analysing across all 9 pillars β€” hang tight, ~20s...
PillarLab

πŸ“Š Market Summary

⚽ Shokichi Iwata vs Erick Badillo

Team/PlayerCurrent Odds
Shokichi Iwata64%
Erick Badillo38%

2 options total

PillarLab

🎯 Best Trade

  • Action: Erick Badillo β€” NO @ 38%

  • Confidence: πŸ”΄ LOW Β· Uncertainty: LOW

  • Why:

  • Mandatory challenger fighting in the champion's home country (Japan vs. Mexico).
  • Must overcome travel and unfamiliar environment.
  • Less proven at the world title level compared to the champion.
PillarLab

πŸ“ˆ Where the Market Stands

OptionMarketRead
Shokichi Iwata64%🟒 FAVORED
Erick Badillo38%πŸ”΄ TRAILING

I price with the market β€” 🟒 favored Β· πŸ”΄ trailing. The analysis below is the why.

PillarLab

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

πŸ“Š 1. Vegas Line

No Vegas line data available, but sportsbooks likely price Iwata as a moderate favorite.

πŸ“ˆ 2. Line Movement

No line movement data; odds appear stable on the prediction market.

πŸ₯ 3. Injury Report

No injuries reported for either fighter; both are expected at full strength.

πŸ“± 4. Reddit Sentiment

No Reddit sentiment data available; crowd bias cannot be assessed.

πŸ”’ 5. Team Stats & Form

No detailed form or stats available; Iwata's champion status and home advantage underpin his higher price.

🌀️ 6. Situational Factors

Badillo fights as the mandatory challenger in Tokyo, traveling from Mexico, giving Iwata a significant home-field advantage.

πŸ’° 7. Handle Split (Public vs Sharp)

No handle split data; public money may lean toward the known champion, but sharp action is unclear.

⏰ 8. Time Decay

LOW - No impending news or injury updates expected before the fight.

⚑ 9. Contrarian Check

Badillo could pull an upset if he lands a knockout, but his price reflects the low probability against a defending champion at home.

PillarLab

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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