Steve Lavin’s Analysis Doesn’t Quite Cut It

During February 10th’s Michigan State-Michigan game, ESPN’s color-commentator Steve Lavin made a fairly large generalization about college basketball teams:

“This is the time of year when teams start to hit a wall. In January, you’ve got a hop in your step, everyone is 0-0 coming out of non-conference play. In March, you’ve got tournaments. But February is when teams slow down, particularly younger teams.”

Initially, I yielded two questions from Lavin’s comment. The first: do teams, in fact, lose more games in February than in other months? Second: If so, is the effect greater in younger teams than their older counterparts?

After explaining the context, I discussed these questions with one of my closest and brightest friends. This was a good decision, because it took him about half a second to point out the inanity of the first question; namely, that all teams can’t hit a wall at the same time, because the number of losers always equals the number of winners. It’s reasonable to believe that Lavin didn’t mean literally all teams suffer in February, but some specificity would have helped. 

The first question still stands, however, if you realize what Lavin actually meant. He meant “this is the time of year when good teams hit a wall,” because really, how many basketball games with bad teams does Lavin watch? None, just like the rest of us (unless you’re a Vanderbilt fan). This intent releases him from the aforementioned logical problem, and allows for the possibility that bad teams benefit from the wall-hitting of the good ones. 

So, me being me, I decided to research the questions associated with Lavin’s statement.  I selected the end-of-season top 25 rankings from 2004-2008, as determined by the Coaches’ Poll, as my data pool. This gives us 125 teams, all of which were good. For each team, I recorded the following: 

  • average age of players that played more than 10 minutes per game (1 = freshman, 2 = sophomore, etc.)
  • the team’s winning % in February
  • the team’s winning % in all other months
  • the team’s winning % overall

After recording these numbers for each team, each year, I averaged them out:

  • 2.585 average age 
  • .775 average winning % in February
  • .792 average winning % in all other months
  • .788 average winning % overall

These averages are only useful in answering the first question. It appears that February is harder on good teams than the other months of the season. This is hardly revolutionary, however. The schedule is usually toughest at this time, with teams deep in the heart of conference games. Losing an extra game or two is almost inevitable in major-conference teams. Ultimately, the answer to the first question is about as unremarkable as the question itself. It receives a resounding “duh.”

The second question is far more interesting, particularly to people like me who feel that youth often receives well-meaning but sometimes baseless criticism in college sports. So, I took the average age, and looked at the winning %s in February of teams above and below that mark. Then I did the same for teams’ other winning %s and overall winning %s:

  • .789 older teams’ winning % in February; .757 for younger; 3.2% difference
  • .804 older teams’ other winning %; .776 for younger; 2.8% difference
  • .801 older teams’ overall winning %; .773 for younger; 2.9% difference

Technically, it appears that Lavin is correct when he says that younger teams falter more than older teams in February. But, as my close and bright friend also pointed out, a 3.2% change in winning percentage doesn’t even translate to one win. The difference in performance is negligible. 

In another time, I would have railed against Lavin for – at the very least – not researching something like this before saying it. He delivered the “particularly for younger teams” part as if it were a throwaway line, as if “but February is when teams slow down” just wouldn’t cut it as an ending. This addition turns an intuitive comment into an assessment that can be empirically substantiated. In itself, this is not a problem, but it becomes problematic when the analyst doesn’t offer any evidence to back up his claim. Essentially, the addition presents two roads. The first road ends with Lavin explaining his reasoning and presumably offering some sort of evidence to substantiate his claim. The other road ends with the ignoring of any obligation to back up a serious assessment. This is the road Lavin took. 

Perhaps at some point during his coaching career, Lavin presided over a young team that faded in February, giving him the comfort necessary to make his claim. Unfortunately, anecdotes are not sufficient, and color-commentators are (or should be) in the business of providing analysis based on the artful balance of experience and evidence. In this case, the result is just another missed opportunity to educate the viewer.


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