← Back to Track Record

Dellavedova vs Heck

Sports Β· Kalshi Β· Called NO, verified LOSS Β· Sep 18, 2026
View the original Kalshi market →
Verified Outcome
LOSS
PillarLab called Hunter Heck will NOT win (NO @ 33%).
Result: Hunter Heck won. The call was wrong. Final result: Hunter Heck won.
Analyzed: Sep 18, 2026, 3:00 AM UTC
Market resolved: Sep 18, 2026, 4:47 AM UTC
Called 2h before resolution. The call was made before the outcome was known.

https://kalshi.com/markets/kxatpchallengermatch/dellavedova-vs-heck/KXATPCHALLENGERMATCH-26SEP17DELHEC?utm_source=kalshiapp_eventdetails

PillarLab
πŸ“‘ Fetching Kalshi data...
PillarLab
βœ… Got data from Kalshi API!0.8s
PillarLab
πŸ” Step 1: Detecting market type and category...
PillarLab
βœ… Category: ⚽ SPORTS βœ… Type: BINARY πŸ“Š Market: Dellavedova vs Heck πŸ“… Date: 2026-09-18T06:00:00.000Z πŸ’° Volume: $86,674 Current Odds: β€’ Matthew Dellavedova: 69% β€’ Hunter Heck: 33%1.2s
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%)4.2s
PillarLab
🧠 Step 3: Deep Analysing across all 9 pillars β€” hang tight, ~20s...
PillarLab

πŸ“Š Market Summary

⚽ Dellavedova vs Heck

Team/PlayerCurrent Odds
Matthew Dellavedova69%
Hunter Heck33%

2 options total

PillarLab

🎯 Best Trade

  • Action: Hunter Heck β€” NO @ 33%

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

  • Why:

  • Heck has a clear serving weapon with 17 aces across four matches (4.3 per match) versus Dellavedova's 4 aces (2 per match).
  • The head-to-head is 0-0, so there is no historical edge for Dellavedova, and Heck has a 60% (+7%) prediction trend in his favor.
  • Heck has no listed ranking disadvantage confirmed, and the market's 33% sits below the 38-40% implied by the bookmaker consensus and H2H widget.
PillarLab

πŸ“ˆ Where the Market Stands

OptionMarketRead
Matthew Dellavedova69%πŸ”΄ OVERPRICED
Hunter Heck33%🟒 UNDERPRICED

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 Dellavedova as the favorite at roughly 58-60% implied, with a -225 Set 1 price and -110 on a 2-0 set-betting line, so the 69% prediction-market price sits above the bookmaker consensus.

πŸ“ˆ 2. PillarScore

No last-5/10 form log is published for either player, but the only venue-specific form line available is Dellavedova's 83% win rate in Vietnam (+39% above baseline), which is the strongest recent-form signal in the data and points to him.

πŸ₯ 3. Injury Report

No injury, suspension, or lineup status is reported for either player; the generic 'walkover' mention in one market result does not name a player and cannot be treated as a confirmed absence.

πŸ“± 4. Reddit Sentiment

No Reddit sentiment data is available for this lower-tier ATP Challenger-level matchup, so there is no crowd-hype signal to fade in either direction.

πŸ”’ 5. Team Stats & Form

Dellavedova's first-serve points won (80%) and second-serve edge offset Heck's higher ace count (17 across four matches vs Dellavedova's 4), and Dellavedova's 83% Vietnam win rate is the more meaningful recent form line.

🌀️ 6. Situational Factors

No bracket, rest, travel, or venue-hostility data is provided; the only situational edge is Dellavedova's documented strong record in Vietnam conditions.

πŸ”€ 7. Line Movement

No opening vs current line movement data is present, so there is no steam or reverse-move signal to read; the current prices show no visible drift.

⏰ 8. Time Decay

LOW - no pending injury news, lineup announcement, or time-decay catalyst is identified for this match, so the price is unlikely to be moved by fresh information before the event.

⚑ 9. Contrarian Check

The main contrarian risk is that Heck's superior ace count (4.3 per match vs 2.0) and the 0-0 head-to-head mean the market may be over-weighting Dellavedova's ranking and Vietnam form against a live underdog with a real serving weapon.

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