Introducing BRCT: A Bracketologist’s Best Friend

Bracketology is a difficult process. Let’s make it a little less difficult.

Today, I reveal one of the secrets behind the Bauertology bracket creation process—the holy grail of bracketology analysis: the Bauertology Résumé Counting Tool. (Or BRCT, pronounced like “bracket,” for short.)

It’s a pretty poorly-kept secret, as I’ve mentioned this tool a handful of times on the r/collegebasketball subreddit and on my Twitter page. Over the past few years, I’ve been devising a tool that simplifies the bracketology process by assigning a score to the factors that the NCAA tournament selection committee analyzes and counting them up into one grand score that can then be used to compare a team’s overall résumé to that of another’s.

And now that COVID cancellations and postponements are behind us (well, for the most part… thanks, Northwestern), teams are generally on even ground in regard to how many games they’ve played at a given time. That’s good news for keeping BRCT normalized, and I feel like that means it’s a good time for BRCT to make its true public debut.

In its current form, BRCT analyzes the important résumé factors from the NET top 105 teams and current projected automatic bids from sub-105 NET teams (all data gathered from the incredible WarrenNolan.com NET Team Sheets Plus webpage) but could potentially be expanded to analyze all 363 Division I teams in the future.

With that introduction out of the way, let’s get into a more in-depth explanation of what BRCT does, how it works, and what its purpose is.

What does BRCT do?

As the name implies, BRCT counts up how strong a team’s overall tournament résumé is by assigning a score to the prominent résumé factors that make up that team’s team sheet. Once each factor is assigned a score, these numbers are counted up into one grand score for that team, reflective of how strong their overall résumé is. These grand scores then make up the ranking system, stacking the teams from top to bottom based on the overall strength of their tournament case.

Numbers will inflate as the season goes on and teams earn more wins and losses of every shape and size. But the for time being, a score of above 100 means that a team is essentially a lock for the NCAA tournament, while a score of around 40 puts you on the tournament bubble.

How does BRCT work?

Unlike other basketball ranking systems that rely on complex formulas, BRCT is extremely simple in nature. It’s easy for anyone to understand, as it relies on the simple proverb of “what feels right.” And it doesn’t get too much into the nitty-gritty of every single aspect of a team’s résumé; it keeps things simple and understandable, tracking only the most important factors you hear about when evaluating a team. While this may make BRCT less objective than other ranking systems, I feel like the results speak for themselves. Here’s a look at how BRCT ranks the 119 teams that make up the NET top 105 and projected sub-105 auto-bids as of today: Thursday, January 19, 2023.

Pretty neat, huh?

Now let’s get into how things are scored. Below are the résumé factors that BRCT tracks and how it awards points to a team based on those factors. Once you’ve read the sections below, feel free to share whether you think BRCT undervalues or overvalues certain résumé factors. But as I’ve tweaked this tool over time and kept track of the numbers, I really think I’ve honed this thing down to a T, and I don’t anticipate making any major changes to the formulas.

COUNTING FACTORS

Let’s start with the counting factors, which are very easy to score as they are based on countable things—wins and losses—with the only adjustments necessary being multipliers for the magnitude of these wins and losses.

Win-loss record: The easiest and most simple factor to understand, BRCT subtracts a team’s loss total from its win total to produce a score. A team that sits at 17-6 overall (counting only Division I games, like the selection committee), would result in 11 points for their W-L record. A sub-.500 team at 8-12 overall would receive -4 points from this category.

Road record: As all NCAA Tournament games are held away from home, the selection committee places some extra value on teams that can get the job done when their home crowd isn’t a dominant factor. BRCT scores road record the same as overall win-loss record, except that teams are awarded 2 points for a road win instead of 1. So, a team that is excellent on the road with a record of 6-2 would receive 10 points, while a team that struggles away from home with a record of 1-7 would be hit with -5 points.

Quadrant 1-4 record: In discussing the quality of wins and losses on any given team’s team sheet, the quadrant system established by the NET rankings is the selection committee’s go-to tool. You can read elsewhere about how the quadrant system works, but in simple terms, there are four quadrants that each bring varying degrees of quality to a résumé depending on the result.

Quadrant 1 wins are what you want—those are wins against the top level of competition. Quadrant 2 wins are also good to have—those are wins against solid, often tournament-level teams. Wins in Quadrant 3 and 4 are frequent, and usually come against the teams you’re “supposed to beat.” They don’t do much for a résumé except provide some padding to your overall record.

As for the opposite result, Quadrant 1 losses aren’t bad to have… in moderation. They symbolize a loss against a good opponent—maybe an opponent that you had no business beating. But selection to the NCAA Tournament relies heavily on how you stack up against other top competition. So, while incurring a Quad 1 loss from time-to-time is OK, you don’t want to make it a habit. The same is true for a Quad 2 loss, though slightly magnified. Then there are Quadrant 3 and 4 losses, and these are deadly. Q3-Q4 losses are what you often hear people refer to as “bad losses”; losses against teams you should have beaten. They’re usually a pretty rare find among at-large contenders, but you do see them on team sheets occasionally.

