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Wooah–looking at your project on my computer atm–very nice design! Love the mouseover information and the filters. Very impressive! Very nice filters. I agree that it would be interesting to see how this data has changed over time. Also, I wonder if it would be cool to also include a score? I’m not sure how that would work, since I think your score differs between what position you play. But maybe, for example the MLB, include the bat hit rate or something. Perhaps use a sub-filter beneath your current filter bar which changes depending on which filter you choose. I’m not trying to diss your project—it’s amazing as is, especially considering the time you had and all the data you had to work with–just trying to push you to include more data, if you have time! 🙂 It’s such a great interface! And, I find it extremely interesting even though I’m not a huge sports fan. -Amanda

This visualization is very interactive in an intuitive way. I also like that you manually scraped their data (i think?) – this set should totally be open; ESPN is doing themselves a disservice if you didn’t grab this via an API. This itself should be proof to a place like ESPN why their data should be open. Anyhow. You seem to have hijacked the look and feel of a real ESPN site – which is very cool, and means you could turn this around and get bought by (or sued by) ESPN in a heartbeat. I like that you used the private data source – it seems to add an authenticity to the visualization that seems to help it. I wouldn’t get the same “ooh” effect if this was the same player data pulled off of Wikipedia. Power of ESPN’s branding, or quality of their data? Unclear. 🙂
You’ve done an incredible job scraping the metadata (and in many cases, creating your own). You should make a blog post that walks through not just the process itself, but the *things you’ve found,* using the insight about sports that you clearly have. The interpretation of the data is what’s going to interest a sports fan to continue playing, and get this project the attention (and lawsuits) it deserves.

This looks like an ESPN visualization. Very nice. I really llike the player profiles you get when scrolling over. Get this on the internet!

The left graph on the left is a little confusing at first. I think it’s because it’s upside down.

Wooo! John Elway! 😀 would be nice to see jersey numbers over time, like if a certain number was not popular but then someone got more welllknown using it and if it became more trendy… i really enjoy that you split it up by position. love seeing the dfferences.

really like the project! would be nice to see more information than just current players
i agree. past players would make this amazing.

It’d be interesting to see a number’s popularity over time. Did #23 become more popular after Jordan?

For the NFL, you should take into account that the numbers aren’t just random — there’s a very specific numbering system described here: http://www.jt-sw.com/football/pro/index.nsf/Documents/0-jers-nums So maybe on the screen you could have something about those brackets, pointing out for example that 1-19 are quarterbacks, punters and kickers. — Okay, never mind, you do have it with the ‘position’ thing. Still, maybe including something on that page about the rules of football numbering might be helpful. most sports have certain numbers associated with position

Very nice and informative visualization. A controller for period is useful.

wow super thorough coverage of different perspectives on the data

The color sort seems to be a bit disorganized when looking at a specific sport. Why not sort the same way you did in “all” ? Grouping experience of position or salary together in an intuitive way. There may already be a logic to it, but i didnt catch that.

Clicking on anything that isn’t a button makes the chart revert to white.

Raymond — this project is a home run, no pun intended. You’ll have to (carefully!) find the right way of releasing it to the public. Beautifully done, and impressively ambitious! It will surely attract tens of thousands of users online!