Remember back 2 months ago when I asked for some help with a class project? After following the exact same path as before, I procrastinated my way into a couple of late nights this week to complete my project. This is definitely a first cut at this, with many improvements to be made before the season starts. I'll give you a few highlights of my findings, with a full report this weekend, after I've actually written my report for class.
- I used 2003-2006 stats as the basis of my model. I then predicted 2007 based on probabilities found in the previous 4 years.
- I used an average of the previous 7 weeks data to estimate what each team would do the next week. Anything beyond 7 weeks was not significant.
- I used Home/Away, Time of Year, Day of Week, and Opponent Group (Division, Conference, Non-Conference) as my Non-Mathematical stats. I may try to incorporate weather as well, but did not have time, and only found a site with the information a few days ago.
Here's what I found out from 2007:
- The Predictor was right 56% of the time, which is great for an initial stab at this. Anything over 50% was going to be a victory for me. I'll have all summer to tweak and make it better.
- It got even better once we exclusively used stats from 2007 (week 7 on). It was correct 62% of the time at the end of the year.
- I tested out 4 teams individually:
- Colts: 7-9 (Lots of room for improvement)
- Redskins: 11-5 (Only predicted against them 4 times)
- Giants: 10-6 (Started 1-5, finished 9-1)
- Patriots: 12-4 (Picked the Colts to beat them, as they should have)
- Colts: 7-9 (Lots of room for improvement)
- The four factors that caused the probability of winning to move the most:
- Rushing Attempts
- Rushing Yards
- Turnovers
- Time of Possession
Again, I haven't written up the full report yet, which is the project for tomorrow night. If anyone is interesting in reading it, just shoot me an email. As I keep updating it throughout the summer, I'll keep you posted on how it is improving. My goal is 70% before the season starts.