Should we now be referring to Chris Tillman as an ace? Well, it depends on what you mean.
In the past, I have found that the most contentious part of the discussion is trying to define what it means to be an ace. Some like to think an ace is the best pitcher on a team, but that definition has some trouble. For example, think about the Diamondbacks with Curt Schilling and Randy Johnson. They certainly were both aces. Others like to think of an ace as being one of the best 30 pitchers in baseball, as in one for each team, but why exactly should we think that there are always 30 aces at all times in baseball? I would think that, like anything, there would be lean times and robust times when it comes to pitching.
Personally, I tend to use the definition that several scouts I know use: An ace is a pitcher who consistently provides elite performance. Using that as a definition, you wind up with anywhere between five to 10 aces in all of baseball. Why? Lots of pitchers wash in and wash out of elite performance. Very few arrive at that level and stay. When you want to discuss a pitcher who is an ace, you want to be sure of that elite performance, as opposed to someone who simply has the potential of elite performance. That is a rather selective definition and it probably should be.
Moving forward, you can use a few different ways to declare a pitcher an ace. You can ask evaluators or look at the numbers. What do the evaluators think? My unscientific polling found agreement on Clayton Kershaw, Felix Hernandez, Yu Darvish, Chris Sale, Max Scherzer and David Price. They thought there were certainly other good pitchers, perhaps ones that used to be in their minds an ace (e.g., Adam Wainwright), but that was their current view.
From the scout side, you never hear about Tillman in the discussion. As he was coming up through the minors, he had potential for a plus fastball and a plus curveball. However, he lost his velocity on his fastball and he has trouble with his curveball command. He is largely considered a good mid-rotation arm and nowhere near an ace.
If you wish to go after advanced metrics, you might use something like fWAR, a holistic statistic that leans heavily on events that a pitcher can control (such as strikeouts, walks and home runs). Using that metric, we would consider a pitcher with an fWAR over five wins to be an elite pitcher. To average that over four seasons might be considered ace-worthy. That would give you Kershaw (18.1 fWAR), Hernandez (17.3) and Scherzer (15.9). Pitchers who might make that level as the season winds down include Justin Verlander (14.8), Sale (14.8), Price (14.3), Wainwright (14.1) and Darvish (14.1). Those two lists are actually fairly similar with only Verlander and Wainwright added to the mix. The highest-rated Orioles pitcher over that time is Wei-Yin Chen at 6.1 fWAR. Tillman is at 5.3 fWAR.
Again, fWAR likes to look at strikeouts, walks and home runs (among other things). With those measures, Tillman looks worse than average. Tillman’s 7.07 strikeouts per nine innings over the past three seasons is 78th-best out of 130 pitchers with a qualified number of innings. His 2.90 rate of walks per nine innings is 87th-best. His 1.19 rate of homers every nine innings is 112th overall. However, his 3.45 ERA over that time period is 34th-best, which is about 20 percent better than those three previous figures would suggest (4.26 FIP).
What would account for those differences? Well, a great defense could work wonders on a pitcher’s ERA. If we look at the Orioles defense over the past two and a half years, we see the club is worth about 70 runs saved per season. Tillman would be seeing about 12 runs saved personally. If you add those runs back in, he has a 3.69 ERA. That only accounts for 25 percent of the difference in expectation versus actual result. That other 75 percent may be either that Tillman can do things that we cannot measure very well or that he has had an amazing string of luck. With the time frame being two and a half seasons, I lean toward the ability side over the luck side.
In the end, Tillman is a kind of pitcher who has shown he can do more than he seems capable of doing. In time, he may be considered an ace, but he will need to continue to be successful year in and year out to earn that distinction. Unlike others with loud tools, he will not simply be given the ace moniker.
