America’s pastime is ripe with opportunities to dust off your data visualization tools and practice your Big Data swing.
As spring begins and bees collect pollen for honey, baseball statisticians collect millions of interesting facts about this year’s baseball season. Ever since the 1870s when sportswriter Henry Chadwick began pulling together players’ data, people have been keeping score on everything from hits and runs to strikeouts and averages.
This year is no exception. There are more than 40 million people playing baseball in the United States alone, distributed between 30 Major League Baseball teams, college teams, little league teams, and guys like me playing on the weekends. That’s a lot of data to collect, even for the seasoned statistician.
Baseball stat fanatics love their averages. They even collect obscure facts such as Weighted On-Base Average (also known as wOBA). According to Riley Brown’s data blog entry “10 Obscure Baseball Sabermetrics“:
“[The] wOBA combines the relative values of each offensive event and weighs them against the actual run value to their team. For example, a single during the 2012 season had a weight of 0.884 because that is the league-average run value that the single will produce. The final number is calculated similar to Slugging Percentage, but encompasses more ways in which a batter can reach base.”
Here’s how one MLB Division’s the 2010 wOBA looks, according to Beyond The Boxscore’s Bill Petti:
While the presentation looks simple enough, the data is based on multiple layers: batting average, walks, being hit by a pitch, etc.
This is where a personalized analytics tool like BIRT can help. Remember that in assessing Big Data such as baseball stats, you’ll need a powerful tool that can scan multiple sources of disparate data and present it in a compelling way. So swing for the bleachers with the BIRT Viewer Toolkit.
The Viewer Toolkit, a free companion package to the Eclipse open source BIRT Designer,IS MADE for developers seeking to embed or integrate BIRT reports within their web applications. The toolkit is a supported, commercial-quality alternative to the sample viewer included in the open source distribution of BIRT.
The Viewer Toolkit allows for: