February 23rd, 2016 — 1:05am
We’re less than one month from Selection Sunday, which means the burgeoning field often called Bracketology is in full swing. Bracketology has taken on some broader meanings over the years, but it most often refers to predicting the selection and seeding of teams in the NCAA Tournament bracket. ESPN’s Joe Lunardi (aka “Joey Brackets”) has made a name and a living on his projections and there are now so many bracketologists that there is a site called The Bracket Matrix that collects all of them (dozens and dozens), displays them in a matrix, and grades them when the final bracket is released.
As a March Madness lover, I am a fan of most things involving the tournament and endorse almost anything that brings interest and discussion to the event. While predicting the NCAA Tournament field certainly falls into that category–and I myself have dabbled in my version of it–there are some aspects of the current state of Bracketology that range from misguided to downright silly.
Continue reading »
Comment » | College Basketball, descriptive, March Madness, review
March 19th, 2013 — 12:20am
Despite what many television analysts might say, seeding does have an enormous impact on a team’s chances to advance in the tournament. Every seed line you move up increases your chances of going further in the tournament. But the seeds don’t always play out that way, and so when the bracket is released we can see exactly what matchups each team will face on their path through the tournament.
Indiana has a clear path to the Final Four
The Hoosiers head the easiest of the four regions. Their 2nd round opponent will be the easiest of the 8/9 matchups (NC State or Temple). In the Sweet 16, Syracuse could provide a stiff test but each other region has a 4 or 5 seed as good or better than the Orange. And the bottom half of Indiana’s bracket is by far the easiest of any region: Miami is the worst 2-seed, Marquette is the worst 3-seed (along with New Mexico) and none of the other teams provide much of a threat. Nobody is ever a shoo-in for the Final Four, there’s too many games against too many good teams, but Indiana definitely increased their odds on Sunday with the path they were dealt.
Also benefiting from this easy bracket is 6-seed Butler, who has a relatively easy path to the Elite 8. Could they shock the world…again…and make it to the Final Four? Continue reading »
Comment » | College Basketball, March Madness, predictive, team evaluation
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
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
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
February 23rd, 2012 — 7:34pm
This post was a 2-part guest post at TeamRankings.com. Here are Part 1 and Part 2.
With a month left in the season, most of college basketball is focused on who’s in and out of the tournament. Those teams near the cut line are on the Bubble, while teams that are securely in the tournament are Locks with little worry of falling out of the bracket and seemingly little left to gain with their dance cards punched.
Turns out, there’s still plenty to play for, especially at the top. As every fan knows, the NCAA Tournament is seeded from 1 to 16 in four separate regions. The top seeds are rewarded by being placed at locations close to home, protected from a home-crowd disadvantage, and–most importantly–pitted against easier opponents. That last point is even more pronounced than one might expect. Obviously every team wants to move up a seed line, but the importance of climbing each rung of the seeding ladder might surprise. Continue reading »
Comment » | College Basketball, March Madness, predictive, talent distribution, team evaluation
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
February 18th, 2012 — 7:05pm
One cool thing we can do with the rest-of-season simulation is look at the effect that the outcome of a specific game can have. As an example, take today’s headline BracketBusters game between Murray State and St. Mary’s that just finished. Entering today, the Racers had a 92.9% chance to get an at-large bid should they fail to win their conference tournament. With a loss today, that would have dropped to 88.6%, but Murray State was able to pull out the big victory at home and–at least according to the Achievement S-Curve–punch their ticket to the Big Dance.
Comment » | College Basketball, March Madness, Quick Slant, simulation, team evaluation
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
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