One way the Orioles have been able to overachieve in the Buck Showalter and Dan Duquette era is by milking every last drop out of the major league roster. That means constantly scouring the waiver wire, hoarding players with minor league options, using those options for both roster gymnastics purposes and to give players extra rest, selecting and keeping Rule 5 draft picks, and sending a never-ending supply of players back and forth on the Norfolk shuttle.
Duquette never stops looking for a way to improve the team's depth, and Showalter is (or at least seems to be) happy to oblige by picking and choosing from sometimes less-than-ideal choices and figuring out the best way to maximize their talents. Showalter is a master at this, particularly when it comes to reliever usage throughout a long season, and is very good at keeping his club's arms fresh.
The Orioles have never been shy about using roster rules and minor league options to their advantage, even when guys like Wei-Yin Chen were unpopularly optioned for a brief period of time in an effort to keep him healthy. Just wait and see how they try to take advantage of the new 10-day disabled list.
This upcoming season, though, is shaping up to be Duquette's and Showalter's greatest challenge in roster juggling. They seem to relish jumping through these hoops, and they've given themselves even more things to worry about than usual.
If figuring out what to do with two Rule 5 picks in Aneury Tavarez and Anthony Santander (likely DL bound) weren't enough, they also have to select a fifth starter among underwhelming options until Chris Tillman hopefully returns in May; figure out if Oliver Drake is worth losing if he doesn't make the 25-man roster (he's out of options); try and make room for Trey Mancini, who is mashing in spring training and is mostly blocked by Mark Trumbo's presence; figure out if Mancini and Pedro Alvarez can survive any amount of time in a major league outfield; and then also discover if Craig Gentry and Joey Rickard can form a successful right-handed side of a platoon with their left-handed counterparts in Hyun Soo Kim and Seth Smith.
The Orioles recently jettisoned Michael Bourn, who just a couple months ago seemed like a strong option to make the club. A broken finger from a botched football catch and his contract opt-out date took care of that, along with him never being a truly great fit with Kim and Smith around (plus Tavarez, who gets a slight bump for the Rule 5 designation).
No team plays the fringes quite like the Orioles, who, while maximizing the major league roster, spend very little on international players and have assembled a farm system that doesn't produce many great choices to round various positions of need. Mancini counts, for sure, but there's a reason why the O's have to experiment with outfielders who aren't outfielders, add guys like Vidal Nuno and Gabriel Ynoa as depth pieces in February, and play the Rule 5 game every season. That doesn't make them bad moves by any means. It's just what the Duquette and Showalter Orioles do. It can be frustrating, and you may wonder how much these peripheral moves really matter. But they do in some small way, as Duquette keeps the roster churning and Showalter figures out which pieces can be useful.
One day, when Showalter and Duquette are long gone, you won't have to pay such close attention to which players have options remaining or how many active roster days are left for a Rule 5 pick. They will be simpler times, but probably not better ones (except for the draft pick selling nonsense; no one will miss that).
27 March 2017
An April Win is Like Any Other Except Maybe the Orioles' April 2016 Wins
"April is the cruelest month, breeding lilacs out of the dead land,
mixing memory and desire, stirring dull roots with spring rain."
T.S. Eliot, the Wasteland
Spring is full of hope. That is certainly true with baseball where projections and predictions can be forgotten and a vision of success can intoxicate the mind. Wins can be exaggerated in importance and losses can be overlooked. The mind can be protected by a shield of acknowledged small sample sizes or the sword of actual successful outcomes. As they come, April is one of the cruelest for a baseball fan as it plays most with their ability to fully comprehend the talent of their chosen club.
A few weeks back, the site discussed the importance of a successful April slate of games. The basic conclusion was that if a team wins a lot in April then they will have a great shot at participating in the playoffs. This was a simple conclusion. We should expect good teams to win whether in April or May or whenever. On any given day, the teams that win are likely to be good teams because good teams win.
With that dip into frigid February waters, I wanted to take a different look at the importance of games played by month. I wanted to compare the importance of winning games in April vs. any other month. We know that good teams win, but does a particular month highlight which team is good?
Replacing the analysis I did on Monday, which I think was impacted by toddler brain rot, I went at it a couple different ways with best fit models using league data over the last three seasons. One, comparing the month record to the total record. Two, comparing the cumulative month to total record. Three, comparing the cumulative month to cumulative total of games for the rest of the season.
