But conventional wisdom says that it is a difficult time for finding an edge. Every gambler in the world has 82 or more games of statistics and video on each team. These guys have dissected the tendencies of any player that has stepped on an NBA court for more that 5 minutes.

However, there is a simple winning strategy in the NBA playoffs: bet on the home team.

Home Court Advantage in the NBA Playoffs

I stumbled upon this edge by accident.

I was looking at home court advantage in the NBA playoffs versus the regular season. This analysis requires a little finesse in the playoffs since the better team can play more home games. Over the last 10 years, home court advantage has been greater in the playoffs (4.5 points) than in the regular season (3.2 points). The visual above shows these results, and my post over at the Wages of Wins journal has all the details of the analysis.

Mike Beuoy of Betting Market Analytics saw the post and wondered whether the Vegas line adjusted for this larger home court advantage in the playoffs. He found that the line has favored home teams by a half a point more in the playoffs than the regular season over the last 10 seasons. This 0.5 points is much smaller than the actual 1.3 point discrepancy.

How to win 53.5% of the time over 683 games

This suggests that there might be an edge. Sure enough, Mike did a database search over at SportsDataBase.com to show that betting on the home team has won 53.5% of games since the 2004 through April 24, 2013. (Clicking on the link will give you up updated win percentage.)

The uncertainty in this win rate over 683 games is about 2%, so it’s not certain that this strategy wins greater than 52.4% of the time. However, a simple analysis shows there is a 72% likelihood this strategy is profitable.

I have not double checked this calculation myself. And I would not dump my life savings into this betting strategy going forward. But this 53.5% win rate is an interesting curiosity from the increased home court advantage in the NBA playoffs.

If you have additional insight, please leave a comment below.

Thanks for reading.

Louisville’s Defensive Rebounding

With athletes like Chane Behanan and Gorgui Dieng, Louisville should rebound the ball extremely well. And they do on the offensive glass, pulling down 35% of rebounds compared with a 27.5% Division I average. However, Louisville is an average defensive rebounding team, allowing their opponents to grab 27.1% of rebounds. This could pose a problem against Wichita State, an excellent offensive rebounding team.

Why does Louisville have such a discrepancy between offensive and defensive rebounding? It could come from Louisville’s high pressure defense that forces turnovers. VCU is another team that plays this style of defense. They grabs 34% of offensive rebounds, confirming the athletic ability apparent from watching them play. However, VCU’s opponents get 29% of offensive rebounds, suggesting that a high pressure, pressing defense makes it difficult to grab defensive rebounds.

Wichita State’s Defense

Wichita State has allowed 91.2 points per 100 possessions, 36th best in the nation. However, when we adjust this raw number for strength of schedule, their defensive rank shoots up to 12th in the nation. This adjustment comes from the 9 of 10 Missouri Valley conference teams that have an offensive efficiency in the top half of Division I teams. The Shockers are predicted to allow 88.2 points per 100 possessions against an average team.

The Shockers are a tough team that slows the game down and control the boards. While The Power Rank gives Louisville a 6 point edge, Wichita State could prevail by getting hot early from 3 point range. Then their excellent defense could take over, preventing baskets and the opportunities for Louisville to set up the pressure defense. Moreover, Louisville is less likely to make up a deficit quickly, as they only shoot 32.7% (222nd in the nation) from 3 point range.

Syracuse’s Field Goal Shooting

From the raw statistics, Syracuse is not a good shooting team. From 2 point range, they hit 48.6% of their shots against Division I opponents, 125th in the nation. However, this doesn’t account for the strength of their schedule. In the Big East, 10 of 15 teams had a raw field goal percent defense in the top 100.

We use our ranking algorithm to adjust 2 point field goal percentage for strength of schedule. Syracuse moves up to 62nd in the nation. They’re not the best shooting team in the country. However, the Orangemen will get the job done if Michigan has one of their poor defensive games. The Power Rank has Michigan favored by about 2 points over Syracuse.

Win Probabilities

From our interactive bracket, the four teams have the following likelihood of winning the tourney.

• Louisville, 43.9%
• Michigan, 25.0%
• Syracuse, 17.5%
• Wichita State, 13.5%

What do you think? Let us know about your basketball insights in the comments below.

