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LG Hoops Advanced Metric 3.0
I have played around with various forms of machine learning and predictive algorithms to find the most accurate and logical NBA all-in-one advanced metric but have ran into a number of issues that caused me to re-think my process. I started to research different popular advanced metrics such as BPM, LEBRON, RAPTOR, and even PIE…
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LG Hoops Advanced Metric 2.0
Check out the most recently updated LG Hoops Advanced Metric! I’ve updated the logic to include Plus/Minus% and stats like deflections, along with cutting down on some more double-counted statistics. The stats are all pulled from the NBA API (the NBA website), and are considered free data. The metric is found through the use of…
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LG Hoops Advanced Metric 1.0
I have been playing around with Python (a programming language) and data manipulation tools to create my own LG Hoops advanced metric. This is my first version of my own metric which utilizes machine learning and theories such as ‘random forest’ (an algorithm technique) to project the overall value of each player. The stats leveraged…
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Top Low-Usage Shooters in the NBA
I love a good old stats query to find some trends/unique players and how they help their teams. One I recently ran is the top 10 players by TS% who are considered low usage (less than 10 FGA). Below are the results: These guys know how to score without high volume attempts – which is…
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NBA Net Rating Prediction
It’s simple – the past 10 years have shown us that the NBA Champion finishes within the top 5 in Net Rating. There’s always conversation about teams with vets or a collection of talent that will put it all together at the right time and make a huge run for the championship, but history tells…
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