Two More Brackets: Strong Predictors vs. Strong Predictors and My Instinct

Who knew analytics could be so much fun? I write about them for a living, but applying them to sports has made them come alive for me. As a result, I took the advice of the Watson Analytics March Madness Prediction worksheet I created and decided to base another bracket on what the worksheet says is a stronger predictor based on Pomeroy’s data: the combination of tempo rank and Pythagorean rank.

WAP2

Watson Analytics provided even stronger combinations, but they were all related to how losses drive wins, so I had to discard them. Anyway, 71% strong was good enough for me.

The result of applying this combination to the bracket was a lot more interesting than using Pythagorean rank alone. I now have a better understanding of why there’s a trend of a 5 seed losing to a 12 seed. My problem is that I haven’t been able to figure out which 12 seed. However, according to my prediction worksheet, Wofford’s combination of tempo rank and Pythagorean rank was more likely to lead to a win than Arkansas’s combination, so that’s where that upset could come.

I did have to make some judgment calls. Based on the statistics, Kentucky is one of four teams that have the combination most likely to lead to wins. The other three are Villanova, Gonzaga, and Notre Dame. This means that Notre Dame and Kentucky must meet in the Final Four. I went ahead and picked Kentucky to win based on the fact that Kentucky is undefeated and John Calipari’s NCAA tournament resume.

I’m also sad to report that Harvard’s combination of tempo rank and Pythagorean rank was better than UNC’s, so apparently my karma for enjoying Duke’s early exits has come due.

There were other surprises, such as UCI’s much better combination than Louisville’s. Also, the analysts who have been saying that Utah is most likely to challenge Duke are correct; Utah’s combo is just a tad less winning than Duke’s. Interestingly, Duke will be no match for Gonzaga when they meet. I’m hoping that because this is a statistical bracket, Gonzaga will make it far enough to play Duke, because usually when I have them going far, they lose early or if I have them lose early, they go far. This. Happens. Every. Single. Year. Enough whining. Here’s the bracket.

Midwest

Midwest 2

West

West2South

South2East

East2

Final Four and Champion

FF2

And finally, I decided I would also take the Watson Analytics information and combine it with some other factors such as the team’s coach’s tournament resume and my personal bias. I’m exhausted from all this cutting and pasting, so I’m just going to show my Final Four and Champion from that bracketFF3. If it turns out this bracket is more of a winner than the others, I’ll post it at the end of the tournament.

I would be remiss if I didn’t mention that my friend Mark Buerger has suggestions for people who would like human help with their brackets. (Hi, buerg!)

Of course, if the Tar Heels would like to defy all statistics and win it all in memory of Dean, I would be content.

 

 

How I Decided to Take a Different Tack for my Brackets This Year

In 1997, I won my company’s March Madness pool and that’s the last time that one of my brackets did not turn into a sea of red by the end of the first weekend. I blame Gonzaga. Since they started getting into the tournament, they never do what I predict and the downward spiral begins. So, this year I decided to avoid going with my gut or listening to analysts, since the results have been disastrous. It is time for drastic action; it’s time to be more scientific.

My decision to try a new process coincides with my work with IBM’s cloud analytics service that anyone can use for free (with limitations) just by registering at www.watsonanalytics.com. You can upload a spreadsheet of data and get information about it with the service, which is called Watson Analytics. I’m a subscriber to Ken Pomeroy’s data (http://kenpom.com/), so I decided to use his data combined with win-loss records and upload it into Watson Analytics to help me fill out my NCAA bracket.

I uploaded the data and decided to use the predict function to see what most influenced wins. I decided to do a very simple analysis where I would simply see what 1 factor was most likely to affect wins based on Pomeroy’s data. After discarding the information that losses were a strong predictor of wins, I found that Pomeroy’s PythagRank was the next strongest predictor of wins.

WinsSo, I filled out my bracket based on Pomeroy’s Pythagorean Ranking. It’s not full of huge surprises, but it’s interesting and it has teams going far in the tournament that I would not have picked on my own. So maybe I’ll have more success with this one. I’m also considering creating another bracket based on a combination of factors such as RankPythag and RankTempo, which Watson Analytics tells me is an even stronger predictor of wins.

