nba_api
hoopR
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| nba_api | hoopR | |
|---|---|---|
| 55 | 6 | |
| 2,238 | 77 | |
| - | - | |
| 7.1 | 7.6 | |
| 13 days ago | 3 months ago | |
| Python | R | |
| MIT License | GNU General Public License v3.0 or later |
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nba_api
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An Analysis of How Chris Paul Has Affected His Teams (And How It May Impact the Warriors)
Thanks to the people putting together the open source nba_api, as well as the people at Basketball Reference and the NBA stats page.
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Stat Changes from Regular Season to Playoffs: 2022 - 2023 Season
NBA Stats API
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Scott Foster gets cracked in the face by Lebron. And Foster has his whistle in his mouth when it happens.
Yea ref stuff is hard to acquire. NBA api could b helpful tho and this is prob a good place to start
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NBA Game IDs to Playoff Game Numbers
I think you'll find this useful: https://github.com/swar/nba_api.
- Experiences with the different nba.com APIs? Which one would you recommend for play-by-play data to calculate player-specific ORtg or DRtg in a game?
- Don't have much experience using APIs, I'm trying to use one but do not know how to get it set up properly
- Trying to use an API in Python but I don't know how to set it up properly. Can I get some help?
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[OC] How does playoff basketball differ from the regular season? Analyzing team stats over the past 40 seasons
All data were collected using the nba_api. The dataset consists of per-game stat averages for all teams starting from the 1983-84 season through the 2021-22 season. In total: 1103 regular season teams, 624 of which made the playoffs in their respective years. Traditional stats include: PTS, FGM, FGA, FG_PCT, FG3M, FG3A, FG3_PCT, FTM, FTA, FT_PCT, OREB, DREB, REB, AST, STL, BLK, TOV, PF, PLUS_MINUS. Advanced stats include: NET_RATING, OFF_RATING, DEF_RATING, EFG_PCT, TS_PCT, PACE, OREB_PCT, DREB_PCT, REB_PCT, AST_PCT, AST_TO, AST_RATIO, TM_TOV_PCT. Note: for plus/minus and all of the advanced stats, I could only get data beginning from the 1997-98 season onwards, which resulted in 743 total regular season teams, 400 of which made the playoffs.
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Downloading stats from nba.com/stats
Is it not on the nba api? https://github.com/swar/nba_api/tree/master/docs/nba_api/stats/endpoints
- [Highlight] Poole gets a tech for passing the ball to the ref
hoopR
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Schedule Sheet Mon 2/27
Thankfully, I've made use of the hoopR package which lets me get data that is up to date, primarily by pulling info from ESPN's APIs. While that does most of the work, there's tweaking that I need to do (most particularly for streamed game broadcasts that aren't ESPN3/ESPN+) but it usually goes fairly swimmingly.
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Help!! Dataset required for Supervised Linear Regression | Learning purposes
hoopR (college and pro basketball)
- Resources for Sports Analytics
- NBA individual player stats for every game.
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Where Can I get Excel File for Regular Season Schedule?
https://github.com/saiemgilani/hoopR Digging around through here will probably help you find a csv which is easy to convert to excel
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An empirical analysis of the relationship between every NBA players' astrological sign and on-court performance in the 2020-2021 season.
Next, we’ll look at a few measures of performance on the court to see whether certain signs are better or worse suited to particular aspects of the game. For each of these, I took player box score statistics (sourced from https://github.com/saiemgilani/hoopR), grouped them by the player’s astrological sign, and calculated their average numbers through the 2020-21 season. First, we’ll look at scoring -- the chart below shows each sign’s average points per game.
What are some alternatives?
nbastatR - NBA Stats API Wrapper and more for R
ImportJSON - Import JSON into Google Sheets, this library adds various ImportJSON functions to your spreadsheet
sportsipy - A free sports API written for python
nba-stats-analysis - Jupyter Notebooks with Applications of Data Science and Analysis with NBA data, using the information available through the NBA Stats API.
ncaahoopR - An R package for working with NCAA Basketball Play-by-Play Data
Python-NSE-Option-Chain-Analyzer - The NSE has a website which displays the option chain in near real-time. This program retrieves this data from the NSE site and then generates useful analysis of the Option Chain for the specified Index or Stock. It also continuously refreshes the Option Chain and visually displays the trend in various indicators useful for Technical Analysis.
nba-sql - :basketball: An application to build an NBA database backed by MySQL, Postgres, or SQLite
NBA-attendance-prediction - Attendance prediction tool for NBA games using machine learning. Full pipeline implemented in Python from data ingestion to prediction. Attained mean absolute error of around 800 people (about 5% capacity) on test set.
Basketball_Analytics - Repository which contains various scripts and work with various basketball statistics
td-ameritrade-python-api - Unofficial Python API client library for TD Ameritrade. This library allows for easy access of the Standard API and allows users to build data pipelines for the Streaming API.
mlbplotR - R package to easily plot MLB logos