Saturday, September 24, 2016

NFL Playoff Implications - Week 3

Here are playoff implications for week three of the NFL season. The purpose of this feature is to highlight games that have a significant impact on the playoff picture (see this post for background).

The playoff implications below are derived from a 50,000 round simulation of the remainder of the NFL season. I use my daily NFL rankings to simulate future games. I can group the simulation runs by the outcome of each game and then see how a team's playoff chances vary between the two groups. The interactive table at the bottom of the post will allow you to see corresponding results for any game or team. The results of the Thursday night game have already been taken into account.

Ranking Week 3 Games by Leverage

The table below ranks the week 3 games by total leverage. Leverage in this context is a measure of both how uncertain a game's outcome is (games between evenly matched teams have higher leverage) and how much the playoff picture swings as a result of that outcome.

Saturday, September 17, 2016

NFL Playoff Implications - Week 2

Here are playoff implications for week two of the NFL season. The purpose of this feature is to highlight games that have a significant impact on the playoff picture (see this post for background).

The playoff implications below are derived from a 50,000 round simulation of the remainder of the NFL season. I use my daily NFL rankings to simulate future games. I can group the simulation runs by the outcome of each game and then see how a team's playoff chances vary between the two groups. The interactive table at the bottom of the post will allow you to see corresponding results for any game or team. The results of the Thursday night game have already been taken into account.

Ranking Week 2 Games by Leverage

The table below ranks the week 2 games by total leverage. Leverage in this context is a measure of both how uncertain a game's outcome is (games between evenly matched teams have higher leverage) and how much the playoff picture swings as a result of that outcome.

Sunday, September 11, 2016

NFL Playoff Implications - Week 1

Playoff implications return for the 2016 season. The purpose of this feature is to highlight games that have a significant impact on the playoff picture (see this post for background).

The playoff implications below are derived from a 50,000 round simulation of the remainder of the NFL season. I use my daily NFL rankings to simulate future games. I can group the simulation runs by the outcome of each game and then see how a team's playoff chances vary between the two groups. The interactive table at the bottom of the post will allow you to see corresponding results for any game or team. The results of the Thursday night season opener have already been taken into account.

Ranking Week 1 Games by Leverage

The table below ranks the week 1 games by total leverage. Leverage in this context is a measure of both how uncertain a game's outcome is (games between evenly matched teams have higher leverage) and how much the playoff picture swings as a result of that outcome.

Wednesday, September 7, 2016

NFL Market Rankings are Live

NFL Vegas rankings are live and will update daily for the remainder of the season. These rankings are an attempt to reverse engineer what the market "thinks". Markets tend to be efficient, and betting markets are no exception. It is difficult to beat the accuracy of the Vegas point spread over any extended period of time. Based on my own research, these Vegas rankings outperform a broad cross-section of NFL power rankings when it comes to predicting future wins.

The current version of the rankings reflect both the latest Week 1 lines and the opening lines for Week 2. Because there are not enough connections between teams with just two weeks of point spreads, I use the week 1-16 point spreads published by CG Technology (formerly Cantor Gaming) earlier this year to fill in the gaps. But once we have week 3 opening lines, the teams should all be connected and we can dispense with the outdated CG lines.

Tuesday, September 6, 2016

20 Years of WNBA Win Probability Graphs

The NBA season is still some two months away, but the WNBA season is in full swing. Regular season play has now resumed following the Olympics shutdown, and the playoffs are just a few weeks away.

One of my offseason goals this year was to extend many of the tools and analysis I had developed for the men's game to the WNBA. I started small last month with the addition of the WNBA to my suite of Vegas team rankings. Today, I have a much more substantial update to announce:

The following tools and stats are available for the entire 20 year history of the WNBA:


Building a Win Probability Model for the WNBA

The nice thing about this project is that I didn't have to start from scratch. WNBA data is structured very similarly to NBA data, so in a lot of ways, I could just point my existing code and methodology to a new dataset. The WNBA win probability model was built using the same approach as the NBA win probability model. It is based on play by play data for over 2,000 WNBA games, going back to the 2007 season.

Sunday, July 17, 2016

Betting Market Rankings for the WNBA

The WNB-Ays
I have added the WNBA to my suite of betting market rankings, to go alongside those for the NBA, NFL, MLB, College Football, and College Basketball. The purpose of these rankings is to reverse engineer an implied power ranking from the Vegas point spreads, essentially distilling the combined wisdom of the market.

Here are the rankings as of July 17:


GPF stands for "Generic Points Favored". It is what you would expect a team to be favored by against a league average opponent on a neutral court. By combining the betting over/under with the point spread, I can decompose GPF into its offensive and defensive components, oGPF and dGPF (note: offense and defense are on a points allowed per game basis, rather than points per possession - there is no way to derive implied per possession metrics from the betting data). GOU stands for "Generic Over/Under" and it is what you would expect the betting over/under to be for that team when playing an average opponent.

Saturday, July 16, 2016

Bonus Tim Duncan Chart - Bank Shots

On the occasion of Tim Duncan's retirement earlier this week, I used SportVU motion tracking data to call attention to an unnoticed element of his game: his low and tight, line drive shot arc.

Using that same data, we can also delve into a more well known aspect of Duncan's shooting game: his bank shot. For the bank shots I am able to identify, the chart below shows where Duncan's bank shots hit the glass. For comparison purposes, I also have a chart for all NBA bank shots.
Duncan seemed to favor the upper left portion of the glass, especially compared to the league average, which is clustered far more in the center, just at the top of the backboard's inner square.

On an unrelated note, I noticed that there appears to be a bias to when a scorekeeper will classify a shot as a bank shot, and that bias is skewed towards made shots. I have found several examples where the motion tracking data clearly shows a missed bank shot, but the official shot description does not call it out. For that reason, I would be skeptical of any stat that shows a particular player is far more effective when shooting bank shots.

Once I have the methodology cleaned up, I hope to use the SportVU create a deeper dive into the bank shot and the underlying physics (similar to last summer's post on the effects of air drag on a basketball's trajectory).