However, it seems so difficult to win your pool. You don’t have time to study up on Southern Miss at Louisiana Lafayette to assign the proper confidence points.
I have a better way for you: The Power Rank 2016 Bowl Season Cheat Sheet. It has predictions for the point spread and total points in each game.
The predictions combine data from a number of sources such as game results and the markets. They have predicted the winner in 73.8% (525-186) of games this season. This record only contains games between two FBS teams and doesn’t include games against FCS cupcakes.
Won a couple bowl pick’em tourneys this year with help from your predictions. The pools I entered were confidence point based and were also against the spread picks. TCU sealed the deal for me in both pools .. I’m a happy member!
Anthony, 2015 season, current member of The Power Rank.
The cheat sheet also ranks games by win probability for people who need to assign confidence points to the winner of games in their pool. In addition, it contains notes on match ups and injuries for each bowl game.
To get The Power Rank 2016 Bowl Season Cheat Sheet, click here.
How a Stanford Ph.D. got into Football Analytics
While I’ve been a crazy fan my entire life, I never expected to work in the sports world. After getting my Ph.D. from Stanford in chemical engineering, I was one of many in search of an academic job.
That changed in 2008. I was reading the paper on Google’s PageRank algorithm and realized all of its similarities with my research. This inspired me to develop a new method for ranking teams.
I worked out some NFL rankings and sent an email to my friends. Enough of them were intrigued for me to explore other sports. It became an obsession, and I found a way to quit my day job to devote all my time to The Power Rank.
In January of 2013, I predicted Alabama would beat Notre Dame on the cover of Sports Illustrated. They called me their analytics expert.
Now, I’m a college football columnist for Bleacher Report, and I’ve contributed to Grantland, Deadspin and SB Nation among other media outlets. A FiveThirtyEight showed that my 2015 NCAA tournament predictions were the most accurate, and my numbers have also appeared on Business Week and CNBC among other media outlets.
— Dan St.Pierre (@DanStPierre9) December 31, 2014
Much better than the average sports analytics – maybe even 2 standard deviations better.
— Dr. Daniel Heller, Marin, CA.
How to rank sports teams
I want to tell you about the membership product that gives you access to my best football predictions and team pages.
But first, let’s take a look under the hood at the engine that drives these analytics.
The foundation of my football analytics is the ranking algorithm. I developed this method from my Ph.D. research at Stanford on the physics of molecules and the math of randomness.
Let’s look at how it ranks college football teams on offense and defense based on yards per play, a powerful efficiency metric.
- It gets the box score of every football game. For college football, this includes over 1400 games on the FBS and FCS level.
- The algorithm creates a network in which the offense and defense of each team are nodes and games are edges that connect the nodes. This was inspired by Google’s PageRank method, which brought order and insight to the complex world of web search.
- From this network, the method develops a set of equations to be solved. For college football in 2016, there are 506 equations (two for each of 253 teams) with 506 unknown variables.
The algorithm solves for the 506 variables simultaneously in college football. This is the key to accurately accounting for strength of schedule. Many other ranking systems do not do this.
- Finally, the variable for each team is transformed into a rating that gives an expected yards per play against an average team.
On every morning after a college or NFL game, my MacBook Air crunches the numbers. The resulting rankings allow me to make predictions for point spreads and totals.
How to instantly evaluate a game
A membership to The Power Rank offers more than just predictions. You also get insight into matchups.
This insight starts with rankings that break an offense or defense down into passing and rushing. Again, yards per play serves as the primary statistic.
It’s most useful to view these statistics for an offense next to an opposing defense. To explain how this works, this visual shows the rushing matchup between Ohio State and Oregon in the 2014 national title game.
For the defense rankings, the better units appear further to the right. This makes it easy to compare with the opposing offense.
The unit with the dot farthest to the right is predicted to have an advantage in the matchup, showing Ohio State’s advantage in the run game.
The team pages use this basic idea to look at matchups for offense against defense. For example, consider the matchup of Ohio State’s offense versus Oregon’s defense.
By looking at this visual, I was able to pick out Ohio State’s advantage in running the football. During the game, Ohio State running back Ezekiel Elliott gashed the Oregon defense for 246 yards on 6.8 yards per carry and 4 touchdowns.
My analysis of this mismatch appeared on Deadspin prior to the game. Here’s what a commenter said about the analysis.
It is the start of the fourth, and it is creepy how on point your predictions are.
— commenter on Deadspin
It doesn’t always work out this way. Football has too much much randomness to be right all the time. But analytics provides a firm baseline for your judgments about football.
Moreover, the team pages, which are updated the morning after any game, are interactive. Click on an opponent in the schedule to see the matchup visuals for a different game. To play with a sample team page, click here. It’s like having a cheat sheet that makes evaluating other teams easy.
Get the 2016 Bowl Season Cheat Sheet
Members of The Power Rank get the 2016 Bowl Season Cheat Sheet, which has spread and total predictions for all 40 bowl games. These are how the predictions have performed this season.
- Straight up, predicting winner of the game: 73.7% (525-187)
- Against the market spread: 50.9% (356-343 with 11 pushes)
- Against the market totals since week 7: 50.5% (198-194 with 6 pushes)
The cheat sheet also has games ranked by win probability for those in pools with confidence points. In addition, it has notes on match ups and injuries in each bowl game.
Members also have access to my NFL predictions for spreads and totals. These are how the prediction have done against the markets through week 14.
- NFL spread: 54.5% (108-90 with 10 pushes)
- NFL totals since week 8: 50.5% (50-49)
I spent a long time searching the web for analytics rather than picks. I finally found it with The Power Rank.
Your analytics provide an excellent foundation for determining the correct line. This assists me greatly with establishing my betting line for the week, and I’m able to adjust my line for non-objective factors knowing that objective factors have been taken into account.
I would recommend a membership to anyone in search of strong analytical reasoning and objective line determination.
— Jeff, Las Vegas, NV.
Members also get a pdf copy of my book How to win your NCAA tournament pool as well as my full bracket advice in March.
Please take up to 30 days to evaluate your membership. If you’re not satisfied for any reason, I will refund your money.
Get only the Bowl Season Cheat Sheet
To get a pdf of the cheat sheet for $39, click on “Get the 2016 Bowl Season Cheat Sheet.”
Get the 2016 Bowl Season Cheat Sheet.
Questions? You can email here or text me at 650-387-2336.