Search results for ‘achievement s-curve’
Selection Sunday 2013 is in the books. Time to release the final Achievement S-Curve of 2013 and see how it compares to the actual bracket.
The 2013 Achievement S-Curve (click twice to embiggen):
It’s time to re-introduce the Achievement S-Curve for the 2013 season. For those of you that are new, I’ll give a quick recap in this post but check out previous posts that go into more detail about the system (try this and this and this for starters).
The Achievement S-Curve is a descriptive rating system that attempts to rate teams based on what they have accomplished. It is a subtle yet important difference from a predictive rating system. While a predictive system attempts to answer the question “who would win if these two teams played today?” a descriptive system answers “who has accomplished the most in the games they’ve already played?”.
An example is probably the best way to demonstrate the differences between the two systems. Let’s take a real-life example. My predictive rating system says that New Mexico is the 33rd best team in the country. That is, there are 32 teams I’d favor over the Lobos, but I’d pick them to beat every other team. Pitt, meanwhile, is the 7th best team. Only six teams in the nation would be favored over the Panthers today. However, New Mexico is 22-4 against the 29th-hardest schedule thus far while Pitt hasn’t fared as well with a 20-7 record against a very similar schedule (24th-most difficult). It is clear that New Mexico has “achieved” more thus far this season than Pitt has. The Lobos have earned a higher seed than Pitt, despite the fact that Pitt would beat them more times than not. Continue reading »
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 »
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 »
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 »
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 »
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.
In my last post, I discussed evaluating teams based on what they accomplished (“most deserving”) versus what they are capable of (“best”). I argued that in selecting teams for the NCAA Tournament, only a team’s wins and losses–not their margin of victory, their statistics, or their “look”–should be considered against their schedule strength in order to determine which teams deserve the reward.
Today, I put my plan into action. I introduce to you the “Achievement S-Curve”. There is no margin of victory, no rebounding margin, no NBA prospects, and certainly no “eye test” where the ASC lives. The ASC doesn’t care how you won or lost, just if you won or lost. This is based solely on each team’s achievements to-date, not their future projections.
First, a disclaimer. I am NOT projecting what the NCAA Tournament field will look like. There are plenty of sites that do that already and do it well (although, when you get spotted 31 of 68 teams, it’s not all that difficult). What I am concerned with here is what the field SHOULD look like…what the committee should look at in determining who is selected and how they are seeded. Continue reading »
Decided to dust off the ol’ blog for the new College Football Playoff system. I’m simply going to apply my Achievement S-Curve [see here] to college football to see who should be selected for the inaugural CFB Playoff this year.
Quick summary of what the Achievement Rankings are doing: determine the most deserving teams based on on-field accomplishments. From each team’s perspective all that matters is whether they won or lost, and how difficult the game was (opponent strength, home/away, etc.). For opponent strength, however, we are free to use a more predictive rating, or true strength. Simple example: the Arizona Cardinals at 8-1 against a tough schedule would come out on top of a most deserving ranking in the NFL and if they season ended today, they certainly deserve the #1 seed. However, the Broncos or Packers or maybe even Seahawks may be the best team and would come out on top of a predictive system (say, Inpredictable‘s, which has DEN #1, GB #2, NE #3, SEA #4…and ARZ #14).
There are two choices to make to utilize my system: you need a rating system to determine the difficulty of the game (mostly the strength of each opponent, but also home-field advantage, etc.) and you need to choose a baseline team to compare against. I’m going to use Sagarin‘s Predictor rating to determine opponent strength and for now, I’ll use the equivalent of the #10 team in the country as our baseline team since we are trying to determine the top 4 teams. So for each team I’ll find what record we’d expect the #10 team in the nation (think Ohio State or Oklahoma) to have had they played their schedule, and we’ll use Sagarin to determine that.
Let’s take Florida State as an example. Here’s their schedule with how often both the #10 team and the #25 team would be expected to win each game:
|Loc||Opponent||#10 Team||#25 Team|
On average, we’d expect the #10 team to win about 8.5 games against this schedule, and the #25 team would win 7.25 on average. Since Florida State is 10-0, their score is +1.5 or +2.75, depending on the baseline team you choose.
Here are the rankings with a #10 team as the baseline:
And if we lower the baseline to the #25 team, we get:
I prefer the higher baseline, which gives more credit to top wins and less to middle tier wins. In either system, the top 4 are Alabama, Florida State, Oregon and Mississippi State, albeit in different orders. TCU, Baylor, and Auburn are next in line in the #10 version. UCLA climbs up to #6 in the #25 version, as they have a bunch of middle-tier wins (Virginia, Memphis, Texas, Washington, etc.). It’s up to you what type of resume you want to reward.
A couple quick notes:
- College football teams play so few “connecting” games (i.e. non-conference games) that team strength ratings (like Sagarin) are very sensitive to these and conferences as a whole can move up or down the ratings based on just a handful of out of conference matchups. The SEC is certainly very strong this year, but it’s possible they as a conference are overrated due to this phenomenon.
- This system does not incorporate certain things that others may thing they should. Some of these I’m okay with: conference championships, for instance, or recent performance. Others, I am strongly against: head-to-head and especially the dreaded “eye” test.
In any case, I’m excited to see how the whole thing plays out. College Football finally has a Playoff.
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 »