NHL Play by Play -> Elasticsearch

Supporting example for the blog post Kibana and a Custom Tile Server for NHL Data.

This examples downloads data from live.nhl.com. E.g http://live.nhl.com/GameData/20142015/2014021136/PlayByPlay.json, indexing it into Elasticsearch. Prepared dashboards are provided with the example, along with instructions on geo-referencing the TIFF image described in the blog post.

Version Requirements

The example has been tested against the following versions:

• Elasticsearch 5.0.0
• Logstash 5.0.0
• Kibana 5.0.0
• NodeJS

Datasets

Datasets are collected from http://live.nhl.com.

Imports it into Elasticsearch by season or by game.

Installation & Setup

• Follow the Installation & Setup Guide to install and test the Elastic Stack (you can skip this step if you have a working installation of the Elastic Stack,)

• Run Elasticsearch & Kibana

  <path_to_elasticsearch_root_dir>/bin/elasticsearch
  <path_to_kibana_root_dir>/bin/kibana

• Check that Elasticsearch and Kibana are up and running.

  • Open localhost:9200 in web browser -- should return status code 200
  • Open localhost:5601 in web browser -- should display Kibana UI.

Note: By default, Elasticsearch runs on port 9200, and Kibana run on ports 5601. If you changed the default ports, change the above calls to use appropriate ports.

Download the following files:

    https://raw.githubusercontent.com/elastic/examples/master/Exploring%20Public%20Datasets/nhl/clean.sh
    https://raw.githubusercontent.com/elastic/examples/master/Exploring%20Public%20Datasets/nhl/go.js

Ingest Data

1. Run npm install

2. Run ./clean.sh to erase any previous data and re-prepare the index (shows an error the first time it runs, that's ok)

3. Run node go.js to importing data as shown below

   Usage:

   node go.js <season> [gameid]
   

   Example, Import the whole 2014-2015 season:

   node go.js 2014
   

   Example, Import a specific game (once you know the id). This is specific for updating real time during a game.

   node go.js 2014 2014030416
   
   

Check data availability

Once the index is created using either of the above options, you can check to see if all the data is available in Elasticsearch. If all goes well, you should get a positive count response when you run the following command.

curl -H "Content-Type: application/json" -XGET localhost:9200/nhl/_count -d '{
	"query": {
		"match_all": {}
	}
}'

Visualize Data in Kibana

• Access Kibana by going to http://localhost:5601 in a web browser
• Connect Kibana to the nhl index in Elasticsearch
  • Click the Settings tab >> Indices tab >> Create New. Specify nhl as the index pattern name, select @timestamp as the Time-field name, and click Create to define the index pattern. (Leave the Use event times to create index names box unchecked)
• Load sample dashboard into Kibana
  • Click the Settings tab >> Objects tab >> Import, and select dashboards.json
• Open dashboard
  • Click on Dashboard tab and open NHL dashboard. Voila! You should see the following dashboard. Happy Data Exploration!

Top Hitters, Shooters, Scorers & Penalties per Game

All Season Top Hitters, Shooters, and Scorers against the Habs

We would love to hear from you!

If you run into issues running this example or have suggestions to improve it, please use Github issues to let us know. Have an easy fix? Submit a pull request. We will try our best to respond in a timely manner!

Have you created interesting examples using the Elastic Stack? Looking for a way to share your amazing work with the community? We would love to include your awesome work here. For more information on how to contribute, check out the Contribution section!