Thanks for reading.

In addition, Duke benefits from the shooting of Seth Curry, who most likely learned his soft touch from his father. Dell Curry played 17 season in the NBA. The list of current college players with NBA genetics extends from Juwan Howard Jr. at Detroit to Shawn Kemp Jr. at Washington.

How much more likely are you to play in Division I college basketball if your dad played in the NBA? Jon Wertheim of Sports Illustrated proposed this question to me. We dug into the numbers to find out.

The odds of playing college basketball

There are 347 Division I college basketball teams. Each team offers 13 scholarships. Hence, there are about 4,511 Division I college basketball players this year.

How does this compare with the pool of young men that could potentially play? There are 1.5 million young men that graduate from high school each year. Since anyone who graduated over the past 4 years could play on a current college team, this gives a pool of 6 million young men that could potentially play college basketball.

With 4,511 rosters spots from a pool of 6 million, there is a 1 in 1330 chance that a typical high school graduate plays college basketball.

The odds of playing college basketball if your dad played in the NBA

To determine the number of current college players with a father that played in the NBA, we simply count all the players. These 22 players are listed below. Clearly, this is an underestimate, as we might have missed some players. In fact, Jon and I missed Glenn Robinson III, one of the most well known players, in our first run through this list.

We also need the total number of college aged men with fathers that played in the NBA. Finding this number requires knowing the number of boys fathered by NBA players between 1990 and 1994. With the social habits of NBA stars, this is impossible.

However, we can make an educated guess about the number of college aged men with fathers who played in the NBA. Wikipedia lists a total of 4,699 players in the history of the NBA. Let’s assume that 1 in 10 of these players had a child between 1990 and 1994, giving a pool of 470 college aged young men.

Now, let’s be honest. 470 is an absurd overestimate. In 1990, the NBA only had 324 players total. However, that’s part of our strategy. We underestimate the actual number of college players but overestimate the pool of young men. This gives us a lower bound on the odds that a child of an NBA players makes a college basketball team. With 22 players from a pool of 470, the odds are 1 in 21, significantly higher than the population at large. The real odds could be as high as 1 in 10.

With these odds, you are at least 62 times more likely to play college basketball if your father played in the NBA.

Genetics makes it at least 62 times more likely to play college basketball

This number is astounding. To put this in perspective, our analysis was sent to a professor in population statistics from a prestigious west coast university. Along with some minor edits, he told us about the following result from his research.

Calculations I published in 1988 indicate that the average American male is about 12 percent more likely to pursue his father’s occupation than any other. The probability was somewhat higher for highly skilled professions.

If your father was a computer programmer, you are more than a 1.12 times more likely to become a computer programmer. For playing basketball, the factor is at least 62.

Clearly, genetics matter, from height to quickness to vertical jump. Of course, these young men grew up in families seeped in basketball. Their fathers most likely taught them the skills they need to make it to the college level.

List of current college players

Please let us know if we’re missing a player with a father who played in the NBA. I just added Ohio State’s Shannon Scott last night while watching their Sweet Sixteen game against Arizona.

• Tim Hardaway Jr. (father Tim Hardaway), Michigan.
• Glenn Robinson III (father Glenn Robinson), Michigan
• Jon Horford (father Tito Horford), Michigan
• David Stockton (father John Stockton), Gonzaga
• Alex Murphy (father Jay Murphy), Florida
• Erik Murphy (father Jay Murphy), Florida
• Seth Curry (father Dell Curry), Duke
• Traevon Jackson (father Jim Jackson), Wisconsin
• Shannon Scott (father Charlie Scott), Ohio State
• Phil Pressey (father Paul Pressey), Missouri
• Antoine Mason (father Anthony Mason), Niagara
• Ledrick Eackles (father Ledell Eackles), Oakland
• Austin Hollins (father Lionel Hollins, coach of Memphis Grizzlies), Minnesota
• Juwan Howard Jr. (father Juwan Howard), Detroit
• Nick Kellogg (father Clark Kellogg), Ohio
• Shawn Kemp Jr. (father Shawn Kemp), Washington
• Ricky Kreklow (father Wayne Kreklow), California
• Tyler Les (father Jim Les), UC Davis
• Dwayne Polee II (father Dwayne Polee), San Diego State
• John Wilkins (father Jeff Wilkins), Illinois State
• Renaldo Woolridge (father Orlando Woolridge), USC
• Sam Cassell Jr. (father Sam Cassell), Chipola Junior College, ineligible at Maryland

Thanks for reading.

