Popularity of Sports Leagues

Sports Leagues Popularity

As my bots continue to bring me data from all across the interwebs I am constantly thinking about interesting questions to ask it.

As I have been focused on numbers generated by various sports leagues I began to wonder about the popularity of these various leagues themselves…

(more…)

February 2019 Power Rankings

NBA Power Rankings February 2019

I have recently been inspired to write code of interest to the legal sports book industry again.  Disclaimer – I have nothing to do with placing bets, taking bets, money exchanges for bets, or anything else to do with actual betting.

What I am almost obsessed with is sports betting odds, probabilities, rankings, etc.  Of course when this kind of data is turned into information it can be of great value to the sports betting industry…

(more…)

The NBA PPR MoneyBall Edition

The NBA PPR – Money Ball Edition

The other day I re-wrote my NBA player ranking algorithm so that it was more commiserate with my current Python skills.  While my coding is significantly better, the basic idea was the same: take the available advanced analytics and determine who really are the most effective players in the NBA.

While I am more confident that this years version better identifies the best on court performances,  I realize it only tells part of the story.

With all apologies to my 15 year old self, basketball is a business.

To that end, I decided to see if I could identify the players that were the best values.  That is – what teams are paying vs. the return they are getting on the court.

(more…)

the best basketball players in the NBA

The Best 25 ( or so ) Players in the NBA 2018 and the 2018 NBA MVP

There is little doubt that advanced metrics have helped the Houston Rockets become the best team in the NBA so far in 2018.  In terms of how the team plays and was built, modern analytics have significantly contributed to their success.    In the spirit of celebrating NBA analytics I thought that I would compile as much advanced player evaluation data as I could to answer the un-answerable: Who is the best player in the NBA this year?

Most Valuable” is such a loaded term these days.  Everybody has their own idea about what makes an MVP.  Some people think it’s the best player on the best team.  Other people focus on old-timey, box score statistics like who’s scored the most points or gotten the most rebounds.  I’ve heard people focus on the word valuable as in this good team would not be good without player x because he adds the most value…

(more…)

Only 14 NBA Teams Matter Now. Okay, Would You Believe 4…

Due to my situationally forced absence from all things digital (nothing horrible, just a very difficult move + personal milestone) I have had allot of time to think.  I have re-written my Pigskin Prognosticator in Python over and over again in my head. When I got back at it for real however,  I went a little sideways.

After talking to my brother for days on end about the NCAA Tournament, I was in full hoops mode.  Since the tourney was wrapping up all I had left of interest was The Association.  So I once again attempted to get some good NBA data; which seems to be more difficult than obtaining reliable football data.  While not as rich as my NFL data source, I did manage to get my virtual hands on some solid NBA team data anyway.

(more…)