So, how do we score wins and losses in each quadrant? Well, as we established earlier, BRCT scoring is based on “what feels right,” so we apply that to the quadrants. As such, a Quadrant 1 win adds 4 points to your total score, but a Q1 loss subtracts 2. So, a team that rocks these Q1 games and goes 10-2 in that category earns a big 36 points, while a team has won against top competition but more often than not flounders with a Q1 record of 2-8 is penalized with -8 points.

As for Quadrant 2, which symbolizes our “balance” quad where you should probably be winning most of these games if you’re a tournament team, a Q2 win nets you 3 points, and a Q2 loss loses you 3. So, it’s essentially on the same scale as your overall record, but magnified to express the importance of beating quality opponents.

Finally, there are Quads 3 and 4. As mentioned before, wins don’t do anything for you here; they’re just filler, so no points are awarded for a Q3 or Q4 win. Losses, however, do you harm. Losing a game to a poor Q3 opponent is a subtraction of 6 points, while falling to a bottom-of-the-barrel Q4 team removes 8 points. The reason these categories are magnified beyond Q1 and Q2 is because of their rarity; a team vying for an at-large spot likely incurs 0-2 Quad 3 losses, compared to playing 10-12 Quad 1 games.

And, going back to our “what feels right” mission, the selection committee will dock points for bad losses, but has generally been willing to forgive them if counterbalanced with good wins. So, in BRCT scoring, a Quadrant 4 loss (-8 points) can essentially be “erased” with two Quadrant 1 wins (8 points), and that just feels right to me. (It also felt right to 2021-22 Rutgers, who snuck into last year’s tournament with a plethora of Quad 1 wins and some dreadful losses.)

RANKING FACTORS

Scoring each of those prior categories was easy because they’re based on the pure counting numbers of wins and losses. The other résumé factors are not so easy, as they’re based on 1-363 rankings systems instead… so we’ll have to score them differently.

Ranking in NET, KPI, SOR, BPI, KenPom, and Sagarin: All six of these rankings systems rank the 363 Division I teams from top to bottom, measuring different things but following a similar structure. NET is the NCAA’s simple 1-363 ranking that helps establish the quadrant system. KPI and SOR are “performance metrics” that rank every team based on how well they’ve performed in the games they’ve played. BPI, KenPom, and Sagarin are “predictive metrics” that calculate efficiency numbers and “predict” how a team should perform based on a variety of factors. All six of these rankings appear on a team’s team sheet, and while you may hear about NET or KenPom more than the rest, no ranking appears to hold significantly more weight than another—not even NET, the ranking system specifically designed by the NCAA itself.

These ranking systems are critical in helping establish which teams are tournament-worthy. Bare wins and losses, even within the quadrant system, only tell you so much. These rankings provide the context for how much those wins and losses mattered.

Because you can’t “count” a team’s ranking like you can a win or a loss, we’ll have to use a different system to score points here. The way we do this is by assigning points to where a team fall in each respective ranking. For all six categories, points are assigned like this:

• 15 points = ranked 1
• 14 points = ranked 2-3
• 13 points = ranked 4-5
• 12 points = ranked 6-10
• 11 points = ranked 11-15
• 10 points = ranked 16-20
• 9 points = ranked 21-25
• 8 points = ranked 26-30
• 7 points = ranked 31-35
• 6 points = ranked 36-40
• 5 points = ranked 41-50
• 4 points = ranked 51-60
• 3 points = ranked 61-70
• 2 points = ranked 71-80
• 1 point = ranked 81-90
• 0 points = ranked 91-100
• -1 point = ranked 101-110
• -2 points = ranked 111-120
• -3 points = ranked 121-130
• -4 points = ranked 131-140
• -5 points = ranked 141-150
• -6 points = ranked 151-160
• -7 points = ranked 161-170
• -8 points = ranked 171-180
• -9 points = ranked 181-200
• -10 points = ranked 201-225
• -11 points = ranked 226-250
• -12 points = ranked 251-275
• -13 points = ranked 276-300
• -14 points = ranked 301-325
• -15 points = ranked 326-363

Much like everything else about BRCT, this point distribution system was fine-tuned over time and is based on “what feels right.”

So, a team that pulls off the clean sweep and is ranked #1 in each of NET, KPI, SOR, BPI, POM, and SAG rakes in a huge 90 points. A more moderate team that ranks 30th in NET (8 points) and is favorable in the eyes of the performance metrics, ranking 17th in KPI (10) and 21st in SOR (9), but is less favored by the predictive metrics, placing 42nd in BPI (5), 60th in POM (4), and 67th in SAG (3), cashes in for a total of 39 points.