Crowd Sourcing for More College Players

Of course we didn’t get all college basketball players with a father who played in the NBA. These are additional players pointed out by our readers in the comments.

• Madut Bol (father Manute Bol), Southern. Thanks, Curtis.
• Nick Wiggins (father Mitchell Wiggins), Wichita State. Thanks, Josh on Twitter.

However, we couldn’t wait that long to see who would win the tourney. We took Jerry Palm’s bracket predictions from yesterday and calculated the win probabilities for each team to advance through each round. These odds are based on our college basketball team rankings, which give a win probability for each game.

We show these numbers in our interactive bracket (click here to open it up in a new tab). To unveil the win probabilities for a team to advance, hover over the team name. To discover the odds that a team wins a game, hover over the circle for that game.

Last year, Amy Nelson of SB Nation made this awesome video about our analytics and this interactive visualization.

You should draw your own conclusion from this year’s numbers. These 3 things jumped out at us.

Florida has largest chance of winning the tourney

What? The Gator team that has dropped 3 games in a weak SEC conference? The team that’s only 11th in the AP poll has a 12.8% chance of winning the tourney?

Florida is the top team in our college basketball rankings. Despite being more than a point and half better than even Indiana, they have lost 5 games this year because of their love affair with the 3 point shot. Over 40% of their shots come from behind the arc. Most nights, they shoot pretty well, hitting 38.4% of their 3′s for the season. However, they can also die by the 3.

Florida’s chance at winning the tourney would be even higher had Palm not put them in the Region of Death. The East region has Duke, Michigan and Syracuse in addition to Florida, all top 10 teams in The Power Rank. The committee takes geography into account when determining the bracket. Since most of the best college basketball teams are east of the Mississippi River, the bracket has regions of vastly differing strength.

Pittsburgh in the West

If the East is the Region of Death, then the West is the Region of Eternal Life. Due to geography considerations, the West has Gonzaga, New Mexico and Arizona as the top 3 seeds. While our numbers love Gonzaga (#3), New Mexico and Arizona are 19th and 15th respectively. One would expect the worst 2 and 3 seed to have a rank of 8th and 12th.

This unbalanced bracket opens the door for Pittsburgh, the 5 seed in the West. After an uncharacteristically poor season last year, the Panthers have surged back on the national scene with coach Jamie Dixon. Ranked 12th in The Power Rank, they have a 10.9% chance of making the Final 4 out of the West. It’s not as high as Gonzaga’s 25.3% chance, but it’s higher than most “experts” will give them.

First round upsets

The Madness of March starts that first Thursday (or Friday on a weird year) of the tourney when higher seeded teams get upset by double digit seeded teams. In Palm’s bracket, Oregon and Butler look most vulnerable.

Oregon has been overrated all year, rising to 19th in the most recent AP poll but only 49th in The Power Rank. They got exposed last night at Colorado, losing by 23. Wichita State has a 55% chance of upsetting Oregon in the first round.

Most people remember Butler for their consecutive championship game appearances from a few years back. However, this year’s team doesn’t have the same defensive toughness as those teams. Middle Tennessee State, who was our highest ranked team not to make last year’s tourney, has a 51% chance of knocking off Butler in the first round.

Interactive Bracket

What jumps out at you in our numbers? (Here’s that link to the interactive bracket again.) Let us know in the comments.

Thanks for reading.

Each year, Rivals assigns a rating or points value to each school that describes the talent of the players who signed a letter of intent. For Sports Illustrated, we developed a model that takes the Rivals ratings and predicts future team performance. To compare the rankings from this model with the preseason AP poll, we looked at which rankings better predicted the final AP poll.

The Rivals model did as good or better than the preseason AP poll on 46 out of 100 teams over the last 4 years. This is remarkable given the limited information the recruiting model has compared with the writers that vote in the AP poll.

To get the full story on SI.com, click here.

Before we count down the top 25 teams for 2013, we note the following about this regression model.

