2013 College Football Modeling: Week 14 Viewing Guide

Little late, happy Thanksgiving!

• As always
• Watchability measures how good the teams are and how likely the game is to be close (Way more detail on what Watchability here)
• The more green a team is shaded, the better its chance to win; the more red, the worse
• Ranking (when listed) is this week's BCS ranking
• All times Pacific

2013 College Football Modeling: Week 13 Viewing Guide

Early post this week as i'll be otherwise occupied in Vegas the rest of the week

• As always
• Watchability measures how good the teams are and how likely the game is to be close (Way more detail on what Watchability here)
• The more green a team is shaded, the better its chance to win; the more red, the worse
• Ranking (when listed) is this week's BCS ranking
• All times Pacific

2013 CFB Modeling: Week 12 Game by Game Predictor

• Predictor has been updated with current data.
• As per usual:
• Type any FBS team into the box and the table will populate with 
• Games
• Past outcomes 
• Future win probabilities 
• Team's ranking each week (according to the model) 
• Scenario analysis
• Graph of expected total regular season wins

Please let me know if you have any questions or find any scheduling/outcomes errors.

2013 College Football Modeling: Week 12 Viewing Guide

Sorry for the late post! 

• As always
• Watchability measures how good the teams are and how likely the game is to be close (Way more detail on what Watchability here)
• The more green a team is shaded, the better its chance to win; the more red, the worse
• Ranking (when listed) is this week's BCS ranking
• All times Pacific

2013 CFB Modeling: Week 11 Game by Game Predictor

Oh Oregon. Is there going to come a year you don't choke up a game? I guess the "Helmet Symbol stands for National Championships" joke is good for another year :)

• Predictor has been updated with current data.
• As per usual:
• Type any FBS team into the box and the table will populate with 
• Games
• Past outcomes 
• Future win probabilities 
• Team's ranking each week (according to the model) 
• Scenario analysis
• Graph of expected total regular season wins

Please let me know if you have any questions or find any scheduling/outcomes errors.

2013 College Football Modeling: Week 11 Viewing Guide

This Thursday in college football has been circled on my calendar for a long time. When we look back at the 2013 college football regular season, there will have been roughly 20 games with Watchability rating greater than 70. 

There are two such games tonight. 

In two huge games with massive BCS implications, Baylor has the chance to show that they belong with Bama/Oregon/FSU/OhioState, and Oregon has the chance to say to FSU "We scoff at your wins over Clemson and Miami (Fl), beat a real top ten team then come see us."

Also this week, there's a game between Alabama and LSU with some BCS implications of its own. The model thinks Bama winning handily is a pretty likely outcome so it's not so high on the Watchability.

• As always
• Watchability measures how good the teams are and how likely the game is to be close (Way more detail on what Watchability here)
• The more green a team is shaded, the better its chance to win; the more red, the worse
• Ranking (when listed) is this week's BCS ranking
• All times Pacific
• Same chart sorted by Watchability here

2013 CFB Modeling: Week 10 Game by Game Predictor

I appreciate everyone's patience in my taking the week off to focus on getting that last exam push in. I felt like the exam went alright, fingers crossed I passed (pass rate is only ~50%).

The model has had a grim view of Miami all season, rating them only as high as #21 and dropping them to #32 after those nonsense performances vs. UNC and Wake. The idea that they were ever a #7 team was reeeediculous. Anyway, I expect after they drop 2 of the next 4 the AP voters will come to agree with my model's assessment. 

•  Predictor has been updated with current data.
• As per usual:
• Type any FBS team into the box and the table will populate with 
• Games
• Past outcomes 
• Future win probabilities 
• Team's ranking each week (according to the model) 
• Scenario analysis
• Graph of expected total regular season wins

Please let me know if you have any questions or find any scheduling/outcomes errors.