"The motivation decay algorithm used in gyms has finally been cracked"

#PokemonGO: Niantic seems to calculate a T(max) - time until maximum motivation decay - and not a decay per hour as a first step. This is the reason that fitting a simple algorithm failed so far. This T(max) is a discontinuous function with a fixed value for low CP Pokemon, a log function for the medium range of CP (with a fudge value to make it sensible) and a fixed value for high CP Pokemon. The fixed value for high range was discovered long ago. I only propose that the 10% start is moved from the previously accepted 2324 CP to 2323 CP. The fixed value for weak Pokemon below 300 CP was a new discovery for me. u/Kaukasiertje seems to have found it before me. Unfortunately I never read his article until just before posting my final results here.​Table 1 shows the different ranges and how T(max) is determined​CP rangeT(max)10-30072 hours300-2322250.35 hours - 72 hours x log10 (CP)2323+8 hours​Table 2 shows how to use T(max) to calculate the hourly decay.​CP rangeHourly decay in %10-3001.11% (or more precise 80/72 %)300-232280 / ( 250.35 hours - 72 hours x log10 (CP) )2323+10%​I have written a much more detailed account how the algorithm was discovered in a series of 7 articles​Quality Data – The Bedrock of any Analysis - Motivation Decay Part 1Ramblings about data quality and how I generated a new more precise data set​Over-fitting – The Bane of all Data Mining Motivation Decay Part 2Ramblings about over fitting - a good R-squared doesn't mean you are right​The Power of a Single Data Point Motivation Decay Part 3Deals how I discovered that the minimum decay has to be 1.11% and not 1%​A Discontinuous Function Wreaks Havoc Motivation Decay Part 4The hypothesis of a lower bound and fixed values for weak Pokemon​This Data is not Farfetch’d – Determining the Lower Bound Motivation Decay Part 5Pinning down the lower bound at 300 CP​How to determine and correct bias in your data (Motivation Decay Part 6) Motivation Decay Part 6How I determined the value of 250.35 as fudge constant and why it makes prefect sense​The true test – predicting the unknown Motivation Decay Part 7Testing the new function on some old data - actually this is already out of date as I discovered better data - see below​The complete blog is here: DrThod Blog​While looking for reddit users here whom to give a shout-out I stumbled upon an article by u/Kaukasiertje Research in Motivation Decay in the current system who used a stopwatch (I couldn't be bothered to go to this lengths) and generated even more accurate data (and more complete) as I did. Comparing his data to my formula I get an average difference of 0.0032% between measured and calculated CP with a max difference of 0.012%. I regard this as a great feat in accurate data gathering - and a nice confirmation to the algorithm detected. via /r/TheSilphRoad https://ift.tt/2Nh9N32