• The regression model has learned from the past by relating recruiting ratings to the team ratings from The Power Rank algorithm. For example, recruiting data from 2009 to 2012 were fit to The Power Rank’s results for the 2012 season. Our team ratings from the regular season have picked the winner in 62.8% of bowl games over the last 11 years, a better percentage than the Vegas line (62.2%). Part of the accuracy of the recruiting model depends on our team ratings.
• We used the final AP poll as the measuring stick for the accuracy of the Rivals model and the preseason AP poll. This poll has problems, as it strongly considers wins but almost ignores margin of victory. However, it was the most relevant measurement of team strength for a general college football audience.
• The 100 teams we looked at were the top 25 teams in the preseason AP poll over the last 4 years. This puts the recruiting model in a better light, since this set of teams didn’t include teams highly ranked by the recruiting model but outside the AP top 25. For example, the recruiting model had Auburn 7th heading into the 2012 season. The preseason AP poll had Auburn 28th, which more accurately predicted their disasterous season.

With the passing of National Signing Day 2013, we now have the Rivals ratings to predict the 2013 college football season. The predictions are based the past 8 years of team performance.

25. Stanford. The Cardinal only had 12 scholarships to offer incoming freshmen. Since the number of recruits directly affects the Rivals team rating, Stanford only had the 61st ranked class this year, a far cry from their 5th ranked class a season ago.

24. Miami (FL). Miami coach Al Golden can’t walk off campus without tripping over a highly touted high school player. However, impending NCAA sanctions made recruiting difficult this year, as they had the 44th best class, much worse than their 9th ranking a year ago.

23. Virginia Tech. Despite two down years, coach Frank Beamer still recruited the 22nd ranked class. The Hokies need QB Logan Thomas’s passing to improve or groom a better passer.

22. California. The Bears continue to recruit well despite the coaching change from Jeff Tedford to Sonny Dykes. However, this ranking is probably too high. The Cal offense will be learning a new spread system under Dykes, while the defense lost coordinator Clancy Pendergast to USC.

21. Washington. The Huskies have continually improved their recruiting rank over the last 4 year, rising from 28th in 2010 to 18th in 2013. Hopefully, some of the linemen recruiting during this time will give QB Keith Price better protection next season.

20. Nebraska. The Cornhuskers pulled in the 17th best class, by far the 3rd best class in the Big Ten. Unfortunately, Michigan and Ohio State were way ahead, and Nebraska has to travel to Ann Arbor this season.

19. South Carolina. With all the media chatter about the talent in Columbus and the draw dropping hits from Jadeveon Clowney, you might think South Carolina is a top 10 recruiting team. In reality, their 16th ranking in 2013 was their best over the last 4 seasons.

18. Tennessee. The Rivals model had the Vols 13th in the nation last season, which was way too high. With new coach Butch Jones taking over, this year’s 18th ranking is also probably too high.

17. Oregon. Over the last 4 years, the Rivals model has consistently underrated the Ducks. The preseason AP poll was more accurate each year. Will this continue after head coach Chip Kelly handed the program over to Mark Helfrich?

16. UCLA. In talent rich Southern California, the Bruins always recruit well. They finally lived up to that talent last season under first year head coach Jim Mora. Their 11th ranked class this year should continue this trajectory.

15. Texas A&M. New coach Kevin Sumlin is getting tons of credit for recruiting the 10th best class this year. Of course, it helps that Johnny Manziel (a 3 star recruit) led the Aggies to their best season in more than a decade.

14. Mississippi. The Rebels and coach Hugh Freeze had a magical signing day, landing two top 10 recruits on the offensive and defensive line. Their 7th ranking is by far their best since 2002. However, three of their rivals in the SEC west are ranked higher in these rankings.

13. Clemson. With their dramatic, come from behind win against LSU in the Chick-fil-A Bowl, the Tigers will surely be an overrated top 10 team in the preseason AP poll. This ranking in the teens seems more appropriate.

12. Oklahoma. In the past 12 years, the Sooners have recruited a top 10 class 7 times. However, none of these top 10 classes have occurred during the last 3 seasons. Coach Bob Stoops needs more talent on the defensive line to start contending for national titles again.

