Stats in the Wild

Lost a few spots yesterday. Currently in 75th. I still need UConn and South Carolina to win in all in the Men’s and Women’s tournament, respectively.

Pre tournament probabilities that the remaining men’s teams would reach the Final 4:

UConn: 56.0% (100% in my aggressive Bracket)

Purdue: 51.8%

Tennessee: 18.2%

Alabama: 10.5%

Illinois: 8.11% (0% in aggressive Bracket)

Duke: 6.23%

Clemson: 2.87%

NC State: 0.87%

Pre tournament probabilities that the remaining men’s teams would reach the Final 4:

South Carolina: 82.5%% (100% in my aggressive Bracket)

Oregon St: 8.09% (0% in my aggressive Bracket)

Texas: 28.0%

NC State: 13.8%

LSU: 18.0%

Iowa: 28.4%

UConn: 27.5% / Duke: 1.37%

USC: 33.4% /Baylor: 4.21%

Cheers.

I thought I finally understood the scoring for this contest, but I can’t reproduce my score on the leaderboard. So I have no idea. But I’m at 141 after the first weekend. Unlikely to cash, looking to just finish top 100.

Sweet Sixteen probabilities for women: (Men’s Sweet Sixteen probabilities are here):

South Carolina: 91.9% (100% in aggressive bracket)
Indiana: 5.83% (0% in aggressive bracket)

Oregon St: 50.1%
Notre Dame: 41.9%

Gonzaga: 21.3%
Texas: 56.8%

NC State: 27.9%
Stanford: 65.4%

USC: 60.1%
Baylor: 12.2%

Duke: 5.1%
UConn: 47.2%

Colorado: 17.1%
Iowa: 56.6%

LSU: 34.0%
UCLA: 57.2%

Cheers.

Well, I’ve gone up in the rankings every scoring update. From 233rd to 170th to currently in 126th. Just about top 15%. That’s positive. And with the new scoring system, there is a ton of room to move up (and DOWN) very quickly.

Probabilities for women’s games today (remember these are pre-tournament probabilities that these teams would reach the Sweet Sixteen, NOT single game win probabilities):

Notre Dame: 79.33%

Ole Miss: 17.45%

NC State: 78.33%

Tennessee: 20.37%

Syracuse: 18.67%

UConn: 76.76%

Oklahoma: 26.11%

Indiana: 69.29%

West Virginia: 11.69%

Iowa: 83.15%

Creighton: 9.48%

UCLA: 85.15%

Kansas: 9.57%

USC: 85.8%

Utah: 40.58%

Gonzaga: 55.04%

And here are my probabilities for the men’s games next Thursday and Friday:

Thursday

Clemson: 7.75%

Arizona: 26.47%

San Diego St: 6.04% (0% in my aggressive bracket)

UConn: 71.53% (100% in my aggressive bracket)

Alabama: 21.37%

North Carolina: 51.43%

Illinois: 27.09%

Iowa St: 46.87%

Friday

NC State: 4.52%

Marquette: 38.57%

Gonzaga: 6.86%

Purdue: 69.26%

Duke: 12.87%

Houston: 69.82%

Creighton: 21.28%

Tennessee: 44.22%

In my aggressive bracket I have South Carolina and UConn winning the men’s and women’s titles with probability 100%. If that happens I pick up 0 loss for all those games in all 6 rounds. And 0 loss in the finals would be absolutely massive in reducing my score as it would be a full 1/6th of my score with 0 loss. So let’s go UConn and South Carolina!

Cheers.

Currently in 170th. Better than yesterday.

My Kaggle probabilities for the men’s games today:
(Remember, these aren’t probabilities that these teams will win this particular game, it’s the pre-tournament probability that they would make it to a particular round.)

Colorado: 18.3%
Marquette: 60.27%

Purdue: 84.1%
Utah St: 7.62%

James Madison: 11.67%
Duke: 50.77%

Clemson: 17.55%
Baylor: 53.01%

Grand Canyon: 13.95%
Alabama: 49.01%

Northwestern: 4.51% (0% in my aggressive bracket)
UConn: 88.83% (100% in aggressive bracket)

Texas A&M: 6.36%
Houston: 83.74%

Yale: 3.25%
San Diego St: 31.47%

My Kaggle probabilities for the women’s games today:
(Remember, these aren’t probabilities that these teams will win this particular game, it’s the pre-tournament probability that they would make it to a particular round.)

Colorado: 42.38%
Kansas St: 53.03%

South Carolina: 97.7% (100% in aggressive bracket)
North Carolina: 0.79% (0% in my aggressive bracket)

Ohio St: 77.5%
Duke: 19.72%

MTSU: 2.73%
LSU: 78.24%

Nebraska: 10.95%
Oregon St: 83.56%

Alabama: 10.63%
Texas: 82.88%

Iowa St: 6.96%
Stanford: 89.52%

Baylor: 36.57%
Virginia Tech: 57.18%

Go UConn.

Cheers.

The real stories everyone should be talking about are how David Carr beat Keegan O’Toole in the semi-finals of the NCAA wrestling tournament at 165, Carter Starocci had to wrestle former national champions back to back in the quarter- (Mekhi Lewis) and semi-finals (Shane Griffith) and he beat them both, and Drake Ayala of Iowa made the finals keep Iowa’s streak of THIRTY THREE years in a row with a national finalist alive.

