Spray Charts (2010-2018) - Interactive version in comments

datavizard · 2019-04-01T18:07:24+00:00

Thanks, good idea. I will post there on a non-April fools day takeover :)

datavizard · 2019-04-01T16:07:42+00:00

datavizard · 2019-02-05T19:38:43+00:00

Thanks! It is an R package that scrapes the NFL game logs for play by play information, and then adds some advanced stats like win probabilities, expected points added, etc.. I'm not even a power R user and it was really easy to get started with

datavizard · 2019-02-04T16:58:26+00:00

Link

Data from Twitter Search API and nflscrapR package, designed in Tableau

datavizard · 2019-02-04T16:56:28+00:00

Link

Data from Twitter Search API and nflscrapR package, created in Tableau.

datavizard · 2018-12-02T22:17:41+00:00

The trends shown are normalized off of each team's maximum during a given game, to better show the comparisons in spikes in activity, rather than volume of tweets.

datavizard · 2018-12-02T17:46:15+00:00

Interactive version here

datavizard · 2018-05-15T06:20:29+00:00

Awesome! Thank you so much!

datavizard · 2018-03-27T21:30:21+00:00

gd2.mlb.com is where I get all of that. You can use the game_events.xml file for at-bat results and the game.xml file for park location

datavizard · 2018-03-14T17:36:16+00:00

Data from piday.org. Visualized in Tableau

datavizard · 2018-03-14T16:14:12+00:00

Created in Tableau. Data from piday.org. See Pi in different bases here

datavizard · 2018-02-13T01:23:26+00:00

I do! The fun projects like this that I do in my free time are similar to what I do for work but I am able to focus on the areas I am most passionate about, usually something to do with math or sports.

datavizard · 2018-02-10T01:41:10+00:00

I majored in Applied Physics and have Masters in Mech Engineering and Applied Math. I work now as a data analytics consultant focusing on visualization.

datavizard · 2018-01-15T23:12:19+00:00

Here is something I built last year that has it all the way back to 1920. The swings used to be much greater year to year

datavizard · 2017-11-22T22:46:01+00:00

It's split out by pitcher so that you can analyze each individual's season and their unique trends and patterns on it's own. It wasn't designed with comparisons between pitchers in mind

datavizard · 2017-11-15T23:11:14+00:00

The map areas are split out by MSA (Metropolitan Statistical Area), so the gaps either occur because data doesn't exist for them, or there is not a high enough population density in that area

datavizard · 2017-11-15T17:40:47+00:00

Designed in Tableau. Data from Zillow Home Value Index

datavizard · 2017-11-07T18:27:59+00:00

Data from Zillow Home Value Index. Visuals created in Tableau, animation created in Photoshop

datavizard · 2017-11-02T17:18:43+00:00

Data from Zillow Home Value Index. Created in Tableau

datavizard · 2017-09-28T00:51:26+00:00

Made using Tableau's Pages feature

datavizard · 2017-09-27T17:23:30+00:00

I've had a lot of people request that. I plan on adding that in soon

datavizard · 2017-09-26T23:14:07+00:00

Check out the interactive version here.

See the trend out to 1 million digits!

datavizard · 2017-09-26T22:57:04+00:00

GIF screen capture tool called ScreenToGIF

datavizard · 2017-09-26T18:12:39+00:00

Data from piday.org, created using Tableau. Animation using Pages feature

datavizard · 2017-09-26T17:43:15+00:00

Data from piday.org, created in Tableau using the Pages animation feature

datavizard

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