Home > Adidas Resale Trend Prediction: Data Modeling Approach with Acbuy Spreadsheet

Adidas Resale Trend Prediction: Data Modeling Approach with Acbuy Spreadsheet

2025-07-19
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Balenciaga Triples (7 styles) -0515

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In the competitive world of sneaker reselling, accurate prediction of Adidas' hottest releases is crucial for profitable arbitrage. This article explores how data modeling using the Acbuy spreadsheet

1. Data Collection Framework

The Acbuy system aggregates multiple key indicators:

  • Google Trends search volume for specific Adidas models
  • StockX/GOAT historical price trajectories
  • Social media engagement metrics (reddit mentions, Instagram hashtags)
  • Early-order cancellation rates from select retailers

2. Model Architecture

Three distinct algorithms drive predictions:

Prediction Model Matrix

Model Type Input Layer Success Rate
Random Forest Historical sales + social buzz 82.3%
LSTM Neural Net Time-series price data 78.1%
Bayesian Network Exclusive drop calendar 86.7%

Data normalization follows MandarinWhisper's 5-point scaling system for cross-platform comparison.

3. Real-World Application

Case Study: Ultraboost 5.0 DNA "Uncaged"

August 2023 datasheet showed:

  • 27% search surge 72hr pre-drop
  • Unusually high Pinterest saves/RV conversion
  • 4.2x baseline StockX "want" count

The model recommended buy quantities based on regional trends, resulting in 19-34% profit margins versus average 12% for unpredicted drops.

Optimizing Your Purchases

To implement this prediction model:

  1. Connect Acbuy spreadsheet via Shopify API
  2. Activate "Regional Hype" tracking channels
  3. Set automated alerts for predicted price inflection points
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