StockX Web Price History Chart

WHAT IT DOES

This tool visualizes StockX price history data for sneakers and collectibles. It scans product pages for historical sales data—sale dates, prices, sizes, and conditions—and displays it as a bar chart with trend indicators. The panel shows average sale price, highest and lowest sale prices, and price volatility. A trend indicator shows the overall price direction (up/down/flat) with percentage change. Sales are displayed in a sortable list showing date, price, size, and condition. Time range filtering (1 month, 3 months, 6 months, all) lets you focus on recent sales, and size filtering helps analyze specific sizes. The chart bars are color-coded—green for above-average prices, yellow for near-average, and red for below-average. Quick export copies all data as CSV to your clipboard.

WHERE IT RUNS

The script activates on StockX pages (stockx.com), including product pages, sneaker listings, and collectible detail pages. It automatically detects historical sales data using multiple extraction strategies that work across different StockX layouts. The panel appears as a draggable overlay that stays accessible as you analyze price history.

HOW TO USE

Navigate to any StockX product page with historical sales data. The panel will appear showing the price history chart and statistics. Select your preferred currency (USD, EUR, GBP) for price display. Use the "Range" dropdown to filter sales by 1 month, 3 months, 6 months, or All. Toggle "Size on/off" to show or hide size information in the sales list. Set the "Refresh (s)" input to control how often the script checks for updates (default 60 seconds). The "Scan" button manually refreshes the data, and "Export CSV" copies all price history data to your clipboard. The chart shows price trends with color-coded bars, and the summary displays sales count, average, highest, lowest, and volatility.

THE TECHNICAL MECHANISM

The script employs a multi-strategy DOM extraction approach for StockX's price history interface. It first attempts structured selectors targeting known class names like .sale-item, .historical-sale, and .price-history-item, then falls back to heuristic detection of sale containers based on content patterns including currency symbols and sale-related keywords. Sale dates are extracted from date patterns with support for multiple formats. Prices are extracted using regex for currency amounts with support for $, €, and £. Sizes are extracted from patterns matching US, UK, or EU size formats. Conditions are detected as "new" or "used" based on text patterns. The time range filtering uses Date comparison with month-based cutoffs. The bar chart uses CSS for rendering with height proportional to price relative to the maximum price. Price volatility is calculated as the standard deviation of sale prices. The trend indicator compares the first and last sale prices in the filtered dataset. The CSV export generates a formatted file with Date, Price, Size, and Condition columns. All settings are persisted using GM_setValue.

THE PANEL

The panel is fully draggable by its header and remembers its position on the page across sessions. It can be collapsed to a small bubble using the minimize button, then restored by clicking the bubble. The panel resizes automatically to fit its content and can be closed with the Escape key or by clicking the close button. The panel's position and state persist globally, so it returns to the same location on subsequent visits.

PLEASE NOTE

Requires the free BotGentz extension to run. StockX may update its site structure, which could affect the script's ability to detect price history data — updates will be released as needed. All price history data is read from the page and displayed locally; nothing is transmitted externally. The script reads data from the visible page and does not access any data beyond what is visibly presented. The script does not modify your StockX account or listings. The time range filtering uses the dates displayed on the page; if dates are not available, all sales are shown. Volatility calculation is based on the standard deviation of prices in the filtered dataset. The CSV export copies data to your clipboard for personal use. This tool is for informational purposes only and is not affiliated with StockX.