For now, I’m going to post screen shots of my bracket where the winners of each game was picked based on Pomeroy’s Pythagorean rank, and I’ll return after the first four and next round of games happen to see how this bracket is doing.

Midwest

MidwestEast

EastWest

WestSouthSouth

Final Four and Champions

FF

 

 

 

 

 

 

I would be remiss if I didn’t mention that my friend Mark Buerger has suggestions for people who would like human help with their brackets. (Hi, buerg!) After all, the human element is rarely more evident than during March Madness.

2014 Selection Show Live Blog

 

A New Shot Clock for College Basketball: 24 seconds

The 2012-2013 college basketball season has thus far been a season of major upsets and equality across the nation. For the neutral and hardcore fan alike, it has not been a season of great offensive efficiency.

A quick Google search reveals numerous stories from headline sources detailing the historically low offensive season to date. Furthermore, television ratings (and the almighty dollar bill) have been in decline for a few years.

What does it all mean? A dying sport, or one in transition? Only time can really tell, but there is one solution the NCAA can implement as soon as next season: a new, shorter shot clock. The shot clock, first introduced at an agonizing 45 seconds in the 1985-1986 season was later trimmed to the current 35 second variation in the early 1990s. Now is the time to take the next evolution in the game and move to 24 seconds.

1. The NBA

Many college basketball fans share an aversion for the NBA. Regardless of the feelings of the hardcore fan, the league represents the highest level of basketball in the world. College basketball, often viewed as a feeder league to the NBA (especially in the one-and-done era), needs to move closer to the NBA style.

The current 11 second gap between the two shot clocks is superfluous. Although the nostalgic view holds college basketball in an unrealistic light in regards to the student athlete, collegiate sports have become a means to an end for the high level athlete. Even the mid-level high school recruit who statistically has only a slim shot at the NBA views college basketball as just a step in the long process of reaching their dream.

Accepting the reality of college basketball’s place, a 24 second shot clock helps the players develop at quicker paces. Allowing the players to develop quicker, allows them to become more efficient, and thus delivering a higher level of quality on the hardwood. Higher quality play is an aspect desperately absent from the current college game.

2. The Neutral Fan

There’s always a danger in a league catering exclusively to the neutral fan, but the perspective is important here. Neutral fans are not watching the college basketball regular season as often as years past according to the link above. Increased television ratings, the focal point of conference realignment on the football side, can benefit the sport in the long term.

Although college football will remain the dominant force in realignment, college basketball does not have to sit idly to the side and go a long for the ride. Increased television ratings by catching neutral fans from improving the quality of play will allow for the potential of greater revenue from television deals to go alongside the revenue from college football.

3. The Modern Athlete

Given the advances in medicine and science, the athlete today is in better shape than the athlete of years past. Why not cater to the new breed of athlete by quickening the pace of games?

Many freshmen enter college campuses with toned bodies due to strict training regimens. Others undergo huge transformations during the first few months on campus due to better diets and training emphasis from their coaches.

Today’s players are better equipped to handle a quicker paced game.

4. Increased Scoring

A 24 second shot clock gives each team, at a minimum, one full possession per minute of the game while one of the teams receives another half possession. Under the current 35 second clock, only one team is guaranteed a full possession per minute of game time.

Increased possessions in a game will allow teams to possess the ball more and subsequently score more. Even if shooting percentages drop or, more likely, stay the same, they’ll be able to score more points per game by virtue of having more opportunities to score.

Under the 24 second clock, each team is guaranteed 60 possessions at a minimum each game. Assuming, hypothetically, a team shot 40% for a game, did not attempt a three point field goal, did not achieve a single offensive rebound, and all made shots were two points, that team would score 48 points.

48 points does not sound too appetizing, but when one considers the extremeness of my hypothetical, it provides a good baseline. Teams will receive other points from put-back attempts on rebounds, three point field goals, and foul shots.

Let’s dream up another hypothetical: a team takes 60 shots (20 three pointers and 40 two points), shoots 40% for all shots from the game, and again received no foul shots or offensive rebounds. That team would score, at a baseline minimum, 32 points from two pointers and 24 from beyond the arc for a combined 56 per game. Again, not very appealing numbers until taken into the context of the rarity of the hypothetical (a game with no offensive rebound put-backs, foul shots, and each team receiving only the minimum amount of possessions per game).