Ranking in strength of schedule (SOS) and non-conference strength of schedule (NCS): Our other two ranking factors are strength of schedule (the quality of your total opponents) and non-conference strength of schedule (the quality of your non-conference opponents). While these factors are not quite as harped on by the selection committee as the other rankings when it comes to measuring a team’s quality, they have been used in the past to justify certain seedings or including/excluding a team, so they are worth measuring.

Because SOS and NCS don’t measure the quality of teams themselves and only measure the quality of their schedule, we will halve the rankings from what we gathered for NET, KenPom, etc., meaning the scale for SOS and NCS looks like this:

• 7 points = ranked 1-5
• 6 points = ranked 6-10
• 5 points = ranked 11-20
• 4 points = ranked 21-30
• 3 points = ranked 31-40
• 2 points = ranked 41-60
• 1 point = ranked 61-80
• 0 points = ranked 81-100
• -1 point = ranked 101-125
• -2 points = ranked 126-150
• -3 points = ranked 151-175
• -4 points = ranked 176-200
• -5 points = ranked 201-250
• -6 points = ranked 251-300
• -7 points = ranked 301-363

In this system, a team that plays a really tough schedule overall—let’s say the 7th toughest (6 points)—but mostly beat up on weak opponents in an easy non-conference schedule, ranked 289th (-6 points), evens out at 0 points for their strength of schedule factors. A team may earn as many as 14 points or lose as many as -14 points based on the difficulty of their schedule—a little boost or hindrance to their overall résumé depending on the quality of the teams they faced.

These ranking factors are the most likely area for scoring to change over time, as teams will naturally earn more points in the counting factors as wins enter the team sheet in the areas of win-loss record, road record, and the quadrants. Meanwhile, points in the ranking factors are bound to a 15 to -15 (or 7 to -7) scale without any way out beyond those limits. If I deem the counting factors to be weighed too heavily later in the season, I may expand the limits of the ranking factors to get back in line with “what feels right.”

All in all, this scoring system may seem arbitrary to you (How can you equate a Quad 4 loss to being ranked 178th in NET, etc.), but it’s easier to understand if you focus less on how each factor is scored and more about how it tallies up in the big picture.

What is BRCT’s purpose?

Simplicity is bliss when it comes to bracketology. While the madness is supposed to happen out on the basketball court, bracketologists may feel like going mad staring and comparing résumés to get their projection just right. BRCT simplifies that process.

While you could very well make a bracket projection based on the numbers that BRCT spits out (and I don’t think it would be terribly off from reality), BRCT is more so a bracketology supplement than a bracketology replacement. I’ve already found myself using BRCT a number of times as I make my way through the seed list, either to pick out which teams I’m going to compare next, or to get an easy glance at how a team compares in Quad 1 to another team, or some other reason.

At the end of the day, I’m still building the bracket myself based on what I think, but BRCT has served as an extremely helpful guidance tool in the selection and seeding process.

I can confidently say that, for me, BRCT has reduced bracketology from a multi-hour process every time I build a new bracket to something that can be completed in less than two hours. It’s a godsend for saving time.

Of course, BRCT is not a perfect tool. At the present moment, it probably overvalues résumés from minor conference teams that have a bunch of wins but are lacking in quality (I’m hoping this begins to even out as power conference teams gain more quality opportunities down the stretch), and much like the Quadrant system, a win at NET #1 Houston is treated the same way as a home win against NET #30 San Diego State—obviously, the selection committee will not treat these wins as equal.

But BRCT is not trying to be perfect; it’s trying to be simple, understandable, easy to use, and effective. And I believe it accomplishes all those goals.

What’s next?

While I’m extremely excited to introduce BRCT in what is close to its final form, there’s still a long road ahead.

The goal is to eventually embed the BRCT rankings as a chart, made visible to all on the Bauertology blog, that updates daily as new numbers and results come in.

However, for now, this remains a dream. I went to school for journalism, not computer programming, so I have literally no clue how to build the self-updating system that I’m envisioning. Every time I update BRCT, I do it manually. It’s a very time-consuming process to update the numbers for 100+ teams, often taking an hour or more, and it’s always prone to human error. A self-refreshing system that draws the data from elsewhere would make this BRCT project so much less of a time sink for me, but I don’t know how to accomplish that.

If someone has expertise on how to build the self-updating system that I’m looking for that can be embedded on the Bauertology blog, please reach out! As mentioned before, when I manually update BRCT, I draw all my data from WarrenNolan.com’s NET Team Sheets Plus webpage, an invaluable resource for all bracketologists, as the important résumé factors are kept in one neat place, and numbers are updated quickly and often. I know there must be some way to pull the data from this website into the BRCT spreadsheet and have it update all by itself, but I don’t know how to do it. So, again, if you think you can provide a helping hand to make this BRCT dream a reality, please, please reach out! You can leave a comment here, message me on Reddit at u/MetaKoopa99, DM me on Twitter @Bauertology, or email me at djbauer1999@gmail.com.

I hope this post has made you as excited about BRCT as I am, and I can’t wait to see where it goes from here. Thanks so much for joining me on this lengthy read, and let’s play some basketball!