Month
|
Cumulative
|
Post
|
|
| April | 0.26 | 0.26 | 0.07 |
| May | 0.32 | 0.50 | 0.15 |
| June | 0.39 | 0.71 | 0.23 |
| July | 0.20 | 0.80 | 0.24 |
| August | 0.56 | 0.93 | 0.18 |
| September | 0.42 | 1 | NA |
With the monthly data, April has the second least correlation to the final season winning percentage. Cumulatively, we see what we would expect with certainty increasing as games played increases. Pre vs Post data suggests that much of the certainty we have is simply put in that games have counted as opposed to gleaning much information into what will happen.
Let's shake it another way. How does winning percentage in April compare to the season end total?
| Season |
Average
|
SD
|
Max
|
Min
|
| >550 | .587 | .086 | .773 | .476 |
| 450-550 | .500 | .104 | .714 | .292 |
| <450 font=""> | .423 | .108 | .583 | .217 |
I used a winning percentage of .550 to represent a likely wild card club or better. That is roughly 90 wins. What we see is that all three batches produced at least one team that looked interesting in April. However, over the past three seasons there has been no terrible April performers who wound up with 90 wins or more.
If we look only at clubs with a .476 winning percentage or greater in April, we cover those 19 high quality clubs, but also 39 more lesser teams. What this means is that historically, an April winning percentage of .476 or more has meant that you have a 33% chance at 90 wins. On the flip side, no team below .476 had 90 wins.
Another angle to look at would be in division games. One might expect that a certain number of teams may actually be impacted with team matchups. We should think that not all games are created equally. While overall record is what decides who gets into the playoffs, that is largely impacted by the leap frogging within the division. We might well expect that a division win or loss is more impactful than a win or loss outside of the division.
For the 2016 Baltimore Orioles, they will be facing in division competition 20 out of 23 games this April. This compares unevenly with last year's 12 out of 23 games. In fact, the Orioles' crunching of division rivals is not really all that common amongst teams. This not common occurrence may well be spread rather evenly amongst teams and would be obscured in the exercise above.
Therefore, I wanted to compare in division vs out of division records against what really matters: games back. In this analysis, I did not look at MLB records in 2016. Instead, my data set contained all AL East teams from 2012 until last season. What I found out was that a divisional game was about 29% more important than a non division game.
Anyway, chew on that for awhile.
24 March 2017
Chris Davis Should Swing More
One of the longstanding criticisms about the Orioles offense is their penchant to avoid walks like the plague. Since 2012, the Orioles rank 23rd in baseball in OBP, despite the fact that they are 6th in runs scored. The biggest reason? The team has hit far and away the most home runs in baseball during that time frame. One of the biggest reasons for that? Chris Davis, who leads all of baseball with 197 homers during that time.
Of course, Davis has been the best OBP guy on the team, posting a .340 OBP since 2012, a mark surpassed only by Nick Markakis (in fewer PA, naturally). Even in what has to be considered a down season in 2016, Davis still finished second on the team with a .332 OBP, and in general runs an OBP that is far better than his batting average, making him almost like a unicorn on this particular team.
This should be great! The O's need OBP guys, and Davis is one of the most patient hitters on the team. It's likely one of the reasons that he may be the best leadoff option on the team. The problem, however, is that the more selective Davis has been in his career, the less success he has seen overall. Davis' walk rate has increased every single season since 2012, with his 13.2% in 2016 representing a career high, but produced his two worst offensive seasons in 2014 and 2016. This is a puzzle, as in general we'd expect high walk rates to correlate with increased offensive success.
One of the factors that may be able to explain this somewhat odd occurrence is to look at how often Davis actually swings the bat, since you can't hit homers and produce big offensive numbers unless you hit the ball. Davis swung at his lowest rate ever last season, swinging at just 42.7% of pitches. His career mark is 49.4%, and in his breakout 2013 season he swung at over 50% of the pitches he saw. To his credit, Davis swung at the fewest pitches outside of the strike zone in his career last season, but the flip side of that is he swung at the fewest percentage of pitches in the zone as well. In fact, the decline in this metric was so precipitous that it almost leads me to question whether his hand injury was far more severe than was reported. Unless his eyesight also declined last season, there is little other reason for why he went from swinging at 68% of strikes in 2015 to just under 60% in 2016.