Showing posts with label MASN Buzz. Show all posts
Showing posts with label MASN Buzz. Show all posts
09 September 2014
20 May 2014
The Value of a Buck
Last Saturday, Buck Showalter left the Orioles to see his daughter graduate from law school. While Mets second baseman Daniel Murphy was hammered in the sports world for missing games for the birth of his daughter, there has been little negative about Showalter taking time off for arguably a lesser family affair. One reason may be that after the reaction Murphy received, members of the sports media realized that perhaps they went to a little off the deep end. Another reason could be that the gulf between Murphy and his backup, Eric Young Jr., is much greater than the difference between Showalter and bench coach John Russell. Russell was at the helm for the Pittsburgh Pirates from 2008 through 2010 for a grand total of 486 games - or 82 more than the number under Young’s belt.
However, to be assured of a competent level of performance in the dugout by the experience of a person as a manager is a mighty large assumption. Over the years, we have witnessed many a manager racking up a few seasons of scribbling lineup cards who appeared to not help out the club all that much. One of the difficulties in figuring out the value of a manager is that his actions are difficult to separate from those of the players.
For instance, Joe Torre was considered a good tactician when it came to managing a bullpen, but much of that was due to having a guy like Mariano Rivera sitting out there. At Camden Depot, we tried to tackle this question by looking at projections. We compiled them from 2003 through 2013. Projected wins were compared with actual wins and those differences were attributed to the managers.
First, we decided to check and see how many seasons of data it took to make as accurate as possible. What we found was pretty remarkable. One season’s worth of data explained roughly 40 percent of year-to-year differences from the projected win total. If we compare two years of managerial data to two years, we wind up with a little above 70 percent, and the metric does not appear to improve from there. In other words, two years of data appears sufficient to describe a manager’s ability to perform against what is expected of his team by projection models.
Second, we wondered if these numbers were actually a function of the general manager. Within our data set, we had 24 managers who spent two seasons with one general manager and then two with another general manager. We compared those records and found that almost 80 percent of the difference could be attributed directly to what the manager brought to the club. This way to measure a manager’s ability seems strangely legitimate.
Now I am not ready to declare a victory here, but it certainly gives us a tool that shows some semblance of being useful in describing the value of a manager. So, going back to the original thought, should we expect the team to perform any differently under John Russell? Well, Russell and Showalter are both in our data set and both have more than two years of experience in that data set. Based on our study, Showalter was the eighth-best manager and was worth 4.1 wins above projected per season. Russell was the second-worst manager on our list and was worth minus-7.7 wins above projected per season. The puts Showalter as being worth 11.8 wins more than Russell over a whole season.
For a single game, well, we will have to use some math that I won’t share here for brevity’s sake, but try to trust me that a win is worth about 9.6 runs this year. That would suggest that a team under Showalter would perform 113 runs better than one led by Russell (those runs can come from increased offensive, defensive, or pitching performances). If accurate, the difference between the two is astronomical. That means with Russell in charge, the Orioles might be in the hole 0.7 runs per game. Last year, that was the difference between nine innings of Scott Feldman and nine innings of Jason Hammel.
I would not say that Showalter would have been able to lead the club to a win in the game where Russell was in charge, but I will say that I feel more comfortable now that Buck is back in the dugout.
However, to be assured of a competent level of performance in the dugout by the experience of a person as a manager is a mighty large assumption. Over the years, we have witnessed many a manager racking up a few seasons of scribbling lineup cards who appeared to not help out the club all that much. One of the difficulties in figuring out the value of a manager is that his actions are difficult to separate from those of the players.
For instance, Joe Torre was considered a good tactician when it came to managing a bullpen, but much of that was due to having a guy like Mariano Rivera sitting out there. At Camden Depot, we tried to tackle this question by looking at projections. We compiled them from 2003 through 2013. Projected wins were compared with actual wins and those differences were attributed to the managers.
First, we decided to check and see how many seasons of data it took to make as accurate as possible. What we found was pretty remarkable. One season’s worth of data explained roughly 40 percent of year-to-year differences from the projected win total. If we compare two years of managerial data to two years, we wind up with a little above 70 percent, and the metric does not appear to improve from there. In other words, two years of data appears sufficient to describe a manager’s ability to perform against what is expected of his team by projection models.
