Category Archives: Sports

Bracket is perfect through day 1

I have two brackets, one based on my model results below (always picking team with better total coefficient) and one based on my own picks. The one based on my own picks went 16/16 yesterday.

Maria’s own picks also went 16/16, and we did not fill out our brackets together. We do have differences in choices today, so at least one of us will not be perfect come the round of 32.

Strength of March Madness Teams

Similar to last year and the year before, I will run my NFL model over NCAA men’s basketball teams to show the strength of each team. The model predicts how many more points a team will score than the “average” team, along with how many more points they will give up on defense. The model is only based on the final scores of games during the season. Positive numbers are good for Offensive strength. Negative numbers are good for defensive strength. My model does not discount (late season runs matter no more than early season victories) and does not account for injuries.

Some things to note:
1. 8 tournament teams are worse than an NCAA Division 1 average team.
2. The top 12 teams are within 5 expected points of each other.
3. West Virginia is the 3rd best team (2nd year in a row) and got a 4 seed. Wichita State is the 11th best team and got a 10 seed.
4. The best teams not to make the tournament are Indiana (14.2 points above average, should be an 8 seed), TCU (13.5), Syracuse (13.0), and Texas Tech (12.9). Illinois State, who went 27-6, is only the 13th best team not to make the tournament (10.1).
5. Wichita State, Oklahoma State, West Virginia, Wisconsin, Marquette, Wake Forest, and Kansas State all deserved seeds that were at least 3 better.
6. Maryland, Minnesota, Arizona, Dayton, and Butler all deserved seeds that were at least 3 worse.

Sports Links 20170308

Lots of interesting sports stuff (to me at least) in my feed reader this afternoon:

March Madness selection favors deserving teams (good win-loss record) over good teams (lots of talent).

Yes, Kentucky likes basketball. Twice as much ESPN viewing in Louisville as Raleigh/Chapel Hill/Durham.

You picked the wrong target, hacker. Don’t mess with Ohio football.

Dangerous takeoff for Michigan basketball team.

Some Explanations for the bad betting results this year

My NFL betting model had a bad year. Apparently, so did sportsbooks in Las Vegas.

NFL favorites went 135-126 against the spread this past season, not counting pushes. It is the third-best mark for favorites in the last 14 seasons. And 141 games went over the total, with 124 staying under, the third-best mark for overs in the last 14 years, according to sports betting analytics site Betlabsports.com on Sports Insights. The betting majority almost always gravitates to the favorite and over, which makes it a bad combination for the books.

To boot, the New England Patriots, the consensus Super Bowl favorites throughout the season and a public favorite, went 16-3 ATS, tying the 1989 San Francisco 49ers for the best single-season ATS record in the last 40 years. In contrast, the Cleveland Browns, widely considered the biggest long shots in the league and the only team to be underdogs in every game, went a league-worst 3-12-1 ATS.

My model tends to choose underdogs due to the regularization of offense and defense strengths. Basically, I assume regression to the mean, and there was no such regression for the Patriots, Browns, Rams, or 49ers this year.

My record in games involving the Patriots: 5-12-1 (the third number is pushes or ties against the spread)
My record in games involving the Browns: 5-9-1
My record in games involving the Patriots: 4-9-2
My record in games involving the Patriots: 5-9-1

Overall in games involving those four teams: 19-36-4 (they played each other in 4 games after week 1).

“You want to gamble against the public, but at some point you’d like to see a team cover. It’s hard to be that bad and not cover, because the spreads get so inflated.”

“I would say 100 percent [the sharps] struggled,” Bogdanovich said.

Also:

“The average margin of victory in 2016 was the lowest in history, relative to total points per game.”

2016-2017 NFL Betting Summary

Loved the first half of the Super Bowl. Still in disbelief about the rest.

The model stunk this year. No other way to say it. Unfortunately. It did much better last year and the year before.

I don’t have a definitive reason yet, or a good postmortem, but my gut says that this was just a weird year. A few teams were great to start the year and then tanked. A few others were terrible to start and then went on a run. Using a model that is just based on the past scores, those sorts of things are going to screw up performance.

