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I think the math was what turned me off in training analysis when I was still a newbie. I have seen a couple of 150+ tsp guys (not a lot) in my 25+ seasons playing this game. It would be nice to see how their trainers pulled it off and what method they used. More recently, a Lithuanian manager broke down the table of Parrot which i thought made training very simple to understand even to a newbie with average intelligence. My mistake before was under estimating height in training speed its advantage and disadvantage. I constantly refer to that table to this day when I need to think about a training plan because it is convenient, and I do find it close to simulating training in this game that we all play.

Though both of you are in opposite views, its not productive to pursue because the conclusion was not based on the same data. So i am just going to go back to what works for me as a trainer. So unless i see more 150+ TSP hofs and atg on the transfer list i am not going to waste energy arguing 2-3 more skill points here and there.

So you believe that training IS for tall players you get 1 JS pop for every 3 IS pops and for a 6'0'' player you get 1 pop every 30? The difference is so large that this should be easy to test.

Crosstraining seems to be a % of the total training going to 1 or more random skills (and presumably the gym replicates that 1x-3x). Whether restrictions exist to this allocation could make a difference, because if it's completely random it could also fall to on the primary training skill. Crosstraining also creates noise in the data.

The PA and 1v1 connection to height is very bland even in rhyminsimon coefficients and it's certainly not as significant as it is for other skills. And since there a multiple variables involved here, I assume the relationship between all the variables was tested. For example, the PA slope may be entirely explained by elastic effect and the typical configuration of skills for players of different height. This could mean that the minimal connection with height is in fact no connection at all as it's driven by other variables highly correlated with height.

Using coachParrot I have not been getting pops in HA with 1 specific player (at least 3 several consecutive pops), while DR was on point. With each pop the margin of error should be decreasing, so something else was going on there. That player in particular had a fairly big imbalance between HA and DR. Using the other coefficients (the training simulator one) the estimate would have been even more off.

Last edited by Lemonshine at 11/29/2019 9:52:37 PM

Hey @Glasschimera,

Do you know if there is a bug on that doc that you provided last year? I made a copy of the doc and followed the steps outlined on the "Player Input" Tab (Sheet). Now when trying to use the "Training Calculator" Tab (Sheet), the data is all messed up.

Is there a copy floating around with no bugs? Or perhaps I missed a step between inputting the data and having it sync to the "Training Calculator" Tab correctly?

Many thanks!

Looks like there were a few users that didn't realize it was a publicly shared doc. I reverted it back to the correct version (https://docs.google.com/spreadsheets/d/1CwTrcEAGffBHhfxSEG...)

try and have HA greater than or equal to OD and passing (most of the

By this you mean OD + PA = HA? Or HA = OD = PA ?

But aren't elastic effects best utilized when there is a big difference between HA, DR, and OD? Then you train OD and it pops quicker or am I missing smth?