11. Hello, computer
How to automate our python scripts to run on a schedule; taking arguments / parameters from a shell input, time zone tricks.
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10. Game on a viz
We move onto producing a summary chart capable of telling the story of each game for the teams as well as players involved.
9. Game-on, game-off
We produce game-specific and matchup-specific shot blot charts to show how the playoffs and matchup has been affecting each team.
8. Seeing the trees in the forest
Breaking down the shot profile data for each player and visualising it to quickly identify and compare players' roles within a team context
7. Standard standouts
Once we have the game data, we need to identify the "standout" games. How might we do that?
5. Distant craving
Starting to analyse NBA play-by-play shot location data by distances to reveal insights into teams' offensive tendencies and edges.