Jordan Spreadsheet (jordanspreadsheet.org) is an independent research site built around one question: which Jordan rep batch is actually worth buying? We've been tracking community QC data since 2019 — over 1,100 posts tallied, batch by batch and colourway by colourway. The site is operated by APU Research Labs and is not affiliated with Nike, Jordan Brand, or any purchasing agent mentioned here.
The site started because the data was scattered. Batch comparisons lived in Reddit threads that aged out, QC breakdowns sat in Discord servers that closed, and first-time buyers were spending money on batches the community had already flagged. The batch comparison guide and the individual silhouette pages — Jordan 1, Jordan 4, Jordan 11 — exist to put that data in one place that doesn't expire.
The focus is Air Jordan reps across the main silhouettes and the main batch families: OW batch, LJR batch, PS batch, OG batch. We cover batch-specific quality scores by colourway, agent comparisons for buying through CNFans, Kakobuy, Sugargoo, Weidian, and Taobao, plus sizing and QC guidance. The agent comparison page breaks down fees and UI across the main platforms. For buyers who want to go direct, the Weidian guide covers the direct-purchase route.
Content is researched and written independently. We don't accept payments from agents or brands to influence rankings. When LJR batch scores higher than OG batch on Jordan 4, that's because the community QC data says so — not because anyone paid for the position.
APU Research Labs is an independent research operation covering Chinese e-commerce, purchasing agents, and the international rep buyer community. We maintain research sites across multiple segments of the rep and alternative fashion space. Our team monitors batch quality shifts, new factory versions, and community feedback on a rolling basis — pages get updated when the data changes, not on a fixed calendar.
This site may contain referral links to purchasing agents and platforms. These don't affect our editorial assessments. If a batch drops in quality, we update the score regardless of any referral relationship. All batch comparisons reflect independent research based on community QC documentation.
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