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@@ -5,82 +5,35 @@ Here's an article by that explains gives some more detail about the project: *[N
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Here's an example of an analysis that you can do with pbprdf: *[Analysis: 3-point shot percentage after other team makes or misses](https://gist.github.com/andrewstellman/4872dbb9dc7593e56abddbe8b998b509)*
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## Running pbprdf
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Install and run
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===============
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To run pbprdf, download the latest release from the Releases page: https://github.com/andrewstellman/pbprdf/releases and make sure Java 8 or later is in your path.
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__Prerequisite: [sbt](http://www.scala-sbt.org/) 1.x and Java 8 or later must be in your path__
This will create a folder called `data/retrieved_*` (with a timestamp at the end of the folder name) with subdirectories for various seasons and playoffs. Move the folder for a season or playoff into the current folder (in this example, the folder with the 2014 playoffs):
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Step 2: Download a set of play-by-play HTML files
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```
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$ ./fetch-wnba-play-by-plays.sh
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$ mv data/retrieved_*/wnba-2018-playoffs .
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```
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Step 3: Run pbprdf and generate the Turtle file for the 2014 WNBA playoffs
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Step 2: Run pbprdf and generate the Turtle file for the 2014 WNBA playoffs
One effective way to execute SPARQL queries against these files is to use [RDF4J Server, Workbench, and Console](http://docs.rdf4j.org/server-workbench-console/). RDF4J Server and its GUI, RDF Workbench, are both web applications that run in an application server like Tomcat.
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__Step 5: Import your Turtle file__
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You can use the instructions above to import your `*.ttl` or `*.ttl.zip` files into your newly created database. You can either use the RDF4J console or RDF4J workbench GUI to execute SPARQL queries.
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## Building pbprdf
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__Prerequisite: [sbt](http://www.scala-sbt.org/) 1.x and Java 8 or later must be in your path__
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