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For anyone interested, here are some results from a study I did a few years ago Each dot represents projected pts yielded from 50 play-throughs of randomised versions of @fplreview.com's 20/21 data, with a decay rate (α) and FT value (β) selected using Bayesian optimisation (8 GW horizon)

fplreview@fplreview.com

@trout-post.com did some heavy analysis on what setting parameters yielded the best outcome a while back that supported ~0.84-0.85. Myself and Mikkel Tokvam had initial rules of thumb (based on concepts like the above) that his analysis ended up close to- which was a pretty cool validation

I never shared these results in detail bc I think they do more harm than good if taken as gospel. My general thoughts are - Any rate 0.8-0.9 is useful - The "optimal" rate probably depends on game state - The best use for decay is to try various rates and learn from the differences between solutions

These results are from just one season, and before recent rule changes I don't think the question of optimal decay rate is closed, but I don't really think it's worth pursuing - it's very boring and noisy and there are other way more interesting & impactful things to study in FPL

While we're on the subject, I'm not sure how to feel about this framing of decay as risk preference 🤔 Decay is the balance of chasing short/long-term gains. Chasing short-term gains is inherently "riskier", but this is only a tiny part of how FPL managers engage with risk bsky.app/profile/ffh-...

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