College Football History 101

Since it’s the middle of baseball season and the NBA draft just finished up, I decided to write about football. Actually, it was the announcement of a real playoff for college football that spurred me to take a look at the sport. Given the dominance of the SEC in the past several years – culminating in a title game that featured two SEC teams from the same division – I wanted to take a look back in history and see if any other conference had a similarly dominant run.

Because college football has never had an official championship we need to make some assumptions to be able to define dominance. I decided to go with the AP poll, since it has been around since 1936 and is one of the more-reputable ways for teams to claim national championships in the pre-BCS days.

Link between rank and points (linear and Sagarin)

Conference dominance, though, should look at more than just the number one team to see how an entire conference is performing. The polls can help with this too. By looking at the top 20 (top 25 since 1989) and assigning point values to each, we can give an overall value to the performance of all the top teams. While we miss out on valuing the lower-level teams, those teams are terrible and I don’t care about them.

Rather than just assigning points in a linear manner (i.e., 1^st ranked team gets 25 points, 2^nd ranked team gets 24 and so on), I wanted to dig a little deeper. I used the average Sagarin rankings for the past couple of years to determine what the curve looks like from 1 to 25. I took the value above the 26^th-ranked team and gave that to each team rather than 25-24-23 etc. The Sagarin-influenced chart looks like this:

This should better-capture the difference between truly elite teams at the very top and the merely good teams at the lower end.

Stop tanking, it doesn't work

Not to brag too much, but I wrote a post recently that looks at whether the NBA’s winners benefited from tanking. It also examined the perennial losers and showed some anecdotal evidence that they’ve done plenty of tanking, intentional or otherwise, to little effect.

I would not really be doing my job (not the real one, the blog one) if I didn’t at least look at some numbers given that the blog is called “Sports + Numbers,” so let’s look at some numbers. AThis post is about evaluating sequences of results. For example, we may look at where teams finish in year 0 and then track subsequent performance. Performance here will be measured mainly in terms of winning percentage and sometimes in terms of playoff or lottery position (e.g., 13^th ranked winning percentage of the playoff teams will be considered 13^th in the playoffs, while second worst winning percentage of the lottery teams will be considered 2^nd in the lottery).

My main goal is to answer the following question: If a team finishes lower in the league than they otherwise would, does it have a demonstrable effect on future performance?

Winning and Losing in the NBA

One of the most widely-held views on the NBA is that you have to bottom out to win. This view holds that teams in the bottom of the playoffs and upper reaches of the lottery are just wasting their time and that they won’t be able to compete without ditching expensive veterans and loading up on top draft picks. I decided to take a look at this view.

Losers and Winners

Before I get to the actual analysis (what a tease!) let’s a take a post to look at recent winners and losers in the lottery era (1984-85 to present) just to get a feel for the stories of those teams.

Winners are relatively easy for this period. You have the Mavericks, Lakers, Celtics, Spurs, Heat, Pistons, Bulls, Rockets and that is it. Every NBA championship in the draft lottery era, 28 years, has gone to one of these eight teams.

The losers are bit harder to define. On one level they are all of the other teams, but that’s a little hard to distill for analysis. On a more manageable level we will take a look at the teams that made the playoffs less than 40% of the time (16 teams out of the current 30 make the playoffs every year, but in 1985 16 out of the then-current 23 teams made the playoffs). These hapless franchises include 4 expansion teams (Bobcats, Grizzlies, Raptors and Timberwolves) as well as the Clippers, Kings, Warriors and Wizards. The Heat, Magic and Hornets were the expansion franchises within the period to avoid this distinction with the Heat winning two NBA titles and the Magic winning an Eastern Conference title.

Power rankings make my head hurt

ESPN.com produces some excellent analysis. Several of the writers working there can slice and dice data in ways that reveal thought-provoking, insightful conclusions. I have a weakness, however, for those delightfully qualitative pieces known as power rankings.

Even though I know that I should know better, I read them every week. I literally cannot stop myself from clicking on that link (figuratively, of course – I could quit if I really wanted to). Imagine, then, just how little control I had when I saw the NFL Future Power Rankings link on the lower right side of my screen. These rankings purported to give a quantitative look at the prospects of each team in the 2015 season.

I started to suspect something might be amiss when I looked briefly at the methodology. The methodology was to poll some of ESPN’s analysts and produce a weighted average of the results. There were instructions given for each category that seemed to make sense. Don’t consider players over 27 except at QB; look at the 2012 draft class, the team’s picks in the 2013-15 drafts and their track record in the draft.

In all, the five categories included Roster (ex-QBs), QBs, Draft, Front Office and Coaching Staff. The 4 analysts – Trent Dilfer, Mel Kiper (he of this track record), Gary Horton and Matt Williamson – voted 1 to 10 for each category and that was the extent of it.

The results of the survey looked all too familiar. There was Green Bay at the top, followed closely by New England, the New York Giants, San Francisco, Pittsburgh and Detroit. Not until seventh was there a team, Philadelphia, that failed to make the playoffs. Three of the four conference championship game participants made the top four. It did not appear to be significantly different from simply ordering teams based on their 2011 record. I decided to take a look at whether current year results are really that highly correlated with results in four years?

3 Picks to Advance 1 Slot??!!

For just a taste of my ongoing project, here is my (still in process) grade of the Vikings-Browns trade last night that sent the #4, #118, #160 and #211 picks to Minnesota in exchange for the #3 pick.

The "Value" field pulls in the log regression of the average % of salary cap value provided by those picks in excess of the first undrafted free agent. That is to say the last pick of the 7th round may provide 0.7% of the cap value in an average season of their career, but they only provide 0.003% excess value over an undrafted free agent. Only the 0.003%, in that case, matters for the trade because that is the extra value provided over what the other team can achieve for free with the next best option (e.g., a UFA).

That will have to be it for the explanation as I need to get back to writing about 6,000 more words for my project on this very topic.