But you probably want to read about basketball, huh?

So here’s a fun, simple data viz of wins by seed:

Below is a plot of wins by seed in the first round of the men’s NCAA tournament. The 6 and 8 seeds combined for only two total wins ((6)Clemson and (8)Utah State). At least one of every seed 1 through 14 advanced and seed 9 through 12 went went a combined 9-7. In total the lower seed won 11 of the first 32 games.

As for the Kaggle contest, I’m currently in 233 out of 820 (top 30%). Not great, but also not terrible either. There should be a lot more shuffling of the leaderboards in these later rounds with the changes in scoring, so it’s going to be way more exciting than past contests, I think. At least in terms of chaos.

Here are my probabilities for the women’s games today:

Tennessee: 78.2%
UConn: 100%
Kansas: 55.6%
Indiana: 98.0%
Notre Dame: 99.1%
NC State: 98.4%
Iowa: 100%
Syracuse: 72.0%
Oklahoma: 76.0%
USC: 99.3%
Ole Miss: 72.7%
West Virginia: 63.0%
Creighton: 56.2%
Gonzaga: 96.9%
UCLA: 99.0%
Utah: 76.0%

And here are my Kaggle probabilities for the men’s games today:
(Remember, these aren’t probabilities that these teams will win this particular game, it’s the pre-tournament probability that they would make it to a particular round.)

Arizona: 51.6% 
Dayton: 19.5%

Kansas: 47.4%
Gonzaga: 35.1%

UNC: 73.9%
Michigan St: 13.3%

NC State: 14.0%
Oakland: 1.78%

Iowa St: 71.6%
Washington St: 11.9%

Tennessee: 69.5%
Texas: 17.7%

Illinois: 55.5%
Duquesne: 5.83%

Creighton: 47.5%
Oregon: 16.8%

Finally, and most importantly, my numbers (8 and 2) hit in the Utah State-TCU game in NCAA sqaures. So worst case scenario, I only lose half my square buy-in. Lettttttt’s gooooooooooooo.

Cheers.

We all know about Super Bowl squares. But last night my friend asked me to be in an NCAA squares pool. I asked him how it worked and he explained to me that it’s the same as a Super Bowl pool, but you have the same numbers for all 63 games (not the stupid F-ing play-in games). So naturally, I wanted to know what the best numbers were. Here are the results based n data from 1985 – 2021, which is just the data that I happened find on my computer first.

The worst set of numbers are the ones that are the same. Since it’s based on only final score, the only way these numbers will hit if a team wins by exactly 10, 20, 30, etc. Also, note that in the pct column, if all squares were equally likely, the pct should be exactly 1% for every square. So even in the worst case (i.e. 1-1), the percentage isn’t that far off from what you would expect if each square was equally likely.

The best numbers are combinations that are all 2 or 3 digits away with 1-8, 0-8, 3-1, 5-2 and 9-6 being the top five all with probabilities that are essentially the same.

To better see the pattern, I made a 2d histogram for all the scores. Here, red, white, and green indicate combinations that are worse, about the same, and better than 1%. You can see the dark green band running up the diagonal of combinations that are 2 and 3 apart.

And just for comparison sake, here is the same plot with NFL scores:

Happy gambling in March!

Cheers.

My article “Here Comes the STRAIN: Analyzing Defensive Pass Rush in American Football with Player Tracking Data” with Quang Nguyen and Ron Yurko was selected for inclusion in the AMSTAT News Editor’s Choice Collection. This means you can read the full article for free (Note: You can always read any of my articles for free. If you just contact me, I’ll send you a free copy. Never ever ever pay the publisher fort access to my work, please).

While glancing through the list there were a few articles that I am particulars interested in reading:

• “The Twentieth-Century Reversal: How Did the Republican States Switch to the Democrats and Vice Versa?” by Andrew Gelman. I’m SO SICK of hearing people talk about how the GOP is the “Party of Lincoln”. Yeah, that’s technically true, but that entirely ignores history. I can’t wait to read this article. 
• “Integrating Data Science Ethics into an Undergraduate Major: A Case Study” by Benjamin S. Baumer, Randi L. Garcia, Albert Y. Kim, Katherine M. Kinnaird, and Miles Q. Ott. This author list is a who’s who of people I turn to when I am developing my courses. Baumer’s book (with Kaplan and Horton) is the foundation for our undergraduate Introduction to Data Science with R (DSCI101) course and our graduate version Introduction to Data Science (with R and Python) (DSCI401) course. 
• “Changes in Crime Rates During the COVID-19 Pandemic” by Mikaela Meyer, Ahmed Hassafy, Gina Lewis, Prasun Shrestha, Amelia M. Haviland. 

Cheers.

“People on the internet” (i’m talking about the anti-vax morons) scream about how myocarditis is a side effect of the vaccine, but big pharma doesn’t want you to know about. Chief, it’s literally listed on the CDC website. 

And if you are that worried about myocarditis, you know what causes myocarditis at much higher rates: Actual Covid-19!

Cheers.