Add 15 foul shots to the last hypothetical at a 60% clip and an additional 9 points are added to the game. Increase the amount of possessions due to up-tempo teams, turnovers created by pressure, etc. and one can see the baseline minimum points provides a good starting point for increasing the scoring of college basketball teams.

Conclusion

The dwindling television ratings, the decreased scoring, the modern athlete, and college basketball’s status as a feeder league to the NBA all point in the direction of decreasing the shot clock to 24 seconds. The decreased clock will eventually increase the overall quality of play and immediately increase the points per game attracting new neutral fans which will increase television ratings. It is important for college basketball to continue evolving to better match the professional game in quality.

Bracketology 2-20-13

Midwest Regional(Indianapolis, IN)   East Region(Washington, DC)
1. INDIANA(B1G) 1. MIAMI(Fl)(ACC)
16. NU(CAA) SOUTHERN(SWAC) 16. NIAGARA(MAAC)
- Dayton Arena(Dayton, OH) - Rupp Arena(Lexington, KY)
8. UNLV 8. OREGON(PAC 12)
9. Oklahoma 9. Creighton
5. Colorado State 5. Illinois
12. Iowa State/Villanova 12. MTSU(SUN BELT)
- Sprint Center(Kansas City, MO) - HP Pavilion(San Jose, CA)
4. KANSAS STATE(BIG 12) 4. MARQUETTE(BIG EAST)
13. LOUISIANA TECH(WAC) 13. Temple
3. Louisville 3. Kansas
14. MONTANA(BIG SKY) 14. NORTHWESTERN ST(SLAND)
- Dayton Arena(Dayton, OH) - Sprint Center(Kansas City, MO)
6. Minnesota 6. Missouri
11. Charlotte/Arizona State 11. California
7. San Diego State 7. Cincinnati
10. VCU 10. North Carolina
- Wells Fargo Arena(Philadelphia, PA) - Palace Auburn Hills(Auburn Hills, MI)
2. Syracuse 2. Michigan
15. VERMONT(AM. EAST) 15. DAVIDSON(SOUTHERN)
West Regional(Los Angeles, CA) South Regional(Arlington, TX)
1. GONZAGA(WCC) 1. Duke
16. ROBERT MORRIS(NEC) 16. NSU(MEAC)HPU(Big. So.)
- Energy Solutions Arena(SLC, UT) - Wells Fargo Arena(Philadelphia, PA)
8. Colorado 8. LaSalle
9. WICHITA ST(MVC) 9. UCLA
5. Oklahoma State 5. Wisconsin
12. BUCKNELL(PATRIOT) 12. Baylor
- Frank Erwin Center(Austin, TX) - Energy Solutions Arena(SLC, UT)
4. Butler 4. Georgetown
13. VALPARAISO(Horizon) 13. AKRON(MAC)
3. NEW MEXICO(Mtn. WEST) 3. Arizona
14. SOUTH DAKOTA ST(SUMMIT) 14. HARVARD(IVY)
- Frank Erwin Center(Austin, TX) - HP Pavilion(San Jose, CA)
6. Notre Dame 6. NC State
11. BELMONT(OVC) 11. Ole Miss
7. Ohio State 7. Cincinnati
10. MEMPHIS(C-USA) 10. ST. LOUIS(A-10)
- Rupp Arena(Lexington, KY) - Palace Auburn Hills(Auburn Hills, MI)
2. FLORIDA(SEC) 2. Michigan St.
15. MERCER(A-SUN) 15. LONG BEACH ST(BIG WEST)

Last 4 IN: Iowa State, Charlotte, Villanova, Arizona State
Last 4 OUT: Kentucky, St. Mary’s, Virginia, Boise State
Next 4 OUT: Maryland, Massachusetts, Alabama, St. John’s
Next in Line: Iowa, Southern Mississippi, Indiana State, Arkansas

Bids by Conference:
(8) Big East
(7) B1G
(6) A-10, Big 12, Pac 12
(4) ACC, Mtn. West
(3) SEC
(2) MVC