About me

Hello, I'm Professor MJ! Nice to meet you!
I'm a statistics professor from Canada. Holding a PhD in statistics has helped me tremendously over the course of my gambling career. When making predictions, I use several statistical models to come up with a projection. Then, I adjust that projection to account for factors like injuries or back-to-back games (since it's hard to incorporate this kind of information in a model based on numbers only).
In other words, my general approach consists of combining numbers with my own knowledge (about certain things that definitely affect the likelihood of an event).
Money is not everything in life. Family is extremely important to me. I'm very proud to be the father of two young boys: Mavrik (6 years old) and Jay (5 years old). Do you understand now where the "MJ" comes from (in "David MJ")?
What's the main goal of this website? To help you. That's it! I want to help as many people around the world get better at NBA betting. Whether through my projections/picks, or my informative articles, the goal remains the same.
How did I first get involved in the online sports gambling business? For one simple reason: arbitrage betting.
What is arbitrage betting? In sports gambling, an arbitrage opportunity occurs when the odds from two different sportsbooks differ so much that the bettor can bet on Team A in the first casino and bet on Team B in the second casino with a guarantee to make a net profit after the game.
If you are interested in learning more from my story related to sports arbitrage, click here. On this page you will learn about a great anecdote (a description of my biggest gain on a single game over the 3-year period where my life was truly centered around sports arbitrage).
I began doing research involving statistics and sports in the summer of 2000. Back then, I was an undergraduate statistics student.
It was just an ordinary morning and I went to check my emails before going to class. I was getting all kinds of unimportant/uninteresting emails every day, so I was quick to delete them.
I received a specific message that I came very close to deleting: it was mentioning a professor in Vancouver looking for a student to work on a research project during the summer. I thought "Vancouver is way too far for me (a 6-hour flight), and my spoken English is bad, so forget it".
Just before I clicked the "Delete" button, I realized that the project involved modeling NBA and MLB (Major League Baseball) games. That sounded pretty interesting!
So I decided to keep the message and think about it. I figured it was an occasion to immerse myself in an English environment, while working on something that really excites me.
A few days later I applied for the job and got it. I had no idea it was the beginning of a wild adventure. I'm so glad I did not delete this email. I have been doing research about stats & sports since then.
As a Master's student, my thesis was about cricket (a sport I knew nothing about, but that resembles baseball on several aspects).
As a PhD student, there was no way I could work on such projects, but I still did it on the side. Finally, when I became professor in 2007 I gained the liberty of choosing my topics.
I have published articles about the following topics:
"Strategies for Pulling the Goalie in Hockey". This one got quite a bit of media attention (you can google it, if you wish). I even got a phone call from two NHL general managers to discuss the content. The main conclusion of the paper was that teams should pull their goalie more early, and in more situations. Coincidence or not, coaches have been pulling their goalie much earlier than they were before the publication of this article.
"Various Applications to a More Realistic Baseball Simulator". In simple terms, this project involved programming a baseball game simulator, where each at-bat is simulated according to the batter's and pitcher's statistics. This tool allowed me to study three things: 1) I introduced a new measure of the ability of a batter/pitcher (instead of having to look at several statistics to get an idea of how good a player is); 2) I was able to assess some in-play strategies like base-stealing and bunting (should you do it in specific situations?); 3) I found the optimal batting order for the 2009 New York Yankees (the order that maximizes the number of runs scored).
"Biased Penalty Calls in the National Hockey League". We show strong evidence that penalties in the NHL are not called randomly at all. Referees do tend to be biased. More specifically, they call more penalties to the team that's currently leading. They also call more penalties to the team that has gotten less power play occasions so far in the game (trying to "even things out"). We also ranked referees according to how biased they were.
"A Computationally Intensive Ranking System for Paired Comparison Data" It introduces a new simple and intuitive method for rankings all 351 teams (which is a hard task because they don't all play each other!).
"Prediction of the margin of victory only from team rankings for regular season games in NCAA men's basketball" This article focuses on predicting the margin of victory of NCAA regular season games (most people only focus on March Madness games).
Professor MJ