Second, we wondered if these numbers were actually a function of the general manager. Within our data set, we had 24 managers who spent two seasons with one general manager and then two with another general manager. We compared those records and found that almost 80 percent of the difference could be attributed directly to what the manager brought to the club. This way to measure a manager’s ability seems strangely legitimate.
Now I am not ready to declare a victory here, but it certainly gives us a tool that shows some semblance of being useful in describing the value of a manager. So, going back to the original thought, should we expect the team to perform any differently under John Russell? Well, Russell and Showalter are both in our data set and both have more than two years of experience in that data set. Based on our study, Showalter was the eighth-best manager and was worth 4.1 wins above projected per season. Russell was the second-worst manager on our list and was worth minus-7.7 wins above projected per season. The puts Showalter as being worth 11.8 wins more than Russell over a whole season.
For a single game, well, we will have to use some math that I won’t share here for brevity’s sake, but try to trust me that a win is worth about 9.6 runs this year. That would suggest that a team under Showalter would perform 113 runs better than one led by Russell (those runs can come from increased offensive, defensive, or pitching performances). If accurate, the difference between the two is astronomical. That means with Russell in charge, the Orioles might be in the hole 0.7 runs per game. Last year, that was the difference between nine innings of Scott Feldman and nine innings of Jason Hammel.
I would not say that Showalter would have been able to lead the club to a win in the game where Russell was in charge, but I will say that I feel more comfortable now that Buck is back in the dugout.
22 April 2014
The Orioles Have an Average Defense
There has been a storyline that has been trumpeted a bit on air and in the media that has not actually been true. You often hear about the club being proficient at fielding and this centering on their ability to avoid errors. At the time of this writing (after a particularly gruesome Sunday), the Orioles had the second-fewest errors in baseball. Only the Houston Astros had less.
On the surface, this looks great. On the surface, our old friend Henry Chadwick (the guy who invented the box score a century and a half ago) would say that errors do not give you the entire story of a player’s or team’s defense.
The problem with only looking at errors, or even the slightly more sophisticated fielding percentage, is that you are only considering batted balls that the player can actually get to. In a previous article, I mentioned the fallacy here as being the Rubbermaid paradox. To restate, if you put a Rubbermaid trashcan out on the field, that trashcan would have no errors and would have cleanly caught a few pop ups giving it a wonderful 1.000 fielding percentage. The paradox here is in the perception. Someone who only considers fielding percentage and errors would be under the impression that the trashcan is a Hall of Fame worthy defender while in actuality, it would be the worst defender that baseball has ever seen. This awareness of the deficiencies in traditional statistics plants a recognized desire to find better quantitative ways to evaluate defense.
Last year saw the Orioles have the fewest errors in baseball history with 54. The team also had the highest fielding percentage at .991. That led people to say that the Orioles had an elite defense. They were right, but the numbers that provided that foundation were not the best ones to use. A better argument would have leaned on more advanced statistics like Ultimate Zone Rating (UZR), which can be found at FanGraphs. How does UZR work? The field is cut up into 64 squares and each batted ball is defined by which square it lands into as well as whether it was a ground ball, line drive, or fly ball. How these scenarios play out provides a baseline or average defensive expectation for each fielder along with the number of runs expected when a certain balls lands a certain way in a certain square.
In other words, Manny Machado plays third base. A number of batted balls come through the zones he covers on the field. MLB as a whole has a certain probability of making plays on each of those balls hit. You then compare Machado’s performance against what the average major leaguer does. For the balls that skate through the hot corner, we know from the MLB database how many runs wound up scoring on average. We then can associate a run value lost for each play Machado misses as well as a run value gained for each he makes. This tells us how many runs saved or lost his performance last season was worth. With respect to 2013, Machado was first with 33.6 runs saved over what an average third baseman would have been expected to save.
How did the team stats look last year? The Orioles ranked third (48.6 runs saved) and were outperformed by only the Diamondbacks (49.7 runs saved) and the Royals (87.6 runs saved). The team also performed well in UZR’s throwing arm (eighth), double play (fifth), range (12th), and error (eighth) metrics. You perform that well on all of those individual measures, you wind up with an elite defensive club.
