How Fast Do Too Good To Go Bags Sell Out? 2026 Data by City

Some Too Good To Go bags remain bookable long enough for a normal app check. Others appear and disappear before a user can finish checkout. To measure that competition, BagRescue matched the first observed availability for an item and date with its later sold-out timestamp.

The live table reports quartiles, medians, matched-drop counts, and store counts for cities with enough data.

What the median measures

For each matched drop, the timer begins at BagRescue's first availability detection and ends at the observed sold-out time. The city median is the middle duration. The 25th and 75th percentiles show how widely results vary.

This is an estimate. Monitoring may first see a bag after it became available, which makes the measured duration shorter than the complete on-sale period. The methodology caps implausibly long matches and requires at least 20 drops across three stores in a city.

Why city rankings are not store predictions

A city can contain a famous bakery that sells in moments and many slower grocery listings. The merchant, bag type, release time, day, and pickup convenience all influence demand. City medians summarize the observed mix; they do not predict one listing.

For store-level preparation, read when Too Good To Go bags drop and monitor recent behavior rather than relying on an old screenshot or social post.

What to do in a fast city

Keep payment details current, favorite only realistic stores, and know the pickup window before the expected release. Removing decision time is usually more useful than frantic refreshing.

An alert may still leave a checkout race. A TGTG scanner or auto-reserve assistant can watch in the background, but it cannot guarantee inventory. Read the fairness and automation discussion before deciding whether the tradeoff suits you.

What to do in a slower city

Do not assume every bag is urgent. Compare merchant ratings, pickup distance, and likely category. A few extra minutes can prevent an unwanted reservation. Use price quartiles by store type for cost context.

Even in a slower city, one high-demand store may sell quickly. Build a backup list and avoid planning an essential meal around uncertain inventory.

Study limitations

The dataset covers US activity observed by BagRescue in the latest rolling 90 days, not every Too Good To Go transaction. City names come from current catalog records. Matching requires both an availability detection and a sold-out record for the same item and date, so unobserved and continuously available bags are absent.

Results can shift as store participation, monitored demand, and release behavior change. Sample thresholds and quartiles are shown to make that uncertainty visible.

FAQ

How quickly do Too Good To Go bags sell out?

It varies greatly. Use the live city table for current qualifying estimates and recent store behavior for a specific listing.

Does the fastest city have the most TGTG users?

Not necessarily. Store mix, inventory size, monitoring coverage, and release patterns also affect measured duration.

Why is my city missing?

It did not meet the threshold of 20 matched drops across at least three stores in the current 90-day window.

Is first detection the exact release time?

No. Monitoring can detect a bag after its actual release, so the study may understate total on-sale time.