11. Texas. Even Mack Brown can’t recruit after 3 subpar seasons. The Longhorns had the 23rd ranked class, their worst since 2002. Their usually excellent defense really needs help after last season.

10. Georgia. How would the Bulldogs recruiting class would have fared if the coaches had told QB Aaron Murray to spike the ball during the waning moments of the SEC championship game? A win over Alabama would have landed Georgia in the national title game against Notre Dame. Instead, they had the 12th best class, a fine rank but the second worst for coach Mark Richt over the last 12 years.

9. Michigan. After a disasterous 3 seasons under Rich Rodriguez, Brady Hoke has turned around this program both on the field and recruiting trail. The Wolverines notched the 5th ranked class after finishing 7th last year. These are their two best ranked classes over the last 8 years.

8. USC. While we kept hearing about the defections from the Trojan’s class, no one mentioned that coach Lane Kiffin still had five 5 star recruits coming to campus, more than any other school (yes, even Alabama). Lack of talent will not be a problem for USC.

7. Auburn. Yes, feel free to call BS on this one. The Tigers continue to recruit well. But unless the next Cam Newton and Nick Fairley show up on campus this fall, Auburn will not return to elite status this season under new coach Gus Malzahn.

6. Florida State. Call BS on this one at your own risk. Despite disappointing loses to NC State and Florida this year, expect the talent rich Seminoles to exceed expectations next season.

5. LSU. It’s a bit shocking that top recruit Robert Nkemdiche picked Ole Miss over LSU. There’s more certainly in winning games in Baton Rouge. Still, coach Les Miles landed the 6th best class in the nation.

4. Notre Dame. The Fighting Irish took full advantage of their undefeated regular season and landed the 3rd best class in the nation. While we should expect Notre Dame to be good next year, 4th is probably too high.

3. Ohio State. The Buckeyes will not surprise anyone this year. In coach Urban Meyer’s first season, Ohio State started the year 18th in the preseason AP poll. Now, with an undefeated season and a 2nd ranked recruiting class, anything but a national title will be a disappointment.

2. Florida. Last year, first year coach Will Muschamp landed the 3rd ranked class despite finishing 7-6. Somehow, a 11-2 season this year got the Gators the 4th ranked class (although they did top the rankings before National Signing Day). Talent is never a problem at Florida.

1. Alabama. Duh. What did you expect? After going 7-6 in his first year at Alabama, coach Nick Saban still recruited the top ranked class in 2008. This started a streak of top ranked classes for Alabama in 5 of the last 6 years. The rest of the SEC should resort to a voodoo consultant to bring bad turnover luck to Alabama next season.

Outlook

No one should take these rankings too seriously. With the short season and the youth of the players involved, college football is incredibly difficult to predict during the preseason. And these rankings have their problems. There’s an incredibly high likelihood that Boise State will be better than the 60th best team in the nation next year.

However, these rankings are still useful, and not only because they are six months ahead of the preseason AP poll. As with all predictive analytics, use these rankings has a guide to help navigate expectations for next season.

Moreover, this is only the beginning of our preseason college football predictions. To keep up to date, sign up for our free email newsletter below.

Thanks for reading.

On his show yesterday, we talked about my Sports Illustrated article on the BCS title game between Alabama and Notre Dame. The article is on the cover of the magazine in the south, although it couldn’t beat out Michael Phelps nationwide. For me, these were the three highlights of being on the show:

• Not getting bashed by callers when I said that Alabama was 2nd in my rankings. (Oregon has the top spot.)
• Talking about Stanford’s Rose Bowl win and how the team rankings predicted the 6 point win.
• Saying “computer code” in an interview on college football.

And if a team is predicted to win by 1 point, they have a 52.4% chance of winning, not the 53% I mention on the show.

To listen to the show, click here.

A few weeks ago, I was in New York City to meet with Mallory Rubin and Ben Glicksman, the college football editors at SI.com. I had an idea for a Rose Bowl story. Earlier this season, I wrote a preview of the Stanford Oregon game based on statistics for drives when quarterbacks Marcus Mariota and Kevin Hogan had played. (Oregon’s Mariota would often be pulled when the Ducks built a huge lead; Stanford coach Shaw only had the sense to start Hogan late in the season.) I thought a similar analysis might be useful for the Rose Bowl. Hogan has now been Stanford’s quarterback for 5 games, and Wisconsin has shuffled through 3 quarterbacks this season.

