> For the complete documentation index, see [llms.txt](https://aon-all-or-nothing.gitbook.io/aon-all-or-nothing/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://aon-all-or-nothing.gitbook.io/aon-all-or-nothing/introduction/audit.md).

# Audit

<figure><img src="https://1854384894-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FlQG9EguFY4wxh3m47Huz%2Fuploads%2F9XtFjY0kMbAnLZwdrIvF%2Fimage.png?alt=media&amp;token=a4231f9f-beb7-4279-8131-a5493cf859d9" alt=""><figcaption></figcaption></figure>

## Spin Mechanism Audit

The provided code snippet determines the winner of a spin based on a weighted random selection. Here's a breakdown of how it works:

1. Initialization:
   * cumulative\_percentage is initialized to 0. This will be used to accumulate the win percentages of players as we iterate through them.
   * random\_percentage is a random float value between 0 and 100. This represents a random point on our "wheel".
2. Iterating Through Players:
   * The code then iterates through each player in the `last_game`'s players list.
   * For each player, their win\_percentage is added to the cumulative\_percentage.
3. Winner Selection:
   * If the random\_percentage is less than or equal to the cumulative\_percentage, then the current player is selected as the winner.
   * This mechanism ensures that players with higher win percentages have a larger "segment" of the wheel, and thus a higher chance of being selected as the winner.

In essence, this method is a form of weighted random selection, where each player's chance of winning is proportional to their assigned win percentage.