There were two baseball stories that I read today that I found incredibly interesting, and I wanted to highlight them here.
Mark Simon had a great post this morning comparing the hang time on a game-changing bloop double the Yankees allowed to the Twins a few weeks ago to Brent Lillibridge’s catch of a Robinson Cano liner that ended a game this week. The takeaway:
Young’s fly ball had a hang time of 4.4 seconds. BIS was able to determine that a ball hit to a spot within a 10 foot by 10 foot zone of that hit location was a base hit approximately 57 percent of the time at that hang time within the last year. So Swisher wasn’t the only player to miss out on a ball hit into that zone.
To show you the impact that the hang time of a fly ball has on a play, check out the chart on the right, provided the day after Young got his game-tying hit. Had that ball been in the air a few tenths of a second longer, it’s almost certainly an out.
On the other end of the spectrum is Lillibridge’s play. Cano’s line drive stayed in the air for just under 2.5 seconds. Within the last year, there were 61 line drives hit to that area, with hang times that rounded to 2.5 seconds. Lillibridge was one of only three players who were able to turn that batted ball into an out.
Click through to see the chart Simon refers to, which really is fascinating in its illustration of baseball as a game where half a second can make a huge difference. Flyballs in the zone where Young’s ball landed that had an extra hang time of 1 second resulted in 36% more outs, while an extra 1.5 seconds turned the play from an almost automatic hit to an easy out. Similarly, on line drives to the zone where Lillibridge made his catch, there seemed to be a tipping point between 3 and 3.5 seconds of hang time, where that extra half-second represents a change of 37% in out rate. This really drives home how baseball is a game of precision, where minute differences can alter the result of the game, as these two plays did in their respective contests.
Another interesting use for this data comes in the field of defensive metrics. Things like hang time data can help add further specificity to the zone data currently used by most metrics, and lend greater context to broad groupings such as “fly balls.” This will allow us to put greater trust in small samples of defensive data, as we can have greater confidence in our understanding and weighting of each data point.
Scott McKinney at BtB posted the first part of his look at whether good minor league systems lead to MLB success. While the answer seems kind of obvious, I think empirically proving that farm system success leads to major league success is an important confirmation of a long-held core belief of most fans and baseball insiders. The takeaway:
As you can see in the above graph, the data shows that organizations with a good minor league system tend to have more success in the five years after a good ranking than the average team by about four wins.
As you would expect, with more wins comes more playoff caliber teams. From 1996 to 2010 33.0% of all MLB teams achieved a pythagenpat win total of at least 87, thus giving them a decent chance of making the playoffs. For teams with top five minor league systems, the rate of superior success is 52.4%.
McKinney points out that large market teams benefit more from their systems than small market teams. This is likely attributable to the ability for a large market club to supplement their homegrown talent with free agents once they have a core that can contend. In part 2, McKinney will look at the balance between homegrown talent and free agents on such teams, something that I think should be interesting to Yankees fans. With a club like the Yankees, the farm system serves to supplement the older core of the club that will usually contain a number of high priced free agents. Conversely, a team like the Twins will be built around homegrown talent and then will fill in with free agents. I am curious to see if there is an “optimal” balance, at which a team can best control costs while continuing to win games.
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