Does Experience Matter in the Early Season?
Everyone says that continuity pays off at season's open. Here's why they're wrong.
The college basketball world, like any sport, is filled with common sense adages and received wisdom that go largely unchallenged so long as they follow reasonable logic. Analysts have long since mastered these, spewing maxims with all the smarm they can muster from their studios in Bristol. I’d like to turn the screws on one of these and see if it holds up to scrutiny.
The Adage
It’s commonly believed that teams which “bring everyone back,” i.e. returning a large percentage of the active players from last season will do better in the early season, as they have an abundance of chemistry while other teams are still learning how to gel together. It makes perfect sense; if an opponent hasn’t figured out their best units yet, an inferior team that has already maximized its roster may be able to beat a team that, later in the season, would be far stronger. If true, this should have massive implications in NCAA Tournament seeding, as early season losses to experienced teams should be weighted lower than losses to late-season juggernauts who took a few months to come together. Of course, another scuzzier implication would be for gamblers, as fading “new” teams during the early season, and then “experienced” teams in the late season would be an effective strategy, so long as the bookies weren’t wise to it.
The Measures
BartTorvik.com tracks the “returning minutes %” of each team heading into each new season. This isn’t a perfect measure, as teams may add additional players through the transfer portal that displace existing starters, but, buy-in-large, it captures the likelihood of similar lineups featuring in successive years for a team. Given limited roster spots and the increasing importance of re-recruiting your own players during the transfer portal era, it’s unlikely that the above scenario plays out all too often.
In measuring team performance, I’ll be using BartTorvik’s “Game Score” a metric that gives a score for each game based on offensive and defensive efficiency, relative to the opponent played. A 10-point loss to a top 10 team may yield a higher score than a 20 point victory over one of the dregs, for example. What’s important here is that Game Score can be used to compare performances throughout the year; a game in November is judged just the same as a game in the NCAA Tournament. In this way, trends in Game Score can represent the overall trajectory of a team relative to the overall level of the country.
The Test
If the common theory that experienced teams are at an advantage during the early season is true, teams with a high Returning Minutes % should see a negative trend in their Game Score, as the relative advantage provided by their head start in chemistry should wane over time. Similarly, teams with a low Returning Minutes % should see an upward trend in their Game Score, as ideal rotations are solidified, and players get used to one another. I gathered the top ten teams with the most and least returning minutes from last season, with the presence of some of college basketball’s worst among the high returning minutes teams dispelling any notion that “running it back” inherently makes a team good; what’s important here is the trend relative to their own performances during the year, even if that ranged from partially pitiful to wholly horrendous.
The Results
While the oldest teams did indeed show a trend of downward performance, this was not mirrored by the bottom ten teams, suggesting that it is more likely to be noise than signal. The trends weren’t indicative of overall team strength either, as South Dakota State had a banner year in the Summit League despite their Game Score veering lower over time, while Idaho State nosed into the positive despite posting a losing record in the marginal Big Sky Conference. This rules out a “contamination,” in which Game Score Trend would’ve been more indicative of general success rather than success relative to a team’s own performances.
The Other Angle
Perhaps this was a problem of measure; if returning minutes itself did not track to relative early season success, maybe it doesn’t capture what’s truly responsible. If college basketball experience is what is valuable, teams that have a higher average age, even if many are transfers, may realize the early season bump I ascribed to teams with high returning minutes. Using BartTorvik’s “Years Played” measure, I gathered the top ten longest and shortest average tenures in college basketball coming into 2022 and looked for the same trend pattern as with returning minutes. Again, this isn’t a perfect measure, as seasons won’t perfectly correlate to possessions played, but it captures a sense of maturity or physical development that, say, a team of mostly rising sophomores like Northern Iowa from the previous table would lack.
Here, the experienced teams flipped the expected trend on its head, improving in Game Score as the year progressed against conventional wisdom. The eventual success of their opposites prove that this isn’t a fully reversed result, and the discordance with expected results suggests that the common view of experienced teams as early season steamrollers doesn’t bear out in truth.
The Takeaways
These sorts of axioms are all over the place in college basketball. Listen to any color commentator or ‘analyst’ during a game, in the newspapers, or on the Internet, and these sorts of expected trends will be taken for granted without second thought. While I don’t think that a few tables disprove the general idea that some teams struggle with chemistry issues early in the season, applying some scrutiny to the unchallenged clichés of the sport is certainly a worthwhile exercise. In this way, the case of experienced and cohesive teams not actually overperforming during the early season is worth keeping in mind the next time you hear a member of the pundit class trotting out the same tired truisms that don’t actually mean anything.
Oh, and if gamblers really believe in this stuff, you can make a killing fading the inefficiency once the lines move (but that’s none of my business).