Blog Update Just a quick update to the blog. I had done a quick update last week that I have been posting daily win projections on Twitter for NCAA Division I Top 25 teams for at least a couple of weeks now.
So here we are, the Final Four of the National Football League. At this point, there isn’t much in the way of surprise with the teams that have made it to this point. You have the two best teams in both conferences
Quick Blog Update All of the work I’ve been doing coding these predictions for the NFL and College Bowl games is leading up to my one true passion, college basketball. I now have the code and the pipeline to make predictions on
It’s the last week of the NFL Regular Season, and there is so much that needs to be decided especially in the AFC. I thought about doing a post on the different playoff and seeding scenarios, but it honestly is headache-inducing. People
For the first week of the 2018 College Bowl Season (December 15th-21st) there were eleven bowls played, and my model predicted correct outcomes on nine of those games. The second week (December 22nd-28th) was way more brutal for me. There were twelve
Blog Updates I made the comment on my LinkedIn post that I was horribly wrong with how many points the Baltimore defense was going to score in last night’s game. My model had them with zero points when they ended up scoring
Blog Update A little bit of a change in plans this weekend. Last week I posted odds for the first week of College Bowl Games through today, December 21st and had originally planned on posting the Week 2 predictions on Saturday the
Today is the beginning of the FBS College Bowl season with six bowl games playing today. I spent an afternoon about a week ago scraping win-loss stats on college football games so decided to apply the original model I had used on
So…about Derrick Henry… Before I start, just want to say…not a huge fan of WordPress 5.0. It’s really rather aggravating. And I just realized I don’t know how to move between “visual” and “text” anymore. Just great! All right, so if you
Last week was my first try at using the statsmodels in Python to try and predict winners for NFL games and compare them against Money Line odds found on Pinnacle. If we use 50% as the threshold between winning and losing a