GameType = games$gameType, # add game type (regular season etc. Mutate(gamePk = games$gamePk, # add game id Tmp1 % mutate(playerType = paste0(playerType,row_number())) # Load schedule dataĭf_final % select(player.fullName,playerType) %>% mutate(eventCode = df_result$eventCode) Finally, we join it all together, add a few additional datapoints (game id, home team, away team etc.) and then join all the plays together into the master data frame and save it to the ‘plays.rds’ file. Scorer, Assist, DrewBy etc.) and then populate with the player’s name for each. Essentially we create a new column for each ‘role’ in a play (eg. What I did was consolidate all these individual tables into a single table (after adding the event code) and then using ‘tidy’ functions to spread each of them into one row so they can be joined the rest of the table. The player data is a bit more complicated, as it has several rows for each player, with a row for each player involved in the play and what their involvement was, like this: The ‘result’, ‘about’, ‘coordinates’, and ‘team’ data is pretty straightforward and we can just column bind into a single data frame with a single row for each play. The data needs a bit of extra parsing, so we collect it into several dataframes and then consolidate it. As before, I created a loop to loop through each game (all 11,292 of them) and download the JSON data. All this can be found at the ‘game’ API endpoint. This data has a wealth of information including all important plays (goals, shots, hits, penalties, takeaways, giveaways etc.), which players were involved and even where the play took place in the form of x and y coordinates. Now that we have the full schedule, let’s use it get all the play by play data sometimes called the Real Time Scoring System (RTSS) data for every game since the 2011-2012 season. Including the teams involved, the scores, team records, and venue information. In addition to the game id’s for each game, there is a host of other info Finally I save it to the ‘schedule.rds’įile. In 2011), so I set it as the start date and then use today’s date as the endĭate. Initially I thought that play by play data started in 2007 (it actually starts Simply put - its the most advanced and easiest to use scoring & stats program in hockey. If you want to post someones career stats, dont even bother asking. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. To do that we can access the ‘schedule’ endpoint in the API. A bad usage of the information here would be setting up a site that archives NHL logos. A tag already exists with the provided branch name. To start let’s load some packages library(dplyr)Īll the play by play and shift data we will need a list of game ids to use in This data will be the basis of my attempts to build some more advanced models to understand Adjusted Plus Minus and WAR/GAR.Īs usual, all my code and data for this exercise I’ve uploaded to my GitHub. For this post I’d share how I was able to use a similar approach to get all the play by play and shift data from 2011 onward. In my last post I showed how I was able to quickly and easily grab all the game stats for every NHL player using R. You can find team data, player data, and all sorts of game data. ![]() The NHL API is a fantastic, free resource for all sorts of NHL data. ![]() Reading Time: 5 minutes Photo by Mika Baumeister on Unsplash getResponseCode () BufferedReader in = new BufferedReader ( new InputStreamReader ( con. This project is inspired by the R package nhlscrapr, an all around must for NHL analytics geeks and. The library hides the guts of the NHL website scraping process and encapsulates not only the data gathering, but data output. setRequestMethod ( "GET" ) int responseCode = con. Provide a Python API for accessing NHL game data including play by play, game summaries, player stats et c. The Gold Standard for advanced European Hockey Data. Var headers = " ) HttpURLConnection con = ( HttpURLConnection ) obj. Advanced Video Analytics & Data for GMs, Coaches, Analysts and Scouts. H 'Accept: application/json' GET HTTP / 1.1 Host : Stay up-to-date with the latest hockey updates, stats, and analysis - your one. Select a language for code samples from the tabs above or the mobile navigation menu.ĭocumenting the publicly accessible portions of the NHL API. NHL Starting Goalies, Line Combinations, NHL News, Opinions, and Editorials. Scroll down for code samples, example requests and responses.
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