Formula to predict baseball success

March 2nd, 2010 - 4:07 pm ICT by ANI  

Nevada (US), Mar 2 (ANI): A Iowa State University physicist has come up with a formula to predict baseball success.

Kerry Whisnant studies the mathematical mysteries of baseball, including a long look at how the distribution of a team’s runs can affect the team’s winning percentage.

He recently took up a decades-old formula written by Bill James, the baseball author and statistician who inspired sabermetrics and is a senior adviser for baseball operations for the Boston Red Sox. The basic formula, which has been tweaked over the years, uses the number of runs scored per game (RPG) and runs given up per game to estimate a team’s winning percentage.

Whisnant took that formula a step further by considering run distributions.

Whisnant’s answer: W1/L1 = (RPG1/RPG2)^a (SLG1/SLG2)^b

Where

a = 0.723 (RPG1 + RPG2)^.373

and b = 0.977 (RPG1 + RPG2)^( -.947)

“I hated math in school, just write me a very condensed summary Kerry,” a baseball fan wrote to dugoutcentral.com, a Web site for baseball talk and analysis, when Whisnant posted his formula there.

Whisnant’s reply: “Bottom line: More consistent teams (narrower run distribution) tend to win more games for the same RPG (runs per game). Teams with higher SLG (slugging percentage) tend to have a narrower run distribution. Given two teams with the same RPG, a team with a SLG .080 higher will on average win one more game a season. If their pitching/defense has the same RPG allowed but a SLG allowed .080 lower, that would add another game.”

So there you have it: “The more consistent a team is in scoring runs, game to game, the better the team’s winning percentage for the total number of runs scored,” Whisnant said.

“My study shows that runs alone don’t tell the whole story,” he said. “Consistency is another factor. You want to score runs, and you want to be consistent.”

Across an entire 162-game season, Whisnant said more consistency could mean two additional wins. And that can be the difference between making the playoffs and calling it quits the first week in October.

Whisnant’s paper explaining the formula was recently named one of four finalists in a contest sponsored by the Massachusetts Institute of Technology’s Sloan Sports Analytics Conference in Boston on March 6. (ANI)

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