Sabermetrics, Scouting and Science of Baseball

The second annual Saber Seminar will be taking place on August 4th and 5th in Boston, MA. Bobby Valentine, Tom Tippett, Kevin Goldstein, Dan Brooks, and many more will be presenting at the conference. Beyond the Box Score's Glenn DuPaul will also be presenting about WAR. Anyone in interested in baseball statistics and the science of the game, should head to Boston for the weekend. Tickets are still available for "baseball's best fans" and all the proceeds for the conference benefit the Jimmy Fund and the fight against cancer.

Vote: The Hall of Fame Inner Circle Project

While my own research lately has been slow and sporadic, friend of BtB Graham Womack is back with another wisdom-of-crowds project. This time, he's looking for the top 50 players of all time to make up an Inner Circle Hall of Fame. The ballot contains all current players in the Hall of Fame, regardless of how they were inducted (BBWAA, Veterans, Negro League Committee, etc.). The ballot does not contain managers and those inducted because of other non-playing roles. Also, since it only features current Hall of Famers, you can't vote for Bob Caruthers. I know you were planning to, but you can't. Let's vote! I'm very curious what Graham finds with this project.

Who Is Baseball's Greatest Hitter?

Over at Baseball Nation, Rob Neyer has posed a simple, but difficult question: who is the greatest hitter in baseball? Rob's narrowed it down to Ryan Braun, Josh Hamilton, Joey Votto, Miguel Cabrera, and Matt Kemp. But the real question here is - how do you identify what makes someone the greatest hitter? What stats would or should you use? How recent should the data be? Share your thoughts here or over at Baseball Nation.

Win Expectancy Calculator

Based on the number of runs scored, I have determined that the formula for win expectancy is the following: Win expectancy = 1-((1/(RS+4.5))^((RS^1.14)/14.1)) [?] RS = runs scored I discovered the coefficients of 1.14 and 14.1 by calculating the cumulative amount of deviation from normal win expectancies (1969-2011), weighted for instances of runs scored, using an extremely vast array of coefficients in MS Excel, effectively using what I like to call a "bowl apparatus". Based on the repetition of the formulas with varying coefficients, 1.14 and 14.1 gave me the lowest cumulative deviation value. Remarkably, even though this was done using data only from 1969-2011, the correlation is even stronger (using these same coefficients) when data is expanded to 1901-2011, and actually accounted for many of the biggest deviations! This suggests that the formula works just as well, if not better, for games before 1969. The link above will take you to Baseball-Reference's situation calculator - try this for yourself! The link below has the collected data. Win expectancy chart (with deviations)

Will Pujols rebound?

Albert Pujols might be done hitting as we've known him.


Looking for the best Late-Bloomers in baseball's past.

Tweaking FIP: now with even less defense!

Here's some work I did recently on a modification of FIP that has even less dependence on defense and luck. The result is a metric with better year-to-year correlation with itself, and better predictive power for ERA. A lot of the comparison built off of a BTB post from earlier this year, so I just wanted to say thanks and to share the link for anyone who's interested.

Pitch Counts Pointless

Pitchers that throw more stay healthier. Why?

The BPP All-Time Dream Project | Baseball: Past and Present

A team of nine players to win a one-off, sandlot game. Featuring guest write-ups from an all-star team of writers, including BtB's own Adam Darowski.

Restricted free agency in MLB?

What would replacing arbitration with restricted free agency look like?

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