Testing Matchup Myth #1: the Rematch

Myth #1: It's hard to beat the same team twice in one season
Myth #2: You can throw out the records for a rivalry game

In this first edition of the two part series, I will be taking on myth #1.

Billy Sims and the Sooners would
get revenge and redemption

The principal idea seems to be that the winner of the first game has less to prove in round 2, is overconfident entering the game, and therefore does not prepare as well or play as hard. The game 1 loser is looking for revenge or redemption.

In modern-era college football, teams play a second time in a bowl game or conference championship game. This is important for two reasons: first, it means that the teams are relatively evenly matched; second, it means that there is a whole new set of motivational variables (e.g. if the team is happy or disappointed to be in that particular bowl game) that will dilute the importance of seeking revenge or redemption for the loser.

There is a second countervailing logic: the winner of the first game already divined a game plan that wins. The loser will need to reevaluate its game plan, and faces a degree of uncertainty that the game plan will be effective. In other words, if the two teams are otherwise evenly matched, the team that won the first game has a better chance of winning the second game precisely because it won the first game.

The Choke at Doak: 31-3 to 31-31; The 5th quarter
in the French Quarter was no better for Florida

So, let's look at the numbers. Since 1950, there have been 49 rematches in college football. (Florida State tied in game 1 in 1994 - the infamous Choke at Doak.) The average score in game 1 has been 29.5-16.4, and in game 2, 31.0-17.7. Home teams were 31-16-1 in game 1. Most game 2s were played on neutral fields; home teams were only 4-6.

Game 1 winners were 29-18 in second games (62%). Simplistically, 62% is less than 100%, so game 1 losers did better in game 2, but 62% is also more than 50%, so game 1 winners were still more likely to win game 2.

Thinking about this logically, the team that won the first game was probably the better team, and so we would expect them to win the second game more often than not. Based on their performance throughout the season, we would have expected game 1 winners to win 61% of game 2s. In reality, they won 62%. In other words, game 1 winners improved their chances of winning the rematch by 1 percentage point.

BYU/UCLA 2007

On average, game 1 winners won the rematch 26.4 to 22.5. We would have expected game 1 winners to win 26.6 to 22.0 on average. That means game 1 losers outplayed game 2 expectations by .79 points. Based on game 2 scores and a pythagorean-style win/loss adjustment, game 1 losers should have won 45% of game 2s, but they only won 38%. Game 2 losers played slightly better by the scoreboard, but they were unlucky when it came to actually winning games.

In conclusion, it is not hard to beat a team twice in the same season - winning or losing game 1 has no effect on winning or losing game 2. But it is hard to blow a team out twice in the same season. So Nebraska/Washington Part II might be closer than 55-21, but don't expect Washington to pull off the upset just because they lost the first time around.

The Myth of Home Field Advantage

Complete Home Field Advantage Statistics

About a year ago, in my most widely read and discussed post to date, I detailed the hard facts of home field advantage. I showed that it was small, isolated stadiums that gave their teams the most boost on the scoreboard and not the rocking behemoths that we love so much. But some people just couldn't handle the truth. I now return to the topic to show how I was right and they were wrong (so suck it Trebek) . . . but also how I was wrong and they were right, as Yoda would say, from a certain point of view.

First, we need to cover some facts. Since 1994, when playing FBS opponents, home teams have won 60% of the time and have outscored their opponents by an average of about 10.5 points. In part, this is because lesser programs often take paychecks to travel and play bigger programs, home teams are more often better teams and therefore win more often.

Home field advantage, though, is very real. On average, home field advantage is about 3.5 points. Specifically, from 1994 to 2008 it was 3.500949. In other words, the home team could expect to do 3.5 points better on average playing at home than at a neutral site against the same team. There is a 7 point swing between playing at home versus playing at someone else's home-exactly 2/3 of the average margin of victory for home teams (10.5). The other 1/3 is because Louisiana-Monroe goes to Alabama and not vice-versa (oh, wait, bad example--suck it Saban).

To understand HFA, we first look at the point differentials (PD) or the difference in the average margin of victory at home versus on the road. Again, this is not my opinion, this is data. Over this period, Arkansas State has lost home games by an average of 1 point, but they have lost road games by an average of 20 for a differential of 19. The highest ranked BCS team is Texas A&M at 10, and there are only 7 in the top 25.

