nba_api
nba-sql
nba_api | nba-sql | |
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55 | 14 | |
2,249 | 164 | |
- | - | |
7.1 | 4.5 | |
21 days ago | 21 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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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
nba-sql
- Shitpost(?) From Nov to Dec, Braun was trusted with 50% more minutes per game, (when he checked in at all), and it resulted in a 50% bump in fg pct.
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nba-sql - A SQL Database for the NBA
I've searched for a good database to analyze NBA players and teams, and couldn't find one. So, I've been working on an app that builds a SQLite / Postgres / MySQL database for the NBA. You can get the Windows alpha here: https://github.com/mpope9/nba-sql/releases/tag/v0.0.6 For OSX / Linux, you need to run it from the commandline. This is very much in the alpha phase, but development is happening at a steady pace in my free time. I've been able to learn some interesting things already, there are examples in the wiki here. I have more advanced example queries that I'm still working on, and have yet to add them to the wiki if any are interested. I'd love some feedback, if anyone has experience with SQL or databases. nba-sql will build a SQLite database by default, but it also supports Postgres and MySQL. You run the application to build the database, then use something like DBeaver to query it.
- Jalen Green Shot Attempts 2021-2022 Season [OC]
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How often has a playoff team done what Dallas did yesterday?
This is what I've found - https://github.com/mpope9/nba-sql
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Steph Curry's Shot Distance Relative To Seconds Left In Game / Period
I used the nba-sql database for this. That database has a table called shot_chart_detail. The table has alot of interesting data, but there are a few columns that are especially helpful: minutes_remaining, seconds_remaining, and shot_distance. Using those columns, the following graph can be made:
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nba-sql: v0.0.4 - Alpha Windows Client Release!
Thanks! I used Postgres and Apache Superset. I wrote a small wiki on how to use it https://github.com/mpope9/nba-sql/wiki/Data-Visualization-with-Superset. Superset doesn't work with SQLite sadly.
- nba-sql: A NBA database from the 1996-97 season until now
- nba-sql: A Postgres Database for NBA Data.
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nba-sql: v0.0.2 Release
The latest Postgres dump can be found here: https://github.com/mpope9/nba-sql/releases/tag/v0.0.2. It is a compressed file, using xz. After decompressing it, you can run it using psql -U -P nba < nba.sql.
- nba-sql: A Relational NBA Database
What are some alternatives?
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espn-api - ESPN Fantasy API! (Football, Basketball)
nba-stats-analysis - Jupyter Notebooks with Applications of Data Science and Analysis with NBA data, using the information available through the NBA Stats API.
pydfs-lineup-optimizer - Daily Fantasy Sports lineup optimzer for all popular daily fantasy sports sites
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.
superset - Apache Superset is a Data Visualization and Data Exploration Platform
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.
hoopR - An R package to quickly obtain clean and tidy men's basketball play by play data.
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.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production