BuzzerBeater Forums

Hi

Joined the project and uploaded all info i have so far, looking forward to see what comes out of this.

Thanks

Great to see more people joining in, and glad you're liking it so far. Sorry I haven't had more time lately to add new features, but for those that haven't been checking, the analyses that are already up there have been getting more and more accurate as more data has been added. The training speed section is getting more useful as filtering for certain ages and heights is more likely to produce meaningful amounts of data, and the age effect curve has gotten nicer and nicer (28-29yo is the one area that still looks pretty odd, because we still don't have a ton of data there, so if anyone's training older guys--even by accident!--it'd be great to get your data included).

We should very soon have something up on trainer level. Between busy holidays and some confusing data (the effect of trainer level looks very different for 18-19yo's than 20+, so I'm trying to nail down whether that's just noise or indicative of some underlying design feature) this has been a bit slow to roll out. But we've got good amounts of data, so hopefully we get there in the next week.

As a small update, the usage stats page now lists the top 5 training types this week (see what people are doing on those shortened weeks, or in the playoffs, or just what the latest trends in training are), and all time (hint, everyone loves OD!).

I have posted this in the Greek forums,hopefully we get some guys to sign here too..

great job everyone, I will do my best with my small team :)

my 18 yo pg, trained pressure and popped in OD (5-6) and in ID (4-5)

Uploaded every training update ever.

Last edited by Ralph54 at 1/5/2012 7:23:40 PM

I am pretty sure he has already looked at the effect of minutes for training, but given the nature of the data there is probably still WAY too much noise and SSS to make any definite assumptions, thus he probably has not let us know.

I'm wondering how it handles the partial minutes in the data...

First of all, everything that's posted uses only instances of 48 minutes, so not a concern that it could be skewing the data.

As for the effect of minutes, yes, showing it like age is the goal. The problem is controlling for everything. E.g., you could show it for 18yo's getting Pressure PG training, but that's so specific that we won't have enough data. You can't really group too many things, because the basic rates change a lot as a function of age, skill and training type.

The real solution, which I've started playing with, is to create a single model that can explain all the data, then doing parameter fitting to figure out exactly how much things matter. The problem with this is that you need to have a decent guess for what the equation should be. I mean, it's easy if things are linear, but minutes are almost definitely not, so you need a way to figure out whether it's best modeled as a decaying exponential, a power law, or something else you haven't even thought of. Which is why I've been trying to start with plots like the age one, it gives a really good sense of what that component should look like.

My current idea is to guess something close and do an analysis of residuals (looking at the difference between the actual and expected data) and seeing if you can use that to find a better model. Unfortunately, this is a bit of a computationally intensive process, so I haven't found a way to do it "live" in php yet (and the method is still *very* rough). And it's tough to combine across a lot of training types. But that's a sneak peak at the long term aim.

Some other good stuff in there that i'll think about wolph.