This also brings up the issue of strikeouts, which is something that any discussion of Davis simply can't avoid. That Davis strikes out a lot is not news. What is interesting, however, is how he strikes out. Davis has, by far, the most called third strikes in baseball since 2012 with 279, and had 79 called third strikes in 2016, which is also the most by far for any player in any season since 2009. Some of that is a simply function of the sheer volume of strikeouts he racks up, but looking a bit deeper into the yearly fluctuations of called K's is particularly interesting. Below is a table of Davis' called strikeout percentage, his Weighted Runs Created (WRC+) and his Weighted On Base Average (wOBA) by year.
Of course, Davis has been the best OBP guy on the team, posting a .340 OBP since 2012, a mark surpassed only by Nick Markakis (in fewer PA, naturally). Even in what has to be considered a down season in 2016, Davis still finished second on the team with a .332 OBP, and in general runs an OBP that is far better than his batting average, making him almost like a unicorn on this particular team.
This should be great! The O's need OBP guys, and Davis is one of the most patient hitters on the team. It's likely one of the reasons that he may be the best leadoff option on the team. The problem, however, is that the more selective Davis has been in his career, the less success he has seen overall. Davis' walk rate has increased every single season since 2012, with his 13.2% in 2016 representing a career high, but produced his two worst offensive seasons in 2014 and 2016. This is a puzzle, as in general we'd expect high walk rates to correlate with increased offensive success.
One of the factors that may be able to explain this somewhat odd occurrence is to look at how often Davis actually swings the bat, since you can't hit homers and produce big offensive numbers unless you hit the ball. Davis swung at his lowest rate ever last season, swinging at just 42.7% of pitches. His career mark is 49.4%, and in his breakout 2013 season he swung at over 50% of the pitches he saw. To his credit, Davis swung at the fewest pitches outside of the strike zone in his career last season, but the flip side of that is he swung at the fewest percentage of pitches in the zone as well. In fact, the decline in this metric was so precipitous that it almost leads me to question whether his hand injury was far more severe than was reported. Unless his eyesight also declined last season, there is little other reason for why he went from swinging at 68% of strikes in 2015 to just under 60% in 2016.
This also brings up the issue of strikeouts, which is something that any discussion of Davis simply can't avoid. That Davis strikes out a lot is not news. What is interesting, however, is how he strikes out. Davis has, by far, the most called third strikes in baseball since 2012 with 279, and had 79 called third strikes in 2016, which is also the most by far for any player in any season since 2009. Some of that is a simply function of the sheer volume of strikeouts he racks up, but looking a bit deeper into the yearly fluctuations of called K's is particularly interesting. Below is a table of Davis' called strikeout percentage, his Weighted Runs Created (WRC+) and his Weighted On Base Average (wOBA) by year.
| Year | Called K% | WRC+ | wOBA |
| 2012 | 24 | 121 | 0.352 |
| 2013 | 24 | 168 | 0.421 |
| 2014 | 32 | 94 | 0.308 |
| 2015 | 27 | 148 | 0.390 |
| 2016 | 36 | 111 | 0.340 |
In years when Davis takes fewer called third strikes, he is at worst an above average hitter and at best one of the game's elites. In years where he takes a higher number of called third strikes, however, he is below average to slightly above.
Now, this may be sample size noise and there are likely other factors that contribute to Davis' offensive inconsistency, but it seems fairly clear that the less aggressive Davis is the less successful he is offensively. A strikeout is an out regardless, but a called third strike is probably the least productive out simply because there is no possibility of anything good happening. In Davis' case, it's doubly unproductive because he hits the ball extremely hard. He consistently ranks in the upper echelon of hard hit balls and obviously produces massive power when he connects.
It seems odd to say that a player should be less selective, and even more so when that player is on the Baltimore Orioles. In Davis' case, however, taking fewer pitches and being more aggressive at the plate certainly seems to correlate with better offensive production. So, I'd suggest something I never thought I'd have to to suggest to an Oriole: swing the bat!
23 March 2017
Darren O'Day: Underappreciated Relief Weapon
There are at least a few things about the Orioles that should have you excited for the upcoming season. In no particular order: Manny Machado, healthy versions of Chris Davis and Adam Jones, Kevin Gausman, Dylan Bundy's first year as a full-time starter, a lineup that should hit plenty of dingers, Hyun Soo Kim's sophomore MLB season, and more. It's hard to top anything Machado does, but here's another big one: a bullpen that has a chance to be sensational.