When I sent them the numbers early last week, they liked the analysis but thought it overlapped too much with Stewart Mandel’s excellent article on Hogan. They suggested I base the preview on Wisconsin. It was not the feedback I was looking for on Christmas day. But it did prompt me to look at something I had been interested in all season: what happened to Wisconsin’s offensive line? The traditional strength of the Badgers had played so poorly the first two games of the season that their position coach was fired after two games on the job.

The analysis of Wisconsin’s rush offense became the center of my analysis of their offense. To read the full article, click here.

Unless you work for ESPN and the BCS contributes to your paycheck, the idea of allowing only two teams to play for the national championship is criminal.

And if you’re reading this numbers based blog, you probably know about the problems with the computer polls used in the BCS rankings.

First, only one of the six ranking systems gives enough details so that others can reproduce the results. The other five black boxes are shrouded in mystery.

Second, the BCS forbids the computers from using margin of victory in their calculations. It does not matter that a 33 point loss says something much different about a team than a 1 point loss. In the name of sportsmanship, the BCS will not give teams the incentive to run up the score.

Last, you may have even heard that Richard Billingsley, the man behind one computer poll, is not a mathematician. As he admitted to the authors of Death to the BCS, “I don’t even have a degree. I have a high school education. I never had calculus. I don’t even remember much about algebra.”

But it gets worse.

Why Strength of Schedule and Margin of Victory Matter

I wasn’t looking for a flaw in a BCS computer poll.

I was thinking about strength of schedule and margin of victory. In college football debates, most people agree that a ranking system should account for these factors. The intuition is obvious. Northern Illinois does not play the quality schedule that Alabama does. Oregon’s 24 point win over a solid Oregon State team says something much different about the Ducks than a 1 point win. However, no one has provided any quantitative evidence to support accounting for schedule strength and victory margin in rankings.

Bowl games at neutral sites provide a simple quantitative test for ranking systems: how often does the higher ranked team win each game? For a system that incorporates neither schedule strength and victory margin, rank teams by winning percentage. For a system that accounts for strength of schedule but not margin of victory, rank teams with the Colley Matrix of the BCS. Last, my rankings account for both.

I spent some time digging into the details of the Colley Matrix.

Colley Matrix does not consider the results of each game

It was easy to get mesmerized by the beautiful mathematics behind Colley’s method. His paper discusses Laplace’s die problem, a symmetric positive definite matrix and solving a linear system of equations. I spent the weekend telling my wife that if college football games had only winners and losers, this would be a dandy little ranking algorithm.

Then thinking back on the equations, it hit me.

The method does not care who a team loses to in ranking them. It considers the win loss record of each team and the number of games played between each pair of teams. However, the specifics of who won each game are not an input to Colley’s method.

Omitting specific game results in a ranking system is like disabling the guiding system on a missile. The technology will do its job, but it will not be that accurate.

You can check this yourself by reading the descriptions of equation 18 and 19 in Colley’s paper. It’s possible to solve for the rankings (equation 17) knowing only each team’s record and how many games each pair of teams played.

As a mathematician, I find this omission appalling. To see why, take Alabama in 2012 as an example. The Crimson Tide lost to Texas A&M, a respectable loss to another top 10 team. But the Colley Matrix does not account for this. Suppose Alabama beat Texas A&M but lost to a bad Florida Atlantic team. Since a top team almost never loses to a bad team, this bad loss should lower Alabama’s rank. It doesn’t.

You can check this with your own example. Wesley Colley has set up a page on which you can add and remove games and recalculate the rankings.

When I first discovered this omission in 2012, Stewart Mandel of Sports Illustrated suggested looking into whether this flawed computer poll was helping Kent State. The Golden Flashes were 11-1 heading in the MAC championship game and ranked 17th in the BCS. If they moved up to 16th or better, they would earn a BCS bowl bid.

Sure enough, the Colley Matrix had Kent State ranked 15th, the highest rank in any computer poll. It did not consider that their lone loss came at Kentucky, a 2-10 team that won zero SEC games that year. This flawed computer poll played a small role in placing Kent State 17th overall in the BCS rankings. I wrote about this on SI.com.