However, this year’s club currently sits 15th in all of MLB in UZR. They are showing well for throwing arm (eighth), double play (seventh) and error (fifth) metrics, but are 23rd for range. The main problems have been the continued erosion of Nick Markakis’ range, Nelson Cruz’s expected poor coverage, and, surprisingly, J.J. Hardy’s performance. Of those, we should only expect Hardy to get better due to his performances in years past and the likelihood that his range troubles are related to his nagging injuries. In general, things should improve when Machado returns as well. The current Orioles third basemen, Jonathan Schoop and Ryan Flaherty, are performing on a projected value of minus-18 runs or about 50 runs worse than Machado over a full year.
For the Orioles to compete, the defense needs to be elite. Right now, it is not.
On the surface, this looks great. On the surface, our old friend Henry Chadwick (the guy who invented the box score a century and a half ago) would say that errors do not give you the entire story of a player’s or team’s defense.
The problem with only looking at errors, or even the slightly more sophisticated fielding percentage, is that you are only considering batted balls that the player can actually get to. In a previous article, I mentioned the fallacy here as being the Rubbermaid paradox. To restate, if you put a Rubbermaid trashcan out on the field, that trashcan would have no errors and would have cleanly caught a few pop ups giving it a wonderful 1.000 fielding percentage. The paradox here is in the perception. Someone who only considers fielding percentage and errors would be under the impression that the trashcan is a Hall of Fame worthy defender while in actuality, it would be the worst defender that baseball has ever seen. This awareness of the deficiencies in traditional statistics plants a recognized desire to find better quantitative ways to evaluate defense.
Last year saw the Orioles have the fewest errors in baseball history with 54. The team also had the highest fielding percentage at .991. That led people to say that the Orioles had an elite defense. They were right, but the numbers that provided that foundation were not the best ones to use. A better argument would have leaned on more advanced statistics like Ultimate Zone Rating (UZR), which can be found at FanGraphs. How does UZR work? The field is cut up into 64 squares and each batted ball is defined by which square it lands into as well as whether it was a ground ball, line drive, or fly ball. How these scenarios play out provides a baseline or average defensive expectation for each fielder along with the number of runs expected when a certain balls lands a certain way in a certain square.
In other words, Manny Machado plays third base. A number of batted balls come through the zones he covers on the field. MLB as a whole has a certain probability of making plays on each of those balls hit. You then compare Machado’s performance against what the average major leaguer does. For the balls that skate through the hot corner, we know from the MLB database how many runs wound up scoring on average. We then can associate a run value lost for each play Machado misses as well as a run value gained for each he makes. This tells us how many runs saved or lost his performance last season was worth. With respect to 2013, Machado was first with 33.6 runs saved over what an average third baseman would have been expected to save.
How did the team stats look last year? The Orioles ranked third (48.6 runs saved) and were outperformed by only the Diamondbacks (49.7 runs saved) and the Royals (87.6 runs saved). The team also performed well in UZR’s throwing arm (eighth), double play (fifth), range (12th), and error (eighth) metrics. You perform that well on all of those individual measures, you wind up with an elite defensive club.
However, this year’s club currently sits 15th in all of MLB in UZR. They are showing well for throwing arm (eighth), double play (seventh) and error (fifth) metrics, but are 23rd for range. The main problems have been the continued erosion of Nick Markakis’ range, Nelson Cruz’s expected poor coverage, and, surprisingly, J.J. Hardy’s performance. Of those, we should only expect Hardy to get better due to his performances in years past and the likelihood that his range troubles are related to his nagging injuries. In general, things should improve when Machado returns as well. The current Orioles third basemen, Jonathan Schoop and Ryan Flaherty, are performing on a projected value of minus-18 runs or about 50 runs worse than Machado over a full year.
For the Orioles to compete, the defense needs to be elite. Right now, it is not.
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