Last year, the trio of Zach Britton, Brad Brach, and Mychal Givens was outstanding. They should again be a nasty group to deal with. Britton put the finishing touches on one of the very best relief seasons of all time. Brach started out on fire and made the all-star team, although he slumped a bit in the second half. And Givens showed how useful he can be, especially if his numbers improve against left-handed batters.
Overall, the bullpen finished first in the American League in ERA (3.40), t-second in strand rate (77.3%), sixth in groundball rate (46.3%), and first in win probability added, all the while finishing just 11th best in strikeouts per nine and 12th best in walks per nine.
One of the most interesting things about the bullpen's outstanding performance in 2016 is they accomplished what they did without a healthy and effective Darren O'Day (though Bundy gave them a nice boost for a while). After throwing at least 62 innings in the previous four seasons, O'Day only threw half that in 2016 as he battled two injuries.
O'Day went on the disabled list in early June because of a strained right hamstring, and he wasn't activated until late July. Then in mid-August, he again headed to the disabled list, this time due to a strained right rotator cuff. Apparently O'Day tried to pitch through the pain, which understandably did not help. When he returned about a month later, he pitched a few more times and started to resemble the O'Day fans had come to expect. He appeared in the O's now infamous wild card loss to the Blue Jays, recording five outs while facing just four batters (thanks to this enormous double play).
There's almost no chance Britton can duplicate his truly amazing season, and maybe Brach will take a step backward as well. But if O'Day is anything close to his 2012-2015 self, the Orioles will have something special on their hands. In his injury-plagued 2016, O'Day posted a 3.77 ERA and a 4.57 FIP. Yet from 2012-2015, O'Day's ERA dropped every year (2.28, 2.18, 1.70, 1.52), and his RA/9 nearly did as well (2.28, 2.32, 1.83, 1.79).
Because he doesn't always post great strikeout rates and isn't a groundball-inducing machine, O'Day doesn't typically put up wonderful fielding pitching independent numbers. That's a large reason why in his first four years in Baltimore, Baseball-Reference has him worth nearly 10 wins above replacement, and FanGraphs pegs him closer to five. If you want to see just how amazing O'Day was in that time span, just look at the following table from Baseball-Reference's indispensable Play Index:
| Rk | Player | ERA+ ▼ |
IP | From | To | ERA | FIP | OPS | OPS+ |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Craig Kimbrel | 239 | 250.2 | 2012 | 2015 | 1.58 | 1.80 | .462 | 33 |
| 2 | Koji Uehara | 227 | 215.0 | 2012 | 2015 | 1.84 | 2.34 | .514 | 38 |
| 3 | Darren O'Day | 214 | 263.0 | 2012 | 2015 | 1.92 | 3.08 | .580 | 59 |
| 4 | Aroldis Chapman | 206 | 255.2 | 2012 | 2015 | 1.90 | 1.74 | .486 | 39 |
| 5 | Greg Holland | 184 | 241.0 | 2012 | 2015 | 2.24 | 2.09 | .569 | 57 |
| 6 | Tony Watson | 166 | 277.2 | 2012 | 2015 | 2.24 | 3.05 | .573 | 64 |
| 7 | Kelvin Herrera | 164 | 282.1 | 2012 | 2015 | 2.52 | 3.09 | .619 | 70 |
| 8 | J.P. Howell | 164 | 205.1 | 2012 | 2015 | 2.24 | 3.55 | .610 | 76 |
| 9 | Jonathan Papelbon | 163 | 261.1 | 2012 | 2015 | 2.38 | 3.03 | .599 | 69 |
| 10 | Joaquin Benoit | 161 | 257.2 | 2012 | 2015 | 2.45 | 3.36 | .586 | 63 |
| 11 | Brad Ziegler | 158 | 276.2 | 2012 | 2015 | 2.50 | 3.44 | .595 | 67 |
| 12 | Kenley Jansen | 157 | 259.1 | 2012 | 2015 | 2.33 | 2.10 | .536 | 55 |
| 13 | Huston Street | 155 | 217.1 | 2012 | 2015 | 2.32 | 3.51 | .585 | 69 |
| 14 | Cody Allen | 152 | 238.1 | 2012 | 2015 | 2.64 | 2.73 | .637 | 76 |
| 15 | Santiago Casilla | 150 | 229.2 | 2012 | 2015 | 2.39 | 3.67 | .618 | 80 |
Some of the very best relievers in baseball are on that list. The Yankees just gave Aroldis Chapman $86 million over five years. Kenley Jansen received a contract for $6 million less over that same time frame. O'Day isn't in their class in terms overpowering the opposition and just reaching back and throwing the ball by hitters. But he gets outs -- plenty of them -- when he's healthy. That matters.
