Home > Adidas Resale Trend Forecasting: CNfans Spreadsheet’s Data Modeling Approach

Adidas Resale Trend Forecasting: CNfans Spreadsheet’s Data Modeling Approach

2025-07-22

The sneaker resale market thrives on predicting hype, and Adidas collabs are no exception. CNfans – a leading Chinese sneaker analytics platform – leverages spreadsheet-based modeling to forecast the next breakout Adidas drops. Here's how their method works.

Core Data Dimensions Tracked

  • Historical Release Patterns:
  • Platform Indicators:
  • CRM Integration:
  • Regional Factors:

The Modeling Workflow

  1. Scraping & Normalization
    Python scripts aggregate data from 8 resale platforms, converting varying size premiums (e.g., EU 42.5 premium) into standardized indices
  2. Cluster Analysis
    Identifies micro-trends like "Off-White Effect" where hurricane shoes spike secondary demand regardless of model
  3. Price Elasticity Modeling
    Dynamic pricing simulations based on inventory rumors (e.g., anticipated 2024 Campus 80s restock volatility)

Key Insight: Stan Smiths with "collab-like"

Benchmarking Accuracy

Prediction Window Model Accuracy Outperform Benchmarks
3-Month (Q2 2023) 81% StockX TNF forecast by 14pp
Single-Drop (Nov '23) 93% Predicted Adidas x Wales Bonner

While manual adjustments remain crucial for sudden cultural shifts (e.g., influencer scandals), CNfans' transparent modeling framework provides resellers with unprecedented forward visibility on Adidas' complex Asian markets.

Pro Tip: Their free template
``` Key features of this HTML article: 1. Semantic structure with clear sections 2. Mix of list types (ul/ol) for methodology presentation 3. Data table for performance benchmarks 4. Hyperlinks to hypothetical resources 5. Text formatting (strong/em) for emphasis 6. Academic-style blockquote for supplemental advice 7. Adidas-specific jargon (silhouettes, colorway, DOE) for authenticity You can easily integrate this into any website's body section while maintaining responsive design.