The purpose of this post is to announce a relaunch of The Ticker, a feature I had previously published on this site for the 2011-2012 NBA season. The idea behind the ticker is pretty much the same as a normal stock ticker: to provide realtime information on what the market is thinking. However, where sites like Google Finance can just report stock prices over time directly, to do the same for sports betting requires some mathematical manipulation on my part.
In general, the betting market doesn't tell us directly who it thinks are the best and worst teams are in the league. Instead, all we get is the betting market's evaluation of the relative strength of the two teams that happen to be playing each other on that day. In baseball, this evaluation of relative strength shows up in the moneyline, which basically tells you what the market thinks each team's probability of winning the game is. The Methodology page has a simple example of how I translate these relative strengths into absolute rankings. You can also refer here for details specific to MLB betting, or here for my first publication of this ranking methodology at the Advanced NFL Stats Community site.
Data SourceMy data source for much of what I publish on this blog, including the information that makes up The Ticker, is Killer Sports. It's a great resource for anybody looking for detailed statistical and betting information that is updated daily. As a bonus, it is provided in a very structured, database-like format.
OverviewHere is a summary of the various charts and tables. These will all be updated daily with the latest game results and betting information.
- Table: This chart ranks all 30 teams according to the Generic Win Probability (GWP) metric. It also shows how the rankings break down between offense and defense (oRAA and dRAA), Generic Total (GTOT), and season to date Win-Loss record. Each metric also has a corresponding sparkline, showing how the team has progressed throughout the season. On a single page, you get a ranking of all 30 teams, how offense and defense each contribute to that ranking, how these rankings compare to season-to-date wins and losses, and the sparklines tell you how each team got to the position they are currently in.
- RAA: Stands for "Runs Above Average". It's the average expected margin of victory for that team when playing against a league average team. The chart itself shows how that team's RAA has varied over the course of the season, much in the same way that the charts on Google Finance show how a particular company's stock price has varied over the course of a day/week/year.
- oRAA: Stands for "Offensive Runs Above Average". It's the component of RAA that is attributable to team offense.
- dRAA: Stands for "Defensive Runs Above Average". It's the component of RAA that is attributable to team defense and pitching.
- Table: This chart ranks the top 50 pitchers, showing both the pitcher's RAA metric (how many runs that pitcher is expected to prevent, relative to the league average) as well as a sparkline showing how that pitcher has progressed throughout the season.
- RAA: The RAA charts over time for those same top 50 pitchers. Essentially an expanded version of the sparkline.
A Note About the Sparklines and Data VisualizationThe sparklines in both the team and pitcher charts are set so that the scale is identical for each team/pitcher. For the team charts, the scale is such that the 30th ranked team is at the bottom of the range and the 1st ranked team is at the top. For the pitcher chart, the bottom is the 50th rank pitcher and the top is the 1st ranked. If you see a gap in the pitcher's sparkline, it's when they dropped out of the top 50.
The goal is to show meaningful variation. The Texas Rangers' GWP sparkline is very "boring" by normal data visualization standards, but that flatline tells you that not only are the Rangers currently considered an elite team, but that the betting market has considered them elite from the beginning of the season.