This, of course, does not actually measure HFA because it does not account for the strength of schedule. For example, Arkansas State's average home opponent was about 12.4 points worse than its average road opponent, so when we take that into account we see that Arkansas State had a 6.8 point HFA, or 13th best in the country.

After accounting for strength of schedule, Boise State and Hawaii come out on top. Oklahoma State is at 4, Texas A&M and Texas Tech at 8 and 9. Beaver Stadium comes in just a hair below Arkansas State at 14. You have to go to 39 with Florida before you find an SEC team.

These are facts-hard, undeniable facts--but there is more to football than point margins. Arkansas State has a real home field advantage, but getting less plastered at home is not anything to write home about.

So I decided to measure HFA as the oomph that helps a team win at home when they would lose on the road. This measure is a bit more technical, but the results are also a bit more satisfying. Interpreting the numbers is just about impossible, but the most important thing to remember is that teams with a larger number have been able to win more games at home that they would have lost on the road than are teams with smaller numbers.

Texas Tech is number 1, as Longhorn fans know all too well. Texas is 12, which might come in handy when they are looking for revenge against the Red Raiders this year. Florida State is at 3, showing the superiority of the tomahawk chop over the gator chomp, which comes in at 14. Despite the long home winning streak at Kyle Field in the 90's, Texas A&M drops to 26.

In summary, home field advantage means different things at different times. It helps almost all teams put more points on the board than their opponents (with the exception of Navy), and this characteristics of home field advantage seems to have less to do with big stadiums and raucous crowds than we might think. On the other hand, home field advantage helps some teams win when they might otherwise have lost. It might not show up in gaudy numbers, but Nebraska is able to win games in Lincoln that they would have lost somewhere else. And at the end of the day, that's what really matters. And Georgia plays better and is more likely to win on the road-go figure.

Big XII North, 2007(8) (P)review

Last year, some teams in the Big XII North finally caught a few splinters from the ugly stick and started hitting back. They even sent a team to a BCS bowl for the first time since Kansas State in '03 and then Nebraska in '01 (if my memory serves me correctly). But in the end, the South continued its reign.

So what should we expect from the land of prairie, corn, cows and, in small isolated gatherings, people? Here are my big questions for the Big XII North in 2008:

1) Will we see a repeat performance from Kansas?
2) Will we see a repeat performance from Nebraska?
3) Can someone from the North win the Big XII?

(See here and here for an explanation of the Performance and Reputation graphs, respectively.)

1) Kansas has an all time record of 554-550-58 for an all time winning percentage below 51%, and has scored a total of 11 points more than their opponents. Nebraska, on the other hand, has won 70% of its games all time and has scored 14,000 more points than its opponents.1 But last year, Kansas scored 37 more in one game than that particular opponent (it is also notable that Kansas scored 76 against the Nebraska basketball team as well).

Kansas was a consistent, solid, and underrated team from beginning to end last year. Mangino made some brilliant personnel moves (whether his own or those of his staff I don't know, but the result is the same) and some guys that the big schools didn't want turned out to work together like clockwork. In the end, though, you can't always expect former QB's to succeed at wide out, thugs to not get in trouble, and players the big schools didn't want to dramatically exceed expectations. For Kansas to have continued success they have to recruit, and Lawrence is still not a high school kids dream destination.



For 2008, though, Kansas has three big things going for it. One, a successful basketball program breeds ready made fans that are looking for something to cheer for (see Texas A&M basketball for an example). Two, they have some stars and many cogs back from a very good team a year ago. Three, they have another soft schedule. They'll lose at OU, but could win the rest and get a second shot at the Sooners on a neutral field. A repeat of last year is too much to ask for, though, and I expect Kansas to lose three this year and finish second to Missouri and Missouri can then make snide remarks about the Cotton Bowl.

2) Nebraska hit rock bottom last year when they demonstrated the human sieve against the Aggies, but then were able to rebound to a more respectable level. This level (about 20 on the Trend-O-Meter, see above) is where Nebraska belongs and will finish again this next year.

The truth of the matter is that Nebraska is on the wrong end of a demographic shift in the United States. As I noted earlier, Tom Osborne achieved more per capita in Nebraska than any coach ever, but now Nebraska is settling back where it belongs. Demography is destiny. A shrinking population relative to other states means that Nebraska has less talent and resources to pull from, and all that tradition will melt into oblivion as the program shrinks into mediocrity.

