What causes a biased deck shuffle in a card game?

The shuffle swaps each card with a random index across the whole array, which is the classic naive shuffle that produces a non-uniform, biased distribution of orderings.

How do I catch this when it only happens for some players?

Capture it automatically from the player's device with the full stack trace, the device and OS, the build, and a breadcrumb trail of what they did. That turns a vague complaint into a specific, reproducible issue you can fix without owning the hardware it happens on.

How to Fix a Biased Deck Shuffle in a Card Game

Quick answer: Replace it with a Fisher-Yates shuffle that for each index i picks a random index in the remaining range [i, n) and swaps once.

A shuffle that picks any index for every swap is mathematically biased, and players notice patterns. Fisher-Yates gives a provably uniform shuffle. Here is the correct implementation.

How to fix it

1. Use Fisher-Yates correctly

Loop i from the last index down to 1, pick a random j in [0, i], and swap cards i and j. Picking j from the full range instead of the remaining range is the bias bug.

2. Seed a real RNG

Use a well-distributed generator, not a low-entropy or repeatedly re-seeded one. Re-seeding with the clock each call can correlate consecutive shuffles.

3. Make it reproducible for replays

If you need deterministic shuffles for replays, seed from a logged value so the same seed reproduces the exact order without sacrificing uniformity.

Catching the ones you can't reproduce

The hardest version of this to fix is the one you can't reproduce — it only happens on a player's hardware, OS, driver, or save state, under conditions that simply aren't present on your machine. A report that says “it crashed” or “it froze” gives you nothing to act on, so the bug survives release after release while quietly costing you players.

Automatic error capture closes that gap. Each failure arrives with its full stack trace, the device and OS, the build number, and a breadcrumb trail of what the player did right before it broke, so even a failure you have never seen becomes a specific, reproducible issue. Fold identical failures into one signature ranked by how many players each hits, and your worklist sorts itself worst-first instead of arriving as a stream of vague complaints.

This is where a tool like Bugnet earns its place. Its SDK captures every error automatically with the full stack trace plus device, OS, memory, build, and game-state context, folds duplicates into one grouped issue with an occurrence count, and ties each to the build it first appeared on — so you fix the problem that hurts the most players first and confirm it is gone when its signature disappears from the next release.

Reproduce it once with full context and the fix writes itself. The hunt is the expensive part.