Before the ball tipped off on the 2026-27 NBA regular season, we published our full 30-team win projections and conference standings generated by our proprietary quantitative models. Unlike traditional power rankings driven by offseason headlines and superstar name recognition, our system evaluates how a team’s entire 10-man rotation (from starting backcourt efficiency and wing spacing […]
Usually, we project total team wins based on the first few weeks of the given NBA season. This year, we wanted to try something different by projecting the number of wins each team will have just based on what we know about them before the beginning of the season. Every NBA offseason brings a wave […]
We have designed and implemented a new machine learning model that projects the total number of wins for each team in a given season. We will update this each day. As of: Wednesday, August 13, 2025 Team Projected Wins (+/-4 Wins) Philadelphia Phillies 95 Milwaukee Brewers 92 Boston Red Sox 90 Los Angeles Dodgers 89 […]
Updated: March 17, 2025 Based on our ML algorithm as previously described here: https://relativitydigest.com/2024/12/28/nba-2024-2025-win-predictions/ Our updated win projections for the season are as follows (all predictions +/- 5 Wins) Team Predicted Total Wins (+/- 5) CLE 58 OKC 57 BOS 53 LAL 52 MIL 51 MIN 50 NYK 48 IND 48 MEM 48 LAC 47 […]
Below, are the predicted NBA team wins for the 2024-2025 seasons (within a margin of error of +/- 5 wins) based on our novel ML algorithm to predict team wins. We collected over 20 years of NBA team data and applied advanced nonparametric, nonlinear models to uncover the relationship between various performance indicators and a […]
Using a lot of data wrangling and NLP, I created a movie and tv show recommender: Basically, the user selects from the drop-down list their movie/tv show of interest, and the algorithm will recommend a combination of movies and tv shows that the user is most likely to be interested in. I tried to include […]
In this post, I attempt to investigate the distribution of prime numbers and the famous Riemann hypothesis.
In the video below, I explain how to derive Kaluza Klein action which occurs from generalizing the Einstein-Hilbert action to five dimensions. The grand implication of this is that gravity and electromagnetism are unified!
Many textbooks when introducing ordinary least squares as a method to do regression (usually via introducing linear regression) don’t explain / derive the coefficients. Here, I explain how to do it using tensor/index notation.