“Sam Feng’s article is a perfect example of anti-science”

In response to my article, I got this tweet the next day. Amidst a flurry of four letter words, a blogger blasted the mathematics behind my analysis of Colley’s method.

I disapprove of Feng because I don’t know what the f*$% he was doing, and I don’t think he knows what the f*$% he was doing either.

I guess that can happen when your writing jumps from a small blog to SI.com. At least he could get my name right.

I promptly replied to his post, and a conversation ensued about the details of the mathematics. In the end, the blogger verified my main conclusion that Colley omits the results of each game. The post started with a rant about “anti-science”. It progressed with a dense mathematical discussion in the comments. It ended with this in the last comment.

I’d rather have Ed’s rankings making the decisions than Colley’s or a roomful of NCAA bureaucrats.

The blogger still had a problem with the example I used in the article, a criticism with some merit. The example is equivalent to the Alabama scenario above. In exchanging the loss to Texas A&M for a loss to Florida Atlantic, the records of these two opponents change. Since the Colley Matrix does consider each team’s record, the rankings do change. However, Alabama’s rank does not change. This makes no sense when a team loses to a cupcake.

To be precise, one can show the rankings remain exactly the same under certain changes of wins and losses. For an example in 2012,

• Stanford beat Oregon
• Oregon beat Washington
• Washington beat Stanford

Suppose we change the result in each game.

• Oregon beat Stanford
• Washington beat Oregon
• Stanford beat Washington

Since all teams have the same record, the rankings stay exactly the same. Oregon would remain 7th despite losing to an average Washington team. It just doesn’t make sense.

However, for the sake of simplicity, I went with the example in which one team traded a loss for a win. At the end of the day, Colley’s method disregards massive amounts of useful information.

Northern Illinois busts the BCS.

Before the MAC championship game in 2012, Kent State threatened to bust the BCS with their ranking of 17th. However, their opponent, Northern Illinois, wasn’t too far behind at 21st.

After winning the championship game, Northern Illinois jumped to 15th in the final rankings to earn a BCS bowl game against Florida State. In the computers, the Huskies made massive jumps in the polls of Richard Billingsley and Peter Wolfe.

Billingsley does not describe this ranking method, so no one knows why he bumped Northern Illinois from 19th to 12th.

However, Peter Wolfe describes his method and even offers a few references for his Bradley-Terry model. This nice academic article by Keener describes the model in some detail, making it possible to reproduce the results. After carefully reading this paper, I didn’t find any problems with the ranking method. It does matter that Kent State lost to Kentucky. The math seems to favor teams that play an extra game, which most likely helped Northern Illinois jump from 23rd to 12th after their win over Kent State.

A Playoff on the Horizon

I didn’t think anything could make me hate the BCS more. I was wrong.

At least the current computer polls will be banished when a four team playoff arrives in 2014. A selection committee similar to the group that determines the field for the NCAA men’s basketball tournament will pick the four teams. I only hope their debates will be aided by better algorithms for ranking teams.

Thanks for reading.

Most of the headlines focus on Notre Dame’s defense. Led by linebacker Manti T’eo, the Fighting Irish have allowed 10.1 points per game, best in the nation. With the injury to USC quarterback Matt Barkley, Notre Dame’s defense will most likely have a good day.

But what about Notre Dame’s offense?

Notre Dame’s Offense

The raw statistics suggest Notre Dame has a poor offense. For example, the Fighting Irish pass for 211 yards per game, a number that includes negative yards from sacks. Their 74th ranking places them below average nationally.

However, total yards per game is a misleading statistic.

Yards per game depends on how many times a team throws the ball. Notre Dame doesn’t throw the ball as often as the spread offense of West Virginia. Using simple division, we divide total pass yards per game by the number of attempts to obtain a better metric of pass offense. Notre Dame averages 6.83 yards per pass attempt, 51st best in the nation.

Simple division turns a below average pass offense into an above average one.

Dividing total yards by the number of plays lets us account for the pace of the football game. It is analogous to the tempo free statistics that Dean Oliver introduced into basketball. Looking at points per possession shed a new light on offenses that didn’t fast break and looked for the best possible shot late in the shot clock. Yards per attempt is the first step in incorporating these ideas into football.

