Research & Analytics

November 04, 2011 12:00 AM GMT
The question, then, is whether we can estimate the "correct" hr/f for a given player. An even more important question is whether we can use that information to predict regression from one season to the next. In two words: yes and yes.
October 26, 2011 12:00 AM GMT
A statistic frequently used to fuel speculation is the number of doubles a player hits - there is often conjecture that a player with a lot of doubles in one year might turn them some of them into HR the next. But does this actually happen with reliable frequency?
July 14, 2011 12:00 AM GMT
Part two of our series on rookie 2H/1H splits that span two seasons. This week, the pitchers.
July 08, 2011 12:00 AM GMT
Blurring the lines of rookie "seasons" to look for mid-year trends of 2010 callups.
June 23, 2011 12:01 AM GMT
There are many ways to get on base, but none are as dangerous or painful as being hit by a pitch. Bruise Rate, or BRU, measures the rate of HBP per 600 PA—or about one season. Check out the active leaders in BRU.
May 18, 2011 2:01 AM GMT
Many thousands of words have now been written about Toronto's Jose Bautista. No worthwhile forecasting system should have predicted more than 18-24 home runs for him entering 2010. But were there any logical indications that he could have not only beat that forecast, but that he could have more than doubled it?
May 11, 2011 12:00 PM GMT
We compare pitchers' 2010 and 2011 year-to-date performances with swing strike percentages, looking for pitchers where the change in SS% indicates a change in Dom different from what has happened so far.
May 04, 2011 12:00 PM GMT
What makes a strikeout? The first picture that comes to mind for many of us is that of a pitcher (probably a closer) blowing the hitter away with his fastball. So what are the pitch attributes that lend themselves to strikeouts more than others? We set out to explore that question this week by looking at PITCHf/x data.
April 27, 2011 12:00 PM GMT
Back in 2009, we began a series of research articles looking at hard-hit data for both batters and pitchers. The research confirmed what you might expect—pitchers with lower hard-hit rates (HH%) generally had better results: higher Dom, lower hr/f rates, and subsequently, lower ERAs. However, at the time of that original research, we didn't have enough years of data to conclude whether pitchers actually had any control over their hard-hit rates. Now we do.
April 20, 2011 12:00 PM GMT
Hunting? In April? Absolutely. The following analysis focuses on the hunt for new closers, with specific focus placed on the timing of transition from one closer to another. Once the hunt is complete and we have satisfied our craving for saves, we will return to the picture above to see if it holds any hidden meaning after all.

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