domhttpx
nba_api
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domhttpx | nba_api | |
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1 | 55 | |
65 | 2,198 | |
- | - | |
3.6 | 7.7 | |
over 2 years ago | about 2 months ago | |
Python | Python | |
MIT License | MIT License |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
domhttpx
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About me | #FirstPost
domhttpx - google search engine dorker with HTTP toolkit built with python, can make it easier for you to find many URLs/IPs at once with fast time.
nba_api
- Don't have much experience using APIs, I'm trying to use one but do not know how to get it set up properly
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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.
- [OC] I Hate Traditional Rebounding Stats, So I Made My Own (A.K.A. Who Are the Most Selfless/Selfish Rebounders)
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Create custom league using API
I asked in another sub, and someone shared a couple of Phyton libraries (this and this) but this all looks gibberish to me. The dream would be to find a programming student/beginner to take on this as a fun side project.
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Where do fantasy sites get their live stats from?
I found this so it appears so https://github.com/swar/nba_api although it seems kinda unreliable
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IMPORTHTML/IMPORTXML workaround for stats.nba.com in 2021?
I've found an endpoint here that has the parameter I'm specifically looking for ("CloseDefDistRange"). But the URL always times out.
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Weekly Friday Self-Promotion and Fan Art Thread
I am a mathematician and data scientist that has always loved basketball. I recently stumbled upon a Python API to get data from the NBA Stats website (https://github.com/swar/nba_api).
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New NBA dataset on Kaggle! - Every game 60,000+ (1946-2021) w/ box scores, line scores, series info, and more - every player 4500+ w/ draft data, career stats, biometrics, and more - and every team (30 w/ franchise histories, coaches/staffing, and more). Updated daily, with plans for expansion!
The data is from stats.nba.com via the nba_api on GitHub. I compiled the data through an extraction script, and keep it updated daily via a fully automated Kaggle data pipeline. The pipeline is described here, and the project repository is here
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New NBA dataset on Kaggle! - Every game 60,000+ (1946-2021) w/ box scores, line scores, series info, and more - every player 4500+ w/ draft data, career stats, biometrics, and more - and every team 30 w/ franchise histories, coaches/staffing, and more. Updated daily, with plans for expansion!
If anyone has a solid data source, similar to the nba_api on GitHub I'd be happy to help create a NFL dataset!
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
nba-stats-analysis - Jupyter Notebooks with Applications of Data Science and Analysis with NBA data, using the information available through the NBA Stats API.
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.
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.
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.
nba-sql - :basketball: An application to build an NBA database backed by MySQL, Postgres, or SQLite
pyracing - A complete overhaul of the original ir_webstats; pyracing is an API client/wrapper for iRacing, the leading online simracing service. pyracing handles the queries to iRacing's (known) URL endpoints and maps the returned JSON data into structured objects, allowing for easier access to the data.
vsphere-automation-sdk-python - Python samples, language bindings, and API reference documentation for vSphere, VMC, and NSX-T using the VMware REST API
sports-analytics - Data collection, processing, visualization, modeling, and ideation in the space of sports analytics
hoopR - An R package to quickly obtain clean and tidy men's basketball play by play data.
Basketball_Analytics - Repository which contains various scripts and work with various basketball statistics