Overall Against the Spread: 105-133
Week 2: 8-8
Week 3: 10-6
Week 4: 6-9
Week 5: 5-8 (1 push)
Week 6: 7-6 (2 pushes)
Week 7: 3-11 (1 game not bet)
Week 8: 6-7
Week 9: 5-6 (1 game not bet, 1 push)
Week 10: 8-6
Week 11: 7-4 (1 game not bet, 2 pushes)
Week 12: 5-10 (1 push)
Week 13: 4-11
Week 14: 8-8
Week 15: 5-9 (1 game not bet, 1 push)
Week 16: 7-9
Week 17: 7-8 (1 push)
Wild Card: 0-4
Division: 2-2
Conference: 2-0
Super Bowl: 0-1

NFL Picks – Super Bowl 2016

The model picks the Patriots (equally good on offense and defense) by 1 over the Falcons (exceptional at offense), unfortunately. Does pick the Falcons against the spread, though.

Overall Against the Spread: 105-132
Week 2: 8-8
Week 3: 10-6
Week 4: 6-9
Week 5: 5-8 (1 push)
Week 6: 7-6 (2 pushes)
Week 7: 3-11 (1 game not bet)
Week 8: 6-7
Week 9: 5-6 (1 game not bet, 1 push)
Week 10: 8-6
Week 11: 7-4 (1 game not bet, 2 pushes)
Week 12: 5-10 (1 push)
Week 13: 4-11
Week 14: 8-8
Week 15: 5-9 (1 game not bet, 1 push)
Week 16: 7-9
Week 17: 7-8 (1 push)
Wild Card: 0-4
Division: 2-2
Conference: 2-0

NFL Picks – Conference Round 2016

Overall Against the Spread: 103-132
Week 2: 8-8
Week 3: 10-6
Week 4: 6-9
Week 5: 5-8 (1 push)
Week 6: 7-6 (2 pushes)
Week 7: 3-11 (1 game not bet)
Week 8: 6-7
Week 9: 5-6 (1 game not bet, 1 push)
Week 10: 8-6
Week 11: 7-4 (1 game not bet, 2 pushes)
Week 12: 5-10 (1 push)
Week 13: 4-11
Week 14: 8-8
Week 15: 5-9 (1 game not bet, 1 push)
Week 16: 7-9
Week 17: 7-8 (1 push)
Wild Card: 0-4
Division: 2-2

Book Review – Ahead of the Curve

Ahead of the Curve: Inside the Baseball Revolution
by Brian Kenny, 2016

We (Maria and I) met Brian Kenny at the 2013 SABR Analytics conference. He was the keynote speaker, and advocated such things at knuckleball academies (to train knuckleball pitchers), bullpenning (using your bullpen more effectively and moving away from the dominance of the starting pitcher), and a information-saavy managerial staff to replace intuitive managers. He’s incredibly well-spoken and brings that to his work on ESPN and MLB Network, and now to his book.

Kill the win. Kill the save. Don’t sign big-money free agents. All are topics in this book, but I think the overwhelming theme is that we need to halt the tyranny of backward-thinking sports media that constantly attacks and belittles analytical thinking. Great book.

Pairs well with Moneyball, obviously (my reading of that one pre-dates when I was writing book reviews for my website). Also pairs well with Big Data Baseball, Mathletics, How to Measure Anything, and Thinking, Fast and Slow.

Amazon Link: Ahead of the Curve: Inside the Baseball Revolution

NFL Picks – Division Round 2016

Ha, I doubt it, but there’s a chance switching from Python 2 to Python 3 mid-season introduced a bug into my code. The results have been awful since then. 0-4 wild card. Ha. Just keep chugging.

Overall Against the Spread: 101-130
Week 2: 8-8
Week 3: 10-6
Week 4: 6-9
Week 5: 5-8 (1 push)
Week 6: 7-6 (2 pushes)
Week 7: 3-11 (1 game not bet)
Week 8: 6-7
Week 9: 5-6 (1 game not bet, 1 push)
Week 10: 8-6
Week 11: 7-4 (1 game not bet, 2 pushes)
Week 12: 5-10 (1 push)
Week 13: 4-11
Week 14: 8-8
Week 15: 5-9 (1 game not bet, 1 push)
Week 16: 7-9
Week 17: 7-8 (1 push)
Wild Card: 0-4