Quality Curve Analysis (March Edition)

Yep, it's that time again. Time for another edition of Quality Curve Analysis. If you are interested in previous analyses, here are the links to the January and February editions. If you need a reference to quality curves, seed curves, and the like, try this article. Now, let's get to the good stuff.

2016: Then and Now

The jump-off point for this analysis has to be the evolution of the QC over the last two months. If you remember from the January Analysis (or read it just before reading this one), I made a prediction about the transformation of the curve. I predicted that once teams got into conference play and began playing against better quality teams on a night-in, night-out basis, the QC would rotate: teams at the top would rotate downwards and teams as the bottom would rotate upwards. The February Analysis showed that perfectly (but logic would have driven any one to that conclusion). The March Quality Curve has also made a significant move, and one I DID NOT see coming. It was so significant of a move, I almost posted an interim update before doing this one. So, what happened??????

The Time Line, Part 2: A Macro-Analyis of the Tournament

In Part 1 of The Time Line, I detailed changes to college basketball and the NCAA tournament, primarily from the Modern Era (1985-present). I then classified the changes into two categories: structural changes to the tournament and technical changes to the game. One change did not fit into
either category, and in my opinion, it could be in a class on its own.

2007: First tournament featuring the "One-and-Done" rule. Implemented by the NBA, all draft prospects must be 1-year removed from high school (or 19 years old) in order to be draft-eligible. It does not mean that draft prospects have to attend college. As the previous NBA drafts (2003-05) began reaching critical mass with "Straight-Outta-High-School" prospects, the NBA implemented this rule to rein in scouting and recruiting operations that had become over-extended as franchises (especially those with lottery picks) had to scour the entire nation at both the high school and college level in order to get the pick right.

For those of you thinking this is going to be an definitive analysis of the one-and-done (OAD) rule, you will be sorely disappointed! Instead, I intend to address a point I made in Part 1 about the relationship between the OAD rule and tournament results. So, I'll start this examination with a familiar data piece, the E8 Aggregation Model (E8AM). The most unusual stretch of games in the E8AM takes place from 2007-2009, which many regard as the calmest years of the tournament in an otherwise volatile era. Producing both a 13 and a 14 in the AM (and there's only one possible way of doing each of these) during this stretch, I think it is no coincidence that it started at the exact same time in which the OAD rule was implemented. So, what happened?

The Time Line, Part 1: A Macro-Analysis of the Tournament

College basketball and the NCAA tournament has endured more than their due share of changes throughout their existence. However, it is hard to imagine that no other year in the history of the college game has seen more "consequential" changes to the game than the 2015-2016 year. While we can crunch every statistic, simulate every "dribble-drive offense vs pack-line defense" match-up, or back-test any system of analysis, a macro-perspective on the game can tell quite a story. The purpose of this article is to document these macro-changes to the game and to articulate a theory about the impact of these changes on the results of the NCAA tournament.

The Time Line

1975 (S): First tournament featuring at-large berths to the tournament. Previously, the tournament was comprised of only conference tournament winners. In 1974, the greatest atrocity in college basketball occurred following the ACC championship game, which show-cased #1 NC State and #2 Maryland. Arguably the two best teams in the country (save Bill Walton's UCLA team), only the winner of this game would go to the NCAA tournament. Essentially, the National Championship game was played before the NCAA brackets were even paired, leading the NCAA in the very next year to implement at-large berths for qualified teams without winning their conference tournament. Since this episode, this atrocity only happens to teams from smaller conferences.

What is the Quality Curve?

As promised, I will be presenting an in-depth explanation of the quality curve (QC), the seed curve (SC). A forward warning: This article may be more technical than practical, meaning it is intended to explain a tool rather than tell its results. So, if you are looking for insights into the 2016 Tournament, this article may not be what you are expecting. If you want to broaden your analytical approach to the tournament, you are probably going to love this article, so let's dive right in.

The Quality Curve

Just as its name would suggest, the quality curve is a line graph displaying the "quality" of the teams in a given year of the NCAA tournament. The above chart shows the quality curve of the 2016 Field in January (blue line) and the same field again in February (pink line).

Quality Curve Analysis (February Edition)

The Idea Behind Quality Curves

As stated in the January Edition, the theory states that the quality of the teams in the tournament can predict the quality of the tournament results. In layman's terms, higher quality teams in the higher seeds will result in a stable, predictable tournament (much like 2007) and lower quality teams in the higher seeds will result in an insane, unpredictable tournament (much like 2014).