Before last season, the Orioles rewarded O'Day with a four-year, $31 million contract. So they clearly value his work. But you still get the sense that he's undervalued -- that Beyond The Box Score article linked above didn't even mention O'Day -- and even a bullpen that already projects to be excellent can use another relief weapon.
You can't predict health, and at 34 years old, O'Day is the eldest member of the O's relief options. Still, during an Orioles' spring training filled with frequent updates on injuries to players like Chris Tillman, Britton, J.J. Hardy, Seth Smith, Michael Bourn, and others, O'Day has fortunately been spared. If O'Day is indeed able to get back to his dominant, freewheeling, elevated-fastball and frisbee-slider-tossing ways, opposing batters will be in even more trouble against the Orioles in late-game situations.
Photo via Keith Allison
22 March 2017
Get Well Soon, Chris Tillman
Chris Tillman served admirably as the Orioles' de facto ace in 2016, but the team will be without him for a little while this season. Shoulder discomfort has kept Tillman out of spring training thus far, and he expects to resume throwing next week. Buck Showalter has indicated that he does not expect Tillman to pitch in the majors in April, and if I've learned anything from pitching injuries, I am afraid to be that optimistic.
Sitting Tillman early in order to let him fully heal and remain effective throughout the season rather than flopping on and off the DL is probably the safest course of action. With that in mind, we should temper expectations for the beginning of the 2017 season. The Orioles hardly have a full starting rotation, much less depth beyond the five pitchers that will regularly work as starters. The pitcher (or pitchers) that will assume Tillman's slot in the rotation in his absence are likely to be worse than him, which makes it harder for the team to win at the same rate they would with a healthy Tillman on the mound.
To estimate the quality of team that will take the field with a replacement pitcher on the mound, and how it compares to the team that takes the field with Tillman pitching, I turned to Joe Peta's base runs team quality formula. This is the process by which we use the base runs formula to estimate how much a team should have scored and allowed given its performance offensively and on the mound, which I have used in the past to evaluate money lines on playoff games,
For this project, I used 2016 statistics to determine how many runs the Orioles would be expected to give up with Tillman pitching compared to how many runs a composite of possible spot starters (Mike Wright, Wade Miley, and Tyler Wilson were my possible replacements). Each of these pitchers had their performances prorated to a full season. Similarly, I prorated season-long performance from the expected nine starting batters to estimate the runs the Orioles would be expected to score.
Using each of these run expectancies in the Pythagorean win formula yields the following team quality matrix:
SP
|
Team
|
Base Runs FOR | Base Runs AGAINST | W%+ |
Tillman
|
BAL
|
797.6 | 679.9 | 57% |
Tillman
|
BAL @ Home
|
861.4 | 679.9 | 61% |
Composite Spot Starter
|
BAL
|
797.6 | 919.4 | 44% |
Composite Spot Starter
|
BAL @ Home
|
861.4 | 919.4 | 47% |
Chris Tillman is effective enough at preventing runs that a composite spot starter would lead a team that plays like a sub-.500 club, while Tillman would be pitching for what looks like a playoff team.
With 24 games in April, Tillman could be replaced by a spot starter in four or five games. In five games with Tillman on the mound, the Orioles should expect to comfortably win three games. Without him, the team would not be expected to win more than two. A small difference to be sure, but a one-win swing out of every five games adds up quickly in a division as competitive as the AL East.
Of course, the Orioles should not rush Tillman back before he's fully healthy and ready to pitch at a high level. Doing otherwise would risk further and more serious injury, and having Tillman pitch injured would probably not yield results much better than his replacements.
Get well soon, Chris Tillman. If this team expects to compete this season in what looks like a tight AL East, it'll need you back, quickly, at full strength.
21 March 2017
Smiling In The Bright Lights: What Will Adam Jones Do For An Encore?
Before I begin, I must eat a little crow. Earlier this month, I confidently proclaimed that nobody cares about the World Baseball Classic.
Oops.
