Category: descriptive


The Achievement S-Curve: 3/10/2012

March 10th, 2012 — 4:41pm

About half of the automatic bids are still up for grabs this weekend, but the NCAA Tournament picture is starting to take shape. It’s time for one last Achievement S-Curve update. As always, the full ratings can be found here. All data updated through Friday, March 9th. Click to view bigger.

Let’s take a look at some of the biggest discrepancies and see what we can learn. Continue reading »

Comment » | College Basketball, descriptive, March Madness, team evaluation

The Blindness of the Blind Resume

March 10th, 2012 — 2:38pm

I love the spirit of the blind resume. I hate the execution.

With Selection Sunday just hours away, you will undoubtedly be inundated with blind resumes comparing multiple teams and asked to decide which team is in and which is out, or which team should be seeded higher. I like the sentiment behind these: strip away the name of the team, their history, their media coverage, their conference affiliation and focus solely on what they’ve accomplished this season. The problem is that the blind resumes focus on the wrong information, making the comparisons flawed.

Why the Blind Resumes are Flawed

A typical blind resume looks something like this: Continue reading »

Comment » | College Basketball, descriptive, March Madness, team evaluation

What the RPI is and what it is not

February 23rd, 2012 — 9:42pm

Earlier today on CBSsports.com, Matt Norlander wrote an article about the much-maligned RPI. He comes to this conclusion:

If anything else, this chart proves there are far too frequent communication breakdowns with teams across the board, enough so that the RPI goes beyond outlier status and continues to prove what many have known for years: If the RPI was introduced in 2012, it’s hard to reason that it would be adopted as conventional by the NCAA or in mainstream discussion.

Norlander then provides the heart of his argument, a table comparing the RPI to various other basketball ratings: Sagarin (overall), KenPom, LRMC, Massey and BPI. He points out that “Texas, Belmont, Arizona and Southern Miss all have big disparity as well. The largest gaps are UCLA (62 points lower in the RPI) and Colorado State (65 points higher in the RPI).”

The RPI is a rating created to measure what a team has accomplished so far this season based on their record and their strength of schedule. It is a descriptive rating. LRMC, Massey, BPI, and Sagarin are predictive ratings at their core (though some are even worse, a random combination of descriptive and predictive). Comparing the RPI to these ratings and concluding that because it doesn’t match, it is flawed, is itself a terribly flawed argument. Of course it doesn’t match, it is trying to measure a completely different thing. I agree, the RPI is flawed, but not because of this.

Norlander’s article should have been about his preference for selecting and comparing teams based on their true strength instead of their resume, and not about the quality of the RPI which has little to do with this debate. Even if the RPI perfectly did it’s job (of measuring how much to reward teams for their performance on the season), it would have failed the test in this article. Let’s take a deeper look. Continue reading »

Comment » | College Basketball, descriptive, March Madness, predictive, review, team evaluation

The Selection Question Revisited

February 21st, 2012 — 9:40pm

The Philadelphia Eagles finished the season 8-8, but outscored their opponents by 68 points, the 5th-best mark in the NFC. Seven of their 8 losses were by one score or less, and they finished the season hot on a 4-game winning streak. Most rankings that try to determine how strong a team truly is had the Eagles as high as the 4th or 10th or 7th best team in the entire NFL. The team was filled with talented players like Michael Vick, LeSean McCoy, and Nnamdi Asomugha, among others, and easily passed the “eye” test as a good team capable of beating anyone at their best. In addition, two of the team’s losses came with their star QB sidelined and a third loss came when star WR DeSean Jackson was benched. When it came time to select the NFC’s playoff teams, the committee decided that Philadelphia was definitely one of the 6 best teams, and left out the Atlanta Falcons despite their 10-6 record as well as seeding the Eagles ahead of the 9-7 Giants, the winners of the Eagles’ division.

**********

I get the feeling that if this were to happen, fans would be outraged. However, this is exactly the type of thing that happens every year in the NCAA Tournament selection process. Continue reading »

Comment » | College Basketball, descriptive, Football, March Madness, team evaluation

The Achievement S-Curve: 2/13/2012

February 14th, 2012 — 12:08am

Quick update on the Achievement S-Curve.

First, the bracket and the full ASC data here:

The ASC is converging with Bracketology. Besides differences in doling out the automatic bids, just two of Lunardi’s at-large teams were not in my bracket–BYU and Arizona–and they were my very first two teams below the cut line. One of the two spots went to Nevada since I give the WAC auto bid to New Mexico St. The other went to Northwestern, who I have all the way up at a 9-seed. I think the Wildcats are not being given due credit for their tough schedule, which I have ranked 10th toughest. Since I touched on Northwestern last week, I’ll use another Big Ten team that I believe is underseeded as this week’s example: Illinois.

