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One breakout title = 99.9% of a studio's traffic: what Roblox's own public API shows about "genre template" games

#gamedev #data #api #roblox

Roblox exposes game and group stats through public, unauthenticated endpoints — no login, no scraping tricks:

GET https://games.roblox.com/v1/games?universeIds=<id>,<id>,...
GET https://games.roblox.com/v2/groups/<groupId>/games?limit=50
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I used them to pull the full public games list for a few independent creator groups that each ship multiple games in the same cheap-to-build "obby" template genre (think: dozens of studios building the same core traversal loop with a different skin). The question was simple: within one studio's own catalog, how concentrated is traffic in the single best title versus everything else they've shipped?

The answer is the same shape every time: a small number of throwaway builds with near-zero traffic, and one outlier that accounts for nearly all of the studio's lifetime visits. Not "most games do okay and one does great" — more like one game is the studio, traffic-wise, and the rest are lottery tickets that didn't hit.

As a sanity check against numbers that are already public knowledge (no anonymity concern), I ran the same script against Uplift Games' group (id 295182):

$ python3 fetch_group_stats.py 295182
Group 295182: 371 published experiment(s)
Total lifetime visits across all games: 44,412,921,224
Top title alone: 44,377,094,324 visits (99.9% of the group's total traffic)

Visit-count distribution:
     0-10K: 355 game(s)
  10K-500K: 12 game(s)
   500K-5M: 2 game(s)
    5M-50M: 1 game(s)
      >50M: 1 game(s)
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One title (Adopt Me) is 99.9% of that group's entire lifetime traffic across 371 shipped experiments. Same power-law concentration as the smaller, anonymized groups in the full writeup — just at a much larger scale.

Why this is more than a curiosity: if you're building in a genre like this, the template itself is clearly not the moat — everyone in it ships near-identical mechanics. The variance between a 45-visit build and a 700M-visit build using the same template looks like it's mostly about timing and whatever the discovery algorithm rewards that week, not the underlying game design. That argues for cheap, fast iteration across many small attempts as the rational strategy, not a sign of low effort — and it argues against reading "the genre did N hundred million visits this year" as evidence that participation in it is a good bet for a typical studio, since almost all of that number is a small number of single-title wins.

Full writeup, the anonymized group data, and a runnable script (fetch_group_stats.py — point it at any Roblox group ID and it computes this distribution itself) are here: https://github.com/singularitystudiosdev/roblox-brainrot-genre-economics

Everything above is reproducible with two curl commands and no auth. If you try it against a different genre or a group I didn't cover, I'd be interested to know whether the same shape holds.

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