Match Up With USC’s Defense

At The Power Rank, we take yards per pass attempt and adjust it for strength of schedule. Since Notre Dame has played top pass defenses such as Stanford, Michigan State and Oklahoma, our algorithm bumps up their pass offense from 51st to 28th. Their rating of 7.04 gives a predicted yards per attempt against an average pass defense.

Below, we show how our adjusted numbers for Notre Dame’s offense match up with USC’s defense. A better defense has a blue dot further to the right. Then the unit with the dot further to the right is predicted to have the advantage in the match up. By overall yards per play, Notre Dame’s offense enjoys a slight advantage over USC’s disappointing defense.

These visuals appear on our interactive team pages, the heart of our premium college football product. For more information, click here.

Outlook

Our team rankings predict a very even game (USC by 0.3 points). However, these numbers reflect a USC team with quarterback Matt Barkley. The Vegas line has Notre Dame as a 6 point favorite.

Is the injury to Barkley worth 6 points? We’ll find out Saturday.

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Our teams rankings predict that Oregon will win by 3 touchdowns at home. This differs only slightly from the Vegas line of 20.5. But lumping an entire team into a single rating does not tell the entire story.

We have taken our team ranking algorithm and applied it to football specific statistics like yards per play. The result is rankings for offense and defense that account for strength of schedule. For Stanford, it separates an elite defense from an average offense. We also rank offense and defense for passing and rushing using yards per attempt.

It’s most convenient to consume these results in match up visuals. Below, we show the results for Stanford at Oregon. Better defenses have a blue dot further to the right. When shown next to an opposing offense, the unit with the dot further to the right is predicted to have an advantage.

These visuals let you instantly evaluate a game. Sports Illustrated used them in previewing Alabama and LSU two weeks ago in their November 5th issue. To learn more, click here.

What do they say about Oregon’s chances of staying undefeated?

When Oregon has the ball

Oregon’s offense scores so many points that head coach Chip Kelly often pulls his starters well before the end of the game. To account for this, we’ve combed through the play logs to identify drives in which the starters played. Through last week, we documented all the details in this post. For the blowout at California last weekend, we use plays until Oregon got the ball up 52-17 with 9:38 left in the 4th quarter.

These adjustments bump up Oregon’s offense in all categories. However, it may be surprising that Oregon’s pass offense ranks 21st. The last two weeks, quarterback Marcus Mariota has had two brilliant performances against USC and California. When we consider all the drives that Mariota has played this season, Oregon has not had an elite passing game. But a freshman can certainly improve over the season. A stand out game against Stanford’s 4th ranked pass defense will even convince our algorithm.

Can Stanford slow down the Ducks’ offense? They haven’t the last two years. But Stanford’s defense, led by linebackers Chase Thomas and Shane Skov, have made the leap to elite status this season. They must first slow down Oregon’s running game. Then they need to get pressure on Mariota when he drops back to throw. It’s a tall order, but Stanford has a better defense than any team Oregon has faced all year.

When Stanford has the ball

The visual shows the average play of Stanford’s offense this season. However, these season long numbers do not distinguish between the quarterback play of a nervous Josh Nunes versus a speedy Kevin Hogan. Head coach David Shaw gave the reigns to Hogan two weeks ago against Colorado.

When using drives with Hogan at quarterback, Stanford’s offense ranks 11th in the nation in adjusted yards per play. This is quite a contrast from their 47th rankings using all plays. Hogan has improved both the passing and rushing game:

• Pass offense: 40th to 8th.
• Rush offense: 55th to 15th.

Hogan has played against Colorado and Oregon State, the 112th and 30th ranked defenses by our numbers, the last two weeks.

However, two games does not offer a lot of data. While Stanford’s offense has most likely improved with Hogan, it’s far from certain the Cardinal are the 11th best offense in the nation. Look for the offense to score points against an Oregon defense riddled with injuries on the line and the secondary.

Oregon’s chance to remain undefeated

Our team rankings give Oregon an 87% chance to remain undefeated. But their injuries along the defensive line alone should worry Duck fans. The Vegas line started at 24 but dropped to 20.5. It might be a closer game than anyone expects.

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