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Yamanaka vs Petrov

Sports Β· Kalshi Β· Called YES, verified WIN Β· Aug 5, 2026
View the original Kalshi market →
Verified Outcome
WIN
PillarLab called Taiyo Yamanaka to win (YES @ 60%).
Result: Taiyo Yamanaka won. The call was correct.
Analyzed: Aug 5, 2026, 1:53 AM UTC
Market resolved: Aug 6, 2026, 9:04 AM UTC
Called 31h before resolution. The call was made before the outcome was known.

https://kalshi.com/markets/kxitfmatch/itf-mens-match/kxitfmatch-26aug05yampet

PillarLab
πŸ“‘ Fetching Kalshi data...
PillarLab
βœ… Got data from Kalshi API!0.6s
PillarLab
πŸ” Step 1: Detecting market type and category...
PillarLab
βœ… Category: ⚽ SPORTS βœ… Type: BINARY πŸ“Š Market: Yamanaka vs Petrov πŸ“… Date: 2026-08-05T11:00:00.000Z πŸ’° Volume: $13 Current Odds: β€’ Taiyo Yamanaka: 60% β€’ Sergey Petrov: 41%10.4s
PillarLab
⏳ Step 2: Gathering intelligence (parallel)...
PillarLab
βœ… Intelligence gathered: Vegas Lines Β· Injury Report Β· Team Stats Β· Reddit Sentiment Β· Situational Factors Β· PillarScore Β· Line Movement Β· Candidate Dossiers (case for + case against, every candidate β‰₯2%)20.4s
PillarLab
🧠 Step 3: Deep Analysing across all 9 pillars β€” hang tight, ~20s...
PillarLab

πŸ“Š Market Summary

⚽ Yamanaka vs Petrov

Team/PlayerCurrent Odds
Taiyo Yamanaka60%
Sergey Petrov41%

2 options total

PillarLab

🎯 Best Trade

  • Action: Taiyo Yamanaka β€” YES @ 60%

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

  • Why β€” the case against Sergey Petrov:

  • No recent match log or scorelines surfaced, so the market has no form evidence to price him above 41%.
  • Only an ITF ranking page confirms he is an active player, not that he is in form.
  • Lack of discoverable results is itself a risk the market has already priced.
PillarLab

πŸ“ˆ Where the Market Stands

OptionMarketRead
Taiyo Yamanaka60%βšͺ FAIR
Sergey Petrov41%βšͺ FAIR

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 reads Taiyo Yamanaka as the 60% favorite β€” no external bookmaker line is published for this ITF-level fixture, so the market's own pricing is the only reference.

πŸ“ˆ 2. PillarScore

Yamanaka's recency-weighted 61.7 comes from a mixed 7W-8L last-15 log with recent wins over Charlton, Karki, Kumasaka, Kothapalli and Genov but straight-sets losses to Jasika and losses to Bouzige/Kim, while Petrov has no logged recent games at all.

πŸ₯ 3. Injury Report

No injury or fitness reports surfaced for either Taiyo Yamanaka or Sergey Petrov, so neither side carries a documented availability disqualifier.

πŸ“± 4. Reddit Sentiment

No Reddit thread or consensus pick exists for this specific ITF match β€” only generic ITF betting chatter that carries no directional signal.

πŸ”’ 5. Team Stats & Form

Yamanaka's most recent verified results are a 2-1 win over Joshua Charlton (2026-05-06) and a 2-1 win over Ronit Karki (2026-05-18), but the same period includes a 0-2 loss to Oscar Jasika and a 1-2 loss to M. Bouzige; no Petrov 2026 match results surfaced.

🌀️ 6. Situational Factors

Venue, surface, draw round and rest/travel details are unconfirmed for this ITF fixture; Yamanaka's greater search visibility is a coverage artifact, not a proven on-court situational edge.

πŸ”€ 7. Line Movement

No opening/current odds pair is published for this exact market, so no line-movement or sharp-money signal exists; the visible 60/41 split shows no drift.

⏰ 8. Time Decay

LOW - no pending injury, withdrawal or draw news is scheduled; the only repricing catalyst would be a fresh Petrov match log surfacing, which is not public.

⚑ 9. Contrarian Check

The only contrarian case for Petrov is evidentiary absence β€” he is an active ITF player with a ranking page, but with no match log there is no factual basis to support backing him at 41%.

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