In fairness, it was a tongue-in-cheek remark to begin with; obviously, SOMEBODY out there cares. And, during last weekend’s WBC-action, that field of somebody’s expanded to include one more, yours truly.
It turns out that meaningful baseball makes for great television – especially when you sprinkle a little national pride on top. And, for Baltimore Orioles fans, having outfielder Adam Jones prominently-involved in the outcome (a 6-3 Team USA victory over the Dominican Republic, the tournament’s defending champ) was an extra thrill - the juicy, red cherry on top.
In case you’ve been out of the country and haven’t seen the play, do yourself a favor and remedy that. Jones makes a leaping catch - ala Mickey Hart - on a Manny Machado, homer run bid to right-center (in Petco Park, no less). The forums lit up, brandishing him with a multitude of nicknames (personal favorite: “GI Jones”).
Such national acclaim has always seemed just out of reach for Baltimore’s star. On one hand, he is a five-time all-star. On the other, he’s finished in the top ten of AL-MVP-voting just once (6th in 2012).
As far as defense goes, he has four gold gloves to his name, but is often treated indifferently by advanced metrics (for more on Jonesie’s defense – and outfield defense in general - check out this article by Depot colleague, Matt Perez).
A.J. has 150 home runs over the last five seasons, but has never even led his own team, in that span. While he’s been the most consistent hitter during his Orioles tenure, it seems he has constantly been overshadowed by someone else’s career year – be it Luke Scott, Chris Davis, Nelson Cruz or Mark Trumbo (cut to a shot of Ty Wigginton shouting, “Hey, don’t forget about me!”).
Most recently, his star has been eclipsed by the incandescent light that is Machado. The kid’s time has arrived, and soon the organization will have tough financial choices to make, regarding their star third baseman’s contract. Jones may be a casualty of such economics, leaving fans to bid premature adieu to another favorite.
Jones has two seasons left on the six-year, $85.5 million dollar deal he signed, in 2012. And, from the club’s perspective, it has aged-well through the prism of inflation. Would you rather have two more years of Jones for $33 million, or seven more years of Jason Heyward for *gulp* $169 million?
That said, Jones turned 31 in August, and there are signs he may be slowing. Last year he was worth a WAR-total of just 1.4. 2016 was also his first sub-100 wRC+ campaign since 2008, his rookie year. His .171 ISO represented a five-year low.
Also, while he has always displayed a bit of a reverse platoon-split, his numbers against southpaws were worse than ever (.580 OPS). Was it just a down year, or a sign that Jones’ career is rolling towards the precipice of an Aaron Rowand-like cliff?
On the plus side, he did strike out a bit less and walked a bit more. He also reversed a three-year downward trend in hard-hit ball percentage. That, coupled with his .280 BABIP (.308 career) and 14.1% HR/FB (15.3% career), could indicate that he was perhaps suffering from a run of bad luck.
Hits will have to drop for Jones because, even with the free pass improvement, his OBP was still a pedestrian .310. That number needs to come up, especially if Showalter is forced to pencil Jones into the leadoff spot again.
Also, his home run totals must not show a major drop-off. Power numbers have been on the rise; 38 players hit 30 or more home runs in 2016. In 2013, there were only 14 such players. Jones just keeps chugging along, but the league’s trends have rendered his power totals from above-average to merely average.
He is under contract through 2018, so the Orioles do have some time to evaluate. It will be interesting to see how they proceed.
Oops.
In fairness, it was a tongue-in-cheek remark to begin with; obviously, SOMEBODY out there cares. And, during last weekend’s WBC-action, that field of somebody’s expanded to include one more, yours truly.
It turns out that meaningful baseball makes for great television – especially when you sprinkle a little national pride on top. And, for Baltimore Orioles fans, having outfielder Adam Jones prominently-involved in the outcome (a 6-3 Team USA victory over the Dominican Republic, the tournament’s defending champ) was an extra thrill - the juicy, red cherry on top.
In case you’ve been out of the country and haven’t seen the play, do yourself a favor and remedy that. Jones makes a leaping catch - ala Mickey Hart - on a Manny Machado, homer run bid to right-center (in Petco Park, no less). The forums lit up, brandishing him with a multitude of nicknames (personal favorite: “GI Jones”).
Such national acclaim has always seemed just out of reach for Baltimore’s star. On one hand, he is a five-time all-star. On the other, he’s finished in the top ten of AL-MVP-voting just once (6th in 2012).
