Jumping to conclusions

Today’s blog post’s sheds a little light on the data that we have collected, the team, the tools, and a cool insight I was able to get an answer on! I’m going to give you a quick breakdown of what’s going on with the data, how we got it, and some of the problems presented.

About our dataset.

So the dataset used for each of the visualizations that you see here and on my tableau dashboard uses the data collected from https://www.tfrrs.org/. I have to give credit to my roommate and co-worker, Evan Keating who was able to gather the data off of the website from the top 500 vaulters from 2010-2020 leaderboard. We were able to collect the top 500 marks in each division, and the top mark for that vaulter.

Additionally, we can tell from each record at what meet this jump occurred, and on what date this jump was taken. This will give us some answers to our more basic questions and can provide us some information to trends for different regions of the pole-vault..

The Problem with the data

To help you understand what is possible with the dashboards that we have created you have to understand the data that we have to work with. Here’s the problem – there really isn’t an easily accessible data source for this information AND different levels of data are managed by different leagues, organizations, entities etc.. This made the start of this process particularly difficult.

There is one source that rules over all others, and in this case it happens to be for the better, the NCAA. Collegiately all marks are recorded and presented in a uniform format over at https://www.tfrrs.org/. This became the source for our data used in this dataset.


Now to be more clear on what we were able to collect, I want to break that down here;

  1. The Top 500 marks of both men and women for
    • Indoor seasons from 2010-2020
    • Outdoor seasons from 2010-2020
    • Divison I, II, & III

OK, so what does this mean? If your best mark of the listed seasons was high enough to reach the Top 500 leaderboard then you will be recorded. So there is not an athlete progression year over year.

Additionally, from 2010-2012 athletes with their recorded marks are marked as NULL. This data inconsistency is something that has skewed some of our initial results as we continue to work through those challenges.

Some cool questions we can answer…!

  1. What is the average height for each of the three divisions? (Top 500)
  2. What is the average height across each division for each gender?
  3. What is the average top 10 height across each year for gender/year?
  4. Have the heights gotten any higher/lower?
  5. Which teams have the highest averages for heights cleared in the top 500?

Our first dashboard covers a running sum of the Top 500 marks since 2010. The total distance covered is 36.6 miles. That’s the equivalent of traveling round-trip from 242nd to the South Ferry station in New York City.

To put it in perspective check it out on the map!

A Big Thanks

Before I get into the data analysis and pole-vault stuff, I have to give credit to those who helped me along the way. Without their contributions some parts of this project would not have been possible. From ideas, questions, data collection, and various development efforts were able to make all of this possible.

Evan Keating  A former roommate and co-worker of mine. He was able to get the initial dataset and momentum for this project would not have been possible.

Influence

Aside from those who were able to make this possible I also wanted to acknowledge the coaches, mentors, friends, and others who I reached out to at the start of the this endeavor. I reached out to a couple of coaches, friends, and other influences in the pole-vault community. Asking similar questions to see what needs to be answered and what would be helpful for others to take a look at.

Did you know that we’ve pole-vaulted from #VanCortlandt to #SouthFerry? Check out this post to see where else the sport of pole-vault is going! #polevault #vault #jumps #trackandfield #data #tableau

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