Dashboard Digest Series – Episode 4 – NFL Predictions

In Episode 4 we will take a look at the four downs of football. We used the Machine Learning Toolkit and more than a decade of NFL data to build models to make predictions during NFL games.

In order to make it quick and easy to plug in a scenario and visualize the most likely outcomes, we made a simple dashboard so editors at Sports Illustrated could try it out during a game. You may have seen the dashboard if you were watching CNN before the Super Bowl earlier this year:

Purpose: Predict the next play
Splunk Version: Splunk 6.4
Data Sources: Every NFL play and player since 1999
Apps: Machine Learning Toolkit, Shapester

The data contains a lot of fields

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Buttercup Games – Level 3: The One-Millionth Flap

1mil_low

On the final day of .conf2016 some of us were having dinner and I noticed the number of total flaps was approaching 1 million. That means people tapped their screen nearly 1 million total times to make Buttercup fly! So of course I needed to open a real-time search and watch it click over.

This made me wonder who was the person who actually touched their screen for the 1 millionth time?  The answer is always just a search away in splunk.

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Congratulations to Mike Ruszkowski, I hope bells rang and confetti rained! I know my co-worker Matt Oliver (at the top of the table above) was gunning for that 1 millionth flap.

Beyond the millionth flap there have been some other impressive statistics. I’m …

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Buttercup Games – Level 2: Buttercup Go data

Buttercup Go is thriving 4,234 people have played the game and lots of data is being generated. In this post I’ll walk through some of the data we are generating.

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The data includes web, OS, load balancer, network, firewall, other AWS data, etc. There are a few other data sources I want to point out specifically.

Authentication Data

We wanted to allow users to play right away, without the need to sign up. Auth0 was a perfect choice. It was quite easy to use and gave us everything we needed. Not only did it allow many authentication options (think Google, Facebook, Twitter, LinkedIn, etc) but Auth0 also generated great data and could send directly into Splunk. Here was the breakdown of how people …

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Buttercup Games – Level 1: The Premise

If you saw the .conf2016 keynote you might be wondering “What is Buttercup Games? Is it for real?” Well, yes and no. It’s not a real company, but it is a real game.

Screen Shot 2016-09-28 at 12.43.49 PMSo why Buttercup Games? Years ago a few Splunkers decided to build some training material around a fictitious company and make it fun. They chose to take our mascot (Buttercup) and something fun (games) and combine them. Buttercup Games was born. Logos were designed, data was generated, classes were created. Maybe you’ve even taken one – if you haven’t you should. Especially if you attended .conf this year and got $5,000 in education credit for free.

A couple of weeks ago some Splunk employees …

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Vote using Splunk

Someone recently challenged me to use Splunk for voting. Splunk is a versatile platform, why not make a voting app? Sigi and Stephen put the app together one afternoon and then I tested it out on a live audience during SplunkLive! San Francisco.

 

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It worked like a charm and we gained insight from the audience. That’s when I realized, although it’s not a typical use case of Splunk, this app could be useful for others. From polling an audience during a presentation or even getting consensus from coworkers on a question during a meeting, maybe I should put the app on splunkbase.

 

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Splunk & 21st Amendment Brew day 2016

Do-ocracy (do͞o äkrəsē): The spirit of taking ownership/command/possession/etc and making it happen. That’s how we operate at Splunk. To commemorate this methodology we teamed up with 21st Amendment to make a DPA, or “Do-Ocracy Pale Ale”.

On February 29th we walked over to 21st Amendment which is conveniently located around the corner from our headquarters (could that in itself be a reason we chose the location of our HQ? Very possibly). Before we started brewing, we thought to throw in a few sensors; since we recently Splunked BBQ using Tappecue we just re-purposed the sensors and modified the dashboard for the brew day.

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There are four primary stages of the brew day:

1. The Mash-In: We add water heated to a specific temperature to the

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NBA Finals 2015

I recently posted a blog about Splunking my golf swing and afterwards a co-worker asked if I could Splunk the NBA finals. He gave me some NBA data and while on a flight today I decided to look into the data a little with Splunk. I don’t know very much about basketball and you all probably have way better questions to ask of the data; nevertheless I gave it a shot on my flight. Note: CLE=Cleveland and GSW=Golden State Warriors

Each file had the date of the game and who played where as the filename.
[2015-05-22]-0041400302-CLE@ATL.csv
[2015-05-23]-0041400313-GSW@HOU.csv
[2015-05-24]-0041400303-ATL@CLE.csv
[2015-05-25]-0041400314-GSW@HOU.csv
[2015-05-26]-0041400304-ATL@CLE.csv
[2015-05-27]-0041400315-HOU@GSW.csv
[2015-06-04]-0041400401-CLE@GSW.csv

Since it was csv I imported it as such and set timestamp based on the date and “elapsed”.…

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FORE! Splunking my Swing

So I went to the golf range last night. It was an indoor range just a few blocks from Splunk HQ called Eagle Club Indoor Golf. They are using stereoscopic camera systems that precisely capture and analyze ball flight. Checkout their place in the virtual tour below.

Naturally, I asked if I could get a copy of the raw data. After an eyebrow raise they said “Sure”. They emailed me a CSV file that looks like below:

Club, Club Head Speed, Ball Speed, Launch Angle, Azimuth, Side Spin, Back Spin, Total Spin, Descent Angle, Carry, Total Distance, Offline, Peak Height, Vert Path, Horiz Path, Face to Path, Face to Target, Lie, Loft, Horiz Impact, Vert Impact,
Driver, 109.7, 159.1, 4.3, -2.6, -1665,

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