The Upset Zone

"You are about to enter another dimension, a dimension not only of sight and sound but of mind. A journey into a wondrous land of imagination. Next stop, the Upset Zone!"* For my readers who also happen to be science fiction aficionados, the intro to this article was a PPB reproduction of the infamous intro to the Twilight Zone television series. I can promise this is not a cross-over to or application of Twilight Zone thinking to bracket picking. I just wanted something cute to lead in the article about a phenomenon that makes you feel like you've just left a bizarre and unusual place. After 2018's R64 games, you probably felt like you had just left the Twilight Zone because 2018's tournament gave us bracket history. That's right, a 16-seed has finally beaten a 1-seed. 34 years of tournaments, 135 match-ups pitting 1-seeds against 16-seeds with 8-10 near-misses among these, and the last 1v16 match-up of the 2018 R64 gave us our Haley's Comet of Cinderellas. In all honesty, I wasn't euphoric about it, even though I should have been since it has never happened before. I wasn't really shocked by it happening (the margin of victory however was a surprise) or the team to which it happened. My first gut reaction to it was the inspiration for this article: "So, now what?"

In this article, I will answer that question: "What's remaining in the Upset Zone for us bracket pickers? To begin with, I want to better understand the conditions that gave way to the first-ever 1v16 upset so that the next one is closer to a given than a guess. Second, I want to know what other historical firsts are waiting for us in the Upset Zone.

Welcome to the 2018-2019 College Basketball Season

Important Dates:
Selection Sunday is March 17, 2019

WELCOME BACK PPB READERS!!! It's nearing the start of the 2018-2019 college basketball season, so we're going to start this new season off with the usual assessment of my predictions made in the previous season. Sit back, relax, and I'll tell you how good or bad I did in the 2017-2018 season (unless you already spent your off-season doing it). The predictions will be graded in chronological order of when they were made, and each individual prediction will be identified by italics and red highlight. Followed by the grades, the PPB schedule for 2018-19 CBB season will appear.

2018 Quality Curve Analysis - Final Edition

Well, the bracket has been released, the match-ups are set, and now it is time to see how the next three weeks will likely play out. If you have read the previous three editions (and if you haven't, here are the links to three very good reads: Jan, Feb and Mar), you will recognize the chart below. It is the Final 2018 Quality Curve.

What is the QC Telling Us?

The same thing I have said all year long: "Parity exists in 2018 and parity translates to an above average number of upsets."

The Mind of the Selection Committee

As readers of my blog already know, a proven method of spotting upsets in a tournament is exploiting the knowledge gap between the Selection Committee and the data scientists. In my introduction articles for the last two seasons (links: 2016 and 2017), I took a simplistic ex post facto approach to understanding the Selection Committee's seeding principles. In short, it seemed as if the Selection Committee put an added value on conference affiliation, where teams from conferences with a better conference-RPI received seeds higher than their individual resume would suggest they deserve. In effect, these teams were over-seeded and other teams from less-valued conferences were under-seeded, and this type of match-up usually favors the under-seeded team. In the 2016 tournament, the B12 and P12 were beneficiaries of this process, yet in the tournament, teams from these conferences went 9-7 and 4-7, respectively (combined 13-14, and 7 of the B12's 9 wins can be attributed to OU's F4-run and KU's E8-run). In the 2017 tournament, the ACC was a huge beneficiary of this process, yet in the tournament, the ACC went 11-8 total with only one team making it to the S16 (6 of the ACC's 11 total wins was UNC's title run). Now that I have seen this process in action for the last two years, I know what to look for in the 2018 tournament...................unfortunately, it may not happen this way. Why? The Selection Committee has a brand new toy for the 2018 tournament called the Quad System. How they implement it will affect our ability to identify potential upsets, and this fact will be the focus of this article. (NOTE: Some sections may be really long-winded due to quality of detail, so for this article, if I feel a section needs a condensation, I will provide one and give it the label of "TL/DR", which means Too Long/Didn't Read.)

The Madness of Metrics and Match-ups

Well, I had three ideas for this article. The first idea came to me when I was putting the final touches on the 3-part series on upsets. Needless to say, what I was hoping would happen didn't happen, which means there won't be any follow-up to that series. Either during the weeks after the tournament starts or during the off-season, I will update Part 2 of the upsets article with the remainder of the withheld data. The second idea spent about two weeks off of the drawing board, then went right back on it, and the only reason it went back on the drawing board is because the idea for this article fulfills quite a few needs. First, I promised the implementation of micro-analysis in the blog, yet here we are in March and none to be found. By micro-analysis, I mean the study of the brackets from the perspective of match-ups and team-specific qualities, rather than macro-analysis, which is the study of the brackets from the big picture perspective of tournament quality and predictability. Shame on me.....until now. Second, I like to be a ground-breaker, a pioneer in the science of brackets, an innovator to the tools of the trade. I tried last year with the article on trend analysis, and yes, I am still following, testing and improving that tool. I think this article will be just as intriguing and innovative as that one. Third and final, it uses the same data I have been using all season, just in a different way. I am going to be using efficiency analysis to predict match-ups. In particular, this article will focus on using the Four Factors as a tool to determine how teams win and lose their games.