The NCAA data is in - The super spike effect is real

distancerunningwizard wrote:

Most of it has to do with not running to many races...

Right. If you ran to a race you'd be all tired out before the gun event went

Another Millennial from Seattle wrote:

zxcvzxcv wrote:

I went through the TFRRS outdoor qualifiers top 100 for the flat distance events for 2021, 2019 and 2018.

[...]

There may be some effect from the Ivy League or any others cancelling their seasons but there's just not a clear shoe effect. M 1500m and M 5000m give you the best basis for a claim to difference but only at the 100th place. The W 1500m at the top is improved. The 10000m does not support that. Meet cancellations could have an effect as well. We just can't conclude anything from the data here.

Nice work. Let's see what the numbers look like in a month, when all the meets and NCAA marks are wrapped up. I'm guessing 800m and 10,000m marks will improve.

So what we have is consolidation then, where we aren't really any faster, just deeper. Which makes sense considering the long layoff, extra year of eligibility, harder regional qualifiers, looming Olympic trials, etc. It's the same for the American pros, who are just grouping in the 13:00 - 13:10 range for men and 14:50ish for women....as an example. The only recent records that were broken, were in the old shoes....Houlihan, Braizer, Frierichs.

If the shoes were THAT big of a deal, we'd see changes at the top as well...like in the marathon. But we don't.

How is your knowledge of statistics for extreme values?

The title of this thread is misleading

The data is in, but the super spike effect is correlated but statistically indeterminate.

Spot on

I notice much thicker packs at the local high school track level. I think what is happening is that runners who otherwise would run into biomechnical issue are able to run at the front with form that usually would be inefficient. What I also notice is that cross country hasn´t changed.