First Post - How I Got Into This

I have been fascinated with the combination of statistics and sports since I was child. Growing up, I remember telling my friends, who were playing video games with me, not to touch the joystick while I wrote down the stats. In those days, about 1986, sports video games did not record the stats, so I did. It was a lot of work, and we only kept track of a small percentage of what people keep track of today, but we were still able to use these stats to, for example, select a video game tournament's MVP. Statistics would be very present in my thoughts also when I was playing a sport. After a basketball game I would know how many points, rebounds, and assists I had at any moment in time. Was this egotistical and selfish? No, a few times I would tell my friends how they performed on the game, and they would claim to have had many more rebounds or assists since the league recorded only the points. Indirectly or directly, I was always interested in having a way to rank players or teams, which brings me to this blog.

This blog is not written to give gambling tips nor an online sports wagering pick. nor do I encourage anybody to go into sports gambling based on these experiments. So, what will I be doing here? Basically, using different statistical measures for predicting outcomes of National Football League (NFL) games. By predicting outcomes, I mean, an estimate of the true spread, the number of points by which team A will beat team B. That is, instead of predicting that the score will be 20-13 in favor of A, I am only interested in predicting that A will beat B by 7. I will keep track of ten different ranking measures or ways to estimate NFL game outcomes. The ranking measures or published in this blog were obtained from published scientific journals, websites, and my own cooked up measures. This blog will help me to create an online notebook, keep track and compare the different estimator's performance on the 2006 NFL season outcomes.

Future Blogs
In my next few blogs, I will give an introduction and explanation to each of the statistical estimators and the different sports (NFL) wagering picks. Some of these estimators are the work of how other statisticians who published their work on well known statistical journals. The estimators vary based on the statistical methodology and the variables they use. For example, one estimator may base her decision solely on previous scores and home-court advantage, while another may take into consideration yards rushed, yards passed, interceptions, sacks and penalties. A statistical methodology used by one estimator may be a standard linear model, another might use a Bayesian approach, and one might use an ad hoc methodology like surveying free opinions from different websites. I will try to stay away from too many mathematical technicalities to explain how each estimator works, but for those savvy statistical readers, I will post references to scientific journal articles and websites for detailed explanations of each estimator. And after that, when the NFL 2006 season starts, watch weekly what these estimators predict and how much imaginary money they win or lose. Stay tuned!


siggy said…
Great job. I stumbled on your sight
back around week 2 of this year and found your picks to be solid week in week out. And you go and top it off with a 4-0. Excellent--keep up the good work.
siggy said…
I have a question for you. What made you choose Washington on Monday Night when your model showed Pittsburgh with the largest probability to win factor for the week?
siggy said…
Jamie will you be posting any playoff picks?
siggy said…
Jamie--it is almost that time again and hopefully the juices are flowing. Have you decided what you are going to do yet? Hope it is a positive. Talk soon--Jerry
siggy said…
Jamie--any insight on what you might do for the upcoming season? I for one am really looking forward to reading and possibly discussing your weekly selections. Thanks for the response.--Jerry