Return and Improve Model: 2018 Revisited

I was unsure about the topic I wanted to discuss for this last article before the January Edition of the Quality Curve Analysis. Of the four articles I have written for this current season, three of them have focused on the 2018 tournament and the lessons learned from it. Since the January QC Article will pivot our entire attention to the 2019 tournament and 75% of the articles leading up to it have been 2018-centric, I think one more article about 2018's wild ride would be fitting. It's not like it could hurt.

Anyways, I'm going to take a second look at the Return & Improve Model. I first revealed this model for the 2017 tournament (Link to the article if you wanted to refresh your memory). I wanted to do a quick article on it during 2018's Crunch Week, but I.R.L. things popped up on that Wednesday and forced me to put it aside. It may have been for the better since some of the findings in this article could only have been discovered ex post facto. So let's jump right into it.

Warming Up the Crystal Ball: 2018-19 Edition

If you are an avid reader of my blog -- and if you're not, then now is a good time to start -- you may remember I did a post in the 2016-17 season with a similar title. No, I won't be providing a link to that article like I normally do, but the article appeared in December of 2016 if you want to look it up. This article will be another attempt at preseason prognostication in December, but in a different fashion than the previous article (which is why I didn't link it). Let's get to it.

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.

2018 Quality Curve Analysis - March Edition

Welcome back PPB-readers! Unless you are in the B10 Conference, we have exactly two more weeks of games until the Selection Show on Mar 11, so that means it is time for the March installment of the QC Analysis series. If you missed the first two installments, here are the links (January and February). While I hope it won't take you two weeks to read this installment, there are a lot of issues that I want to discuss in this installment and I doubt that I will get to address them in the Final Edition. So let's get started.

The "Experieneced Talent" Model (Post-Season Update)

What a week of college basketball (and I could make the same exasperated comment for the officiating of that week too, but that's another story for another time). In this past week alone:

• #1 NOVA, #2 UVA, #8 AUB, #13 ARI, #19 WVU, and #23 NEV lose "home games" to unranked teams
• #10 KU, #15 TENN, #20 MICH, and #25 MIA lose road games to unranked teams
• #3 PUR, #17 OKLA, and #24 UK lose both games played for the week (and to PUR's credit, both of their losses came against Top-14 teams).
• #5 XAV gets two road wins, the first to some of the best officiating I've seen in quite some time and the second to the absolute worst late-game officiating I've seen in quite some time.
• Most importantly, the Selection Committee released their annual in-season mock tournament field with the Top 16 teams and their seedings on Feb 11, exactly four weeks before the real deal on Selection Sunday Mar 11. While I will refrain from issuing my full thoughts on the contents of this release, it should suffice enough to say: "What a way to end this week!"

If you are not convinced by last week alone that the 2018 tournament is going to be a wild one, then reading this article will be a waste of your time. As I have teased on the blog for over two months, this article will detail a quirky model that I conceived to measure and/or predict the stability or instability of the tournament.

2018 Quality Curve Analysis - February Edition

As we approach the completion of another month in basketball, it means that it is time for another installment of quality curve analysis. If you haven't read the January Edition of QC Analysis, here is the link to that article. It is definitely worth the full read, as I believe it will put you ahead of your bracket-picking competition in March. Nonetheless, the key points in that article:

1. Parity in the 2018 tournament (the key ingredient for upset soup)
2. One of the wildest days in college basketball and its distorting effect on the QC
3. Where 2017's tournament contenders were located in the 2017 Jan QC Analysis

At the risk of appearing lazy, I think I'm going to follow these same themes in the Feb Edition. If you took the liberty of reading (or even re-reading the January Edition), the same thematic structure to the article will provide continuity between the two reads. Likewise, I don't think much has changed in the basketball universe since the January edition, so keeping the same themes is fitting. Let's see what the February QC predicts for us.

Upsets in the Making (Part 3) - Statistical Analysis of Upsets

As I hinted in the January Edition of the QC Analysis, I do think the 2018 tournament will be filled with upsets, and it is why I have focused upon a three-part series on upsets. I also turned it into a three-part series (from one single article) due to the sheer volume of information. Since it has been one month from the last article on upsets, a recap of the series's content is in order:

• Theoretical Approach - Examining how upsets happen and could potentially happen (UPMs) given the structure of the 64-team/16-seed bracket.
• Historical Approach - Examining how upsets and UPMs have happened in the 64-team/16-seed bracket, both on a yearly basis and on a seed match-up basis.

In both of those articles, as well as this one, the objective is to create a generic view of upsets, one that ignores bias-inducing elements like team name, W-L records, match-up statistics (efficiency ratings, win percentages, coach PASE), and etc. While other tools will provide secondary insights on the expected number of upsets (QC Analysis) or which match-ups seem likely to produce an upset (round-by-round seed guide or OS/US analysis), these three articles aim to produce a primary framework for understanding how they arise. Now, let's see what statistics can show us about upsets.

2018 Quality Curve Analysis - January Edition

While everyone else in the world is turning in the new year watching the ball drop, I'm pretty sure my loyal readers are turning in the new year by reading this article. Okay, I'm not that interesting of a writer, but it has reached that point in the season where we take our first potential peek at the 2018 tournament. Today, I bring you the January Edition of the 2018 Quality Curve Analysis, which is an annual tradition here at PPB, and to make it even more special, it marks the birthday of PPB. Today, PPB turns 2-years old (technically Jan 8, but I go by the article, not by the date on the calendar). I do want to take this quick opportunity to thank all my readers for this special occasion: If you guys weren't reading and interacting, I know for sure I wouldn't be writing articles. I owe this birthday to you all! So, Thank You Very Much, and with that, we move onto the gift that keeps on giving: The Quality Curve.