Bracketology has the Illini as a 12-seed while the ASC sees their resume as worthy of a 6-seed. For comparison’s sake, since I have already picked on Florida in the past, I’ll spare them and go after their in-state rival Florida St. (#11 in the ASC, #6 in Bracketology). I’m going to debut a new tool to help display a team’s schedule. These graphs show a team’s schedule from toughest game to easiest. Green bars show wins while red bars indicate losses. The gray bars represent the opposite score for that game should the outcome have been flipped. This allows us to see exactly how a team is arriving at its score.

Here are the graphs (no cool name yet, but I should come up with one) for Illinois (on top) and Florida St. on the bottom (try clicking twice to view them larger). Continue reading »

Comment » | College Basketball, descriptive, March Madness, predictive, team evaluation

Who’s REALLY Going Dancing?

February 10th, 2012 — 12:08am

Around this time of year, there’s lots of talk about who’s in and who’s out and who’s on the bubble. Plenty of chatter about what may or may not get your team into the Big Dance. Tons of discussion of big wins and bad losses.

I’ve spent the past few weeks posting my Achievement S-Curve, an objective, reward-based system of who should be in the tournament if the season ended today. But the season is not going to end today, despite how much Murray State may have wanted it to end before they took their first loss to Tennessee State tonight. It’s interesting and fun to play committee member and decide the fates of 345 college basketball teams more than a month before the actual brackets are released. But what we really should be interested in is what is going to happen the rest of season.

It’s cool to see that overachievers like Murray State and San Diego State have climbed into the top half of the bracket, but if we know they’re likely to come down to earth a little bit that’s much more insightful. Conversely, underachievers like Alabama or Saint Louis might be on the bubble right now but if they’re going to work there way off of it and into the bracket, we shouldn’t really care too much.

The Solution: Simulation Continue reading »

Comment » | College Basketball, descriptive, March Madness, predictive, simulation, team evaluation

The Achievement S-Curve: 1/30/2012

January 30th, 2012 — 11:04pm

Those following along (those that have not, start here, here, and here) know that the goal of the Achievement S-Curve is to reward teams for what they have accomplished on the court. Wins and losses count. Strength of schedule counts. Scoring margin, the eye test, true team strength…they don’t count.

There are good arguments against simply selecting and seeding teams based on who is the most deserving as opposed to just the best teams. For one, some people simply prefer to select the best teams and see them go at it in the tournament. Secondly, while seeding teams based on achievement rewards the top teams with good seeds and likely easier paths in the tournament, you may sometimes inadvertently hurt some of these teams who draw teams that underachieved during the season. Take Washington as an example from last season–they were a top 10 team by some rankings of the best teams but underachieved and drew a 7-seed. A team that earned a 2-seed would actually be better off as a 3-seed drawing an easier 6-seed as opposed to being slotted across from the Huskies.

So, this week, I offer two alternative S-Curve systems: Continue reading »

Comment » | College Basketball, descriptive, March Madness, predictive, team evaluation

The Achievement S-Curve: 1/23/2012

January 23rd, 2012 — 11:04pm

I will try to update this every week, though I won’t provide nearly as much commentary. For an introduction and explanation, try these three posts.

This week, I’ll get right to it with the chart. As always, the full S-Curve with additional information can be found here.

This week, I’ll tie in some comments about this week’s ASC as examples for what are the main differences between my ratings and ESPN’s Bracketology by Joe Lunardi (and other similar “bracketology” predictions). Continue reading »

Comment » | College Basketball, descriptive, March Madness, team evaluation

The Achievement S-Curve: 1/16/2012

January 16th, 2012 — 5:26pm

Last year, I introduced the Achievement S-Curve. The idea behind it was that teams should be rewarded for their season based on their wins and losses and the strength of their schedule. This is in opposition to the other camp of evaluating and seeding teams for the tournament, where teams are judged based on who is the “best” regardless of record. I discuss this dichotomy in further detail in this post from last year.

Methodology

The result was my Achievement S-Curve, and I’m bringing it back for a second go-round this year. I explained the methodology last year, but I’ll give a quick summary here: Continue reading »

Comment » | College Basketball, descriptive, March Madness, team evaluation

An Assessment of Total Quarterback Rating

August 4th, 2011 — 11:27pm

Earlier today, ESPN released (some) details of their brand new rating system for quarterbacks dubbed Total Quarterback Rating, or Total QBR (or even further abbreviated, just QBR), aimed at replacing the popular yet flawed Passer Rating. So what is it? And is it a worthy replacement?

To answer that question, let’s first take a look at what is currently out there, which will let us compare Total QBR and pinpoint the major differences.

Continue reading »

Comment » | descriptive, Football, player evaluation, review

Back to top