As far as defense goes, he has four gold gloves to his name, but is often treated indifferently by advanced metrics (for more on Jonesie’s defense – and outfield defense in general - check out this article by Depot colleague, Matt Perez).
A.J. has 150 home runs over the last five seasons, but has never even led his own team, in that span. While he’s been the most consistent hitter during his Orioles tenure, it seems he has constantly been overshadowed by someone else’s career year – be it Luke Scott, Chris Davis, Nelson Cruz or Mark Trumbo (cut to a shot of Ty Wigginton shouting, “Hey, don’t forget about me!”).
Most recently, his star has been eclipsed by the incandescent light that is Machado. The kid’s time has arrived, and soon the organization will have tough financial choices to make, regarding their star third baseman’s contract. Jones may be a casualty of such economics, leaving fans to bid premature adieu to another favorite.
Jones has two seasons left on the six-year, $85.5 million dollar deal he signed, in 2012. And, from the club’s perspective, it has aged-well through the prism of inflation. Would you rather have two more years of Jones for $33 million, or seven more years of Jason Heyward for *gulp* $169 million?
That said, Jones turned 31 in August, and there are signs he may be slowing. Last year he was worth a WAR-total of just 1.4. 2016 was also his first sub-100 wRC+ campaign since 2008, his rookie year. His .171 ISO represented a five-year low.
Also, while he has always displayed a bit of a reverse platoon-split, his numbers against southpaws were worse than ever (.580 OPS). Was it just a down year, or a sign that Jones’ career is rolling towards the precipice of an Aaron Rowand-like cliff?
On the plus side, he did strike out a bit less and walked a bit more. He also reversed a three-year downward trend in hard-hit ball percentage. That, coupled with his .280 BABIP (.308 career) and 14.1% HR/FB (15.3% career), could indicate that he was perhaps suffering from a run of bad luck.
Hits will have to drop for Jones because, even with the free pass improvement, his OBP was still a pedestrian .310. That number needs to come up, especially if Showalter is forced to pencil Jones into the leadoff spot again.
Also, his home run totals must not show a major drop-off. Power numbers have been on the rise; 38 players hit 30 or more home runs in 2016. In 2013, there were only 14 such players. Jones just keeps chugging along, but the league’s trends have rendered his power totals from above-average to merely average.
He is under contract through 2018, so the Orioles do have some time to evaluate. It will be interesting to see how they proceed.
20 March 2017
Brady Anderson is Teddy Roosevelt
 |
| A Fit Theodore Roosevelt |
Fast forward to 2010, a few weeks before Showalter was hired, and Peter Angelos brings Brady Anderson out of the cold as an independent member of the organization. It was a familiar sight. Almost a decade earlier, Angelos did the same with Mike Flanagan. Angelos saw someone who clearly loved the Orioles, was capable, and had exciting ideas like using psychoanalysis for rafting players. Flanagan was paired with Jim Beattie in order to show him the ropes until Angelos felt Flanagan was ready enough to jettison Beattie. Unfortunately, good will money quickly evaporated for Flanagan and his ideas often produced more groan inducing stories than success (i.e., the psych testing was not properly translated into Spanish, which caused the club to ignore Jaime Garcia's results that were impacted by his English proficiency).
Anderson came in with transformative ideas about adherence to nutrition, training, and positive player thinking. His offseason home out West became a gathering place for young or struggling players to get back into experiencing success. Players like Zach Britton came into his own after his experience with Brady (though he tends to credit Dave Wallace and Dom Chiti on his transformation into a dominant closer), but the record is not perfect as Hyun Soo Kim had to unlearn what his experience taught him.
Regardless, Brady Anderson's experience seems awfully similar to Teddy Roosevelt's experience. Roosevelt was a progressive. He was a champion of conservationism (a thoroughly accomplished taxidermist), an advocate of Charles Darwin, a religious progressive (to the extent that he would be unelectable today), a firm believer in American opportunism, and a dedicated implementer of new ideas and technology. Roosevelt was also in a privileged position to easily rise through political opportunities before lucking into a vice presidency, which led to him becoming president.