3) Generally, expect the South to continue its dominance and to even recover some of its big stick shrapnel from the North. Focusing more on the Big XII championship game, though, the North has in Missouri a potential contender that could bring the title north again. But, as always, the Big XII is OU's to lose.

Why Some Teams are Good, Part 2 - The Importance of Population

Obviously, a team has a better chance of landing a recruit if he lives nearby (or, in the case of Joe McKnight, they might be wishing they had stayed closer to home). In this blog I provide some evidence to support a claim I made in part 1 that increasing population increased the talent pool and, therefore, led to better football teams.

I picked 8 states more or less at random. I tried to include states from a variety of regions, with a variety of sizes and that have experienced a variety of population trends. I have included both Nebraska and Oklahoma, and, honestly, I don't know why.

Ratings come from Soren Sorenson, who you will find listed in the Statistics Hall of Fame. I have added 5000 to all scores so that they are all positive (Sorenson's system ranges from -4000 to +4000, +or- a thousand). Population data is drawn from the Census. Census data is collected every ten years and I have used my own estimates to fill in the gaps.

I have looked at states as a whole, adding together the ratings of all teams in that state, because teams in the same state recruit for players in the same talent pool. For now, I am ignoring population growth in the region (e.g. Georgia benefits from population growth in Florida), and characteristics of the population (e.g. old people in Arizona don't play football), but some day I will look at those issues in more detail.

So, first we begin in 1950.

The 8 states are Nebraska and Oklahoma, which I already mentioned, Florida, Arizona, New York, Indiana, North Carolina and Alabama. The graphic on the left shows the teams as they were ranked in 1950, color coded by state. Florida State, UCF, USF, and Buffalo did not have D 1 programs at the time (or, in some cases, did not have a football team, or just started admitting boys to the school).

This chart is important because, from here on, I will be focusing on indexed values for the state, so that indexed value will always reference back to this starting point. For example, 1950 was a good year for Oklahoma and Army (perhaps the two best teams in the country). This will be important to keep in mind.

This next chart demonstrates an important principle as well. This compares the percent of the total points held by a state (with their scores added together) of all the points available against the percent of the US population in that state. So, New York, despite Army's success, was under-performing. Anyone who has been to a high school football game in Dallas and in Rochester knows why this is happening. It shouldn't surprise anyone that Oklahoma performed the best giving their population size. Alabama was facing a unique challenge in segregation. It would be another 20 years before Sam Bam Cunningham would convince Bear Bryant to integrate, allowing Alabama to dip much deeper in its talent pool.

The population of most states would grew over the next 50 years, but some grew much faster than others. Florida and Arizona are good examples of states that blew up in terms of population, while New York stagnated.

In the following charts, I present data for each state in terms of their performance and their population over the 5 decades from 1950 to 2000. The black line is the team's performance. It is a running four year average which I use under the assumption that players from a cohort will play for a team for four years. The red line is the indexed population, where 100 is equal to the population in 1950. The blue line is based on the same principle, but represents the percent of the US population represented by that state, so that if a team's population is growing slower, but slower than the entire US, the blue line will fall but the red line will rise. The red line, therefore, represents the real talent pool and the blue line the relative talent pool, and because teams are good relative to each other, we should focus on the blue line. (You can click the charts to see a bigger version.)


Nebraska had some kicking teams in the 70's and the mid to late 90's, which shows up in their chart. The population as a percent of the US population was actually going down, but Nebraska kept spitting out world class teams. It makes me think that Osborne may have been a much better coach than we give him credit for. Arizona's performance isn't improving with its rapidly growing population. I think two things are at issue. First, Arizona doesn't have as strong of a football culture as the rest of the South and, second, Arizona's programs might be experiencing a bit of a lag.

I was a little surprised to see how well Indiana fits the pattern. Notre Dame has a unique advantage to recruit nationally and should be able to overcome general demographic shifts. Notre Dame claims their challenges are rooted in high academic standards, so I guess I'll have to look at that claim another day.

Alabama has been generally outplaying its population since the 50's but, like all the others, its performance is generally falling with the decline in its relative population size. The effect of integration on performance is still a little unclear, but something I will definitely look at more closely in the future.

But the overall results from this little experiment are clear--population trends in a region definitely effect the performance of that regions teams. The black lines tend to go where ever the blue lines are going. It also shows that we can't ignore culture, quality of coaches and the power of programs to attract players from long distances.