Heps 1500 Development Rankings

This is a total waste of energy. You need to know the number of athletes and their starting points to create more a accurate study, then define what is impressive. As an athlete trends toward a more an elite level their improvement curve becomes less prounounced. For example a 3:52 kid can improve to 3:46 over 4 years and that's not significant but a 3:44 kid over the same period of time who improves to 3:40 is. Your study is pointless.

Can you do this for the Ivy League women’s 1500 too?

Another factor which is very important when looking at development in terms of which coach is better is what did they do in high school. Just because someone runs 4:06 for 1600m in high school does not mean they are more talented than the guy that ran 4:16 in high school. How many time trial races did they run? What was their mileage? Did they have other teammates on their team that ran under 4:30 (which may indicate strong high school coach and therefore that this athlete may be closer to their genetic best).

There are many other factors in looking at development within a program and coaching ability.

Get a life. wrote:

This is a total waste of energy. You need to know the number of athletes and their starting points to create more a accurate study, then define what is impressive. As an athlete trends toward a more an elite level their improvement curve becomes less prounounced. For example a 3:52 kid can improve to 3:46 over 4 years and that's not significant but a 3:44 kid over the same period of time who improves to 3:40 is. Your study is pointless.

If you a referring to a starting point in college, I think you misunderstand basic algebraic equations.. That’s exactly what the constant value is estimating. If you are referring to high school, I completely agree, but I haven’t found a good way to import that data easily.

In terms of a wasted of time: fair enough hahah but it’s summer! At least it refreshes my python and pandas knowledge a little!

Ignant wrote:

Another factor which is very important when looking at development in terms of which coach is better is what did they do in high school. Just because someone runs 4:06 for 1600m in high school does not mean they are more talented than the guy that ran 4:16 in high school. How many time trial races did they run? What was their mileage? Did they have other teammates on their team that ran under 4:30 (which may indicate strong high school coach and therefore that this athlete may be closer to their genetic best).

There are many other factors in looking at development within a program and coaching ability.

This is obviously a factor and covers some of the huge amount of confounding variables.. One would hope that with a large enough sample size these would start to cancel out because I can’t think of any better way to control them.

this might not be a truly accurate picture of what is happening. But, it does give a good indication of which programs are doing a good job and which one is not.