Saturday, October 31, 2015

New Live Feature: The "SO" calculator

You were so preoccupied with whether or not you could,
you didn't stop to think whether you should.
Depending on your perspective, you may consider this a neat feature or an abomination.

Continuing work from last year's playoffs, I am sharing live win probability graphs on my site for all regular season games (although I'm still working out some kinks in the implementation).

In addition to the standard win probability metrics from last year, there is a new table that accompanies each graph, which I'm calling the "SO" Calculator ("SO" being short for Significant Other).

Most of us have been in the position where our wife/boyfriend/child/etc. does not care about a game we are watching and simply wants to know when it's going to be done. And most of us lie. If there is 4:55 on the clock, well say "about five minutes". And with a straight face too.

Thursday, October 29, 2015

Turnover Index Week 8

Unfortunately, there are no bets this week that satisfy our wagering criteria, but here are the week seven results:

Wednesday, October 21, 2015

Turnover Index Week 7 - Expect the Jets to Regress

We're off to a good start for the 2015 season. Our first bet against the spread was successful, with the Browns covering (just barely) against the Broncos as a 4 point underdog. Here are the results (we'll add a row to this table each week):

weekbetswonstarting
bankroll
amount betprofitsending
bankroll
6 1 1 $1,000 $49 (5.0%) $45 $1,045

There have been no shortage of surprising starts this NFL season (it's been positively weird). Among those surprises are the New York Jets, who have won four of their first five, despite an offseason marred by coaching changes, bad debt, and sucker punches.

Over those first five games, the Jets have averaged three turnovers per game on defense, which currently leads the league. But turnover success on defense is fleeting, and history suggests the Jets are unlikely to maintain this pace throughout the season. Going back to the 1989 season, here is how teams have fared after racking up at least 15 defensive turnovers in their first five games (48 teams in total):

Teams with at least 15 Defensive Turnovers in their 1st 5 Games
turnovers/gmwin percentagainst the spread
Games 1-53.272%68%
Games 6-162.052%45%


Wednesday, October 14, 2015

The Return of the Turnover Index

Make money betting on the NFL with this one simple trick!

For the past three NFL seasons, I have been publishing picks against the spread based on a simple betting strategy. That strategy, in a nutshell, is to bet on teams with a much lower defensive turnover total (season-to-date) than their opponent.

In the NFL, turnovers are largely random events. They correlate somewhat with team offense, but hardly correlate at all with team defense. However, the betting public has been slow to recognize this fact. Teams that have amassed strong records by "forcing" defensive turnovers may be overvalued by the market.

That's the theory, anyways. In practice, results have been modest. Over three seasons, my picks have gone 40-34-2 against the spread. That's enough to eke out a slight profit, but nothing spectacular. And it is somewhat below the 59% cover rate implied by my original analysis.

Sunday, October 11, 2015

NFL Week Four Power Ranking Roundup

This time last year, nobody was quite sure what to make of the 2-2 Patriots. In my power ranking roundup post from last year, here is where six different ranking systems placed them:
  • Simple Ranking System - #26
  • Football Outsiders' DVOA - #23
  • FiveThirtyEight Elo - #7
  • ESPN Power Rankings - #16
  • Inpredictable Market Rankings - #14
  • Advanced Football Analytics' Efficiency Rankings - #27
As we know, the Patriots went on to win 10 of their 12 remaining regular season games en route to another Superbowl title - an outcome predicted with eerie prescience by Skip Bayless (of all people):
The New England Patriots will rise like the phoenix from the ashes of Monday night's 41-14 loss in Kansas City and land at the University of Phoenix Stadium in Glendale, Arizona, playing in Super Bowl XLIX.
This year, however, there is no confusion, only consensus. The New England Patriots are the #1 team across all six power rankings after week four of the season. As a reminder, I archive these week four rankings and then test their accuracy in predicting future wins, once the season is finished.

Saturday, October 10, 2015

PitchF/x for the NBA

One of sports analytics' first "big data" moments came with Major League Baseball's introduction of PitchF/x in 2006. With the help of cameras installed in each stadium, each pitch is now tracked at an obsessive level of detail. Where once we had just "ball" or "strike", pitches can now be classified according to pitch type, velocity, release point, and movement.

In addition, strike zone position is also tracked for every pitch, and can then be converted into nifty looking scatter plots, such as those found on Fangraphs. The chart below is the scatter plot for Max Scherzer's recent no-hitter, his second of the season.
Earlier this year, I rolled out my attempt at PitchF/x-style analysis for the NBA. "ShotF/x" would have been a snappy name, but probably a trademark violation. So, I called it ShArc instead, short for Shot Arc Analysis. In that initial post, I used a simple physics model to examine the finer details of player free throw shooting - shot angle, release height, peak height, and accuracy. The raw data came from SportVU, the NBA's version of the PitchF/x system. Because the data was noisy, I applied some basic physics to tease out the most likely trajectory from the scatter of data points.