24:null 25:["$","title",null,{"children":"Watch the NBA Finals Players Data Jam on Observable | Observable | Observable"}] 2a:T450,The 2022 NBA Finals Playoffs started yesterday with Game 1 shockingly going to the Boston Celtics over the Golden State Warriors. With Observable being a remote company ([BTW we're hiring](https://observablehq.com/about#jobs)) headquartered in San Francisco, CA, home of the Warriors, with a global team we're pretty excited about the NBA Finals. As NBA Basketball fans, the team at Observable wanted to combine efforts of analyzing each game while also having fun showing the variety of ways to use Observable. The end result is a notebook that is not only for data analysts or data practitioners but also NBA fans and even the [#NBATwitter](https://twitter.com/search?q=%23nbatwitter&src=typed_query&f=live) community can enjoy. The project is led by Data Visualization Developers, [Paul Buffa](https://observablehq.com/@pstuffa) and [Anna Wiederkehr](https://observablehq.com/@wiederkehra), along with designs from [Virginia Poltrack](https://observablehq.com/@virginiapoltrack). The team has created a new interactive way to watch the NBA Finals players have a Data Jam in a notebook on Observable.2b:T543,### How to watch? The day after each game, everyone can visit this collection to see the [NBA Finals Players Data Jam notebook](https://observablehq.com/@observablehq/nba-finals-boston-celtics-vs-golden-state-warriors) from each game. Each notebook will feature player analysis and data visualizations from the actual NBA Finals game. The notebook provides five analyses on _The Game Data_, _Who Was On The Court_, _The View From The Score Board_, _Play-By-Play_, and _Player Summaries_. Throughout the notebook, NBA data fans can view data animation cards of players who made or missed shots over the course of the game, along with their sentiment analysis, plus fouls by the team. A bar chart race like "The flux of gameplay" that shows the score for each team, a play, over the course of the game by shot analysis. A look at successful shots on the court, each shot made, by team, over the course of the game. No NBA game analyst would be complete without breaking down the game by type of plays, or shot attempts and shots made by each team over the course of the game. The [NBA Finals Players Data Jam](https://observablehq.com/@observablehq/nba-finals-boston-celtics-vs-golden-state-warriors) concludes with a _Player Summaries_ plot that breakdowns players by their points and rebounds during the game, by each team. Check it out! 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\n### Make your own NBA Finals Players Data Jam\nOne of the best parts of the [NBA Finals Players Data Jam](https://observablehq.com/@observablehq/nba-finals-boston-celtics-vs-golden-state-warriors) is that you can jam along and you can create your own data analysis with our data on Observable. Every day after a Finals game, we'll be posting new notebooks with the game data. You can fork each notebook, add your own data visualizations from existing game data, and invite your friends to collaborate on the NBA Finals data. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":70,"value":"___","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":14,"value":"

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":28,"value":"### More NBA data visualizations on Observable\nThe team at Observable are not the only NBA fans that use Observable. We've created a collection of numerous notebooks from the community such as [Russell Goldenberg's The Real MVP in the NBA](https://observablehq.com/@russellgoldenberg/the-real-mvp-in-the-nba) notebook, [Ryan Menezes's Shot charts for every NBA player](https://observablehq.com/@ryanvmenezes/nba-player-hex-calcs) notebook and [Nicholas Ortenzio's NBA Clutch Stats Comparison](https://observablehq.com/@nor/nba-clutch-stats-comparison) notebook. You can view the collection [here](https://observablehq.com/collection/@observablehq/nba-on-observable).\n\n___","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":133,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":17,"value":"### How to follow the NBA Finals Players Data Jam?\nOnce we have the data from each finals game we'll share the notebook in the collection [here](https://observablehq.com/collection/@observablehq/nba-finals-players-data-jam) and data snippets from the game analyst along with the notebook via the [@ObservableHQ](https://twitter.com/observablehq) Twitter account.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":152,"value":"buttonCTA(\"View The NBA Finals Players Data Jam Collection\", \"https://observablehq.com/collection/@observablehq/nba-finals-players-data-jam\", \"#000\") // ui blue","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":83,"value":"___","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":79,"value":"banner(\"Interested in learning more about collaborating with data?\", \"Sign up for free\", \"https://observablehq.com/product?utm_medium=social&utm_campaign=nba_data_jam&utm_source=observablehq.com\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":76,"value":"import {banner} from \"@observablehq/brand-assets\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":95,"value":"import {buttonCTA} from \"@observablehq/buttons\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W2c","stdlib":"1","titling":"auto"}} 29:"$28:body"