Roosevelt was also a bit of an eye rolling buffoon. He ignored established protocol, which is certainly evidence by Anderson and how he interacts with players. He would turn anything into a competition, which we all remember from tales of people running into Brady late at night and finding themselves in foot races. He could also find the pearls in the muck that other more traditional minds refused to find because of their distaste for dirt. Roosevelt's buffoonery is a major part of the reason why he accomplished so much. Anderson is in the same camp.
These point are well brought up in Ken Rosenthal's article on Anderson. You can tell there are strong adherents to Brady and others who dislike him enough to put their names in print to negative perspectives. Dave Wallace gives several quotes noting that Anderson would run rough shod over coaches at the MLB level and affiliates with instruction without connecting with the coaches or explaining what he was having the player do. This sounds a little like the issue with Rick Peterson and one wonders whether Brady's guidance was influenced by Peterson's snake oil analytic mysticism. That said, Brady is much better received by Buck than Peterson ever was.
Dom Chiti only gave Rosenthal a single sentence, but it was effectively that Brady's presence is why he choose to go elsewhere. This does not exactly jive with his previous statements likening him to a scorned lover waiting on a phonecall that never came in October and November. It also does not square with the once again frank Dan Duquette who said he grew tired of Chiti and Wallace shenanigans with Brady. The third negative voice came from Matt Wieters who simply stated that Brady was an outsider and had no place in the clubhouse where Brady maintains a locker.
Discord is not exactly a cause of concern and a disruptor like Brady will cause discord. Some might worry about how this all plays into Brady's future. The current structure of the Orioles is a two headed monster. Duquette handles the 40 man roster, Buck handles the 25 man active roster, and who is on the 25 man roster is sometimes a delicate negotiation between the two. Both are known to seek out Angelos to get their ideas through over the other's objections. Brady, a tight friend of the Angelos family, is the floating head in this operation. He keeps his nose clean by dedicating himself for player betterment on the field, but those actions sometimes counter what Duquette or Buck want. He extreme avoidance about discussing managing or being a general manager appears to keep him away from their disdain.
That said, this creates an uncomfortable situation where a person between worlds exists. In the contentious world of baseball where ownership and management routinely exploits and undermines players, concern is understandable. However, the ability to communicate between all levels of the organization is also quite advantageous.
Lets compare two organizations and how they communicate applied analytics. For the Pirates, it is a family affair. No lines are drawn in information sharing. Analysts in the front office are fully incorporated into the organization. You will find them in the clubhouse, in Spring Training, really almost anywhere. Analyst and player can have a discussion that can be mutually beneficial because players can experience things analysts cannot see with their data and vice versa.
How does information routinely travel in the Orioles' system? An analyst may come up with an idea about how to position, let's say, Adam Jones. Analyst presents this to the head analyst. Head analyst presents this to an assistant GM, assistant GM presents this to GM, this assistant GM or someone else presents this to the division lead (i.e., Buck), lead discusses this with staff, and then staff works with player. Sometimes this line varies, but I am not aware of a single time where a base level analyst communicated directly with a player. This siloed atmosphere makes it incredibly difficult share information that can make players and analysts better at what they do. Chiti and Wallace feeling undermined may be an example where they feel hierarchy was undermined.
Which begs the question of how Brady, a disrupting force who appears to want to undermine existing power structures, will be used in the future. Dan Duquette seems to be a proponent of information sharing, but maintains a silo structure under his domain. Buck Showalter is a great advocate for silos. Brady is a bit of an odd duck. If he gains control will he bring with him an open atmosphere of interaction or does he see himself as a great man, a great communicator who alone can bridge gaps?
That is really the positive read. The negative read? Brady ignores all convention including convention that is in place for good reason. He breaks down controls that protect players from the meddling of management. Wieters comments may be less about Brady himself and more about how Brady's presence undermines the protection the players have won from individuals who may have had more nefarious goals than Brady has (or yet has shown). There is also concern that the expedience of communication for Brady creates instability for coaches and a situation where sides form. Team chemistry may still be scoffed at by some, but a toxic work environment is a toxic work environment.
Teddy Roosevelt had to deal with similar issues. His progressivism had him modernize the Navy, get the Panama Canal built, and firmly established an American sense of environmental conservatism. His head first mentality led him to great heights and great success. However, it is also what led to his downfall and a broken back end of his public career. Brady is still closer to the beginning of Roosevelt's tale. Brady is running back and forth, shooting at enemy combatants in Cuba trying to surrender these past five years as the Orioles have the most total wins in the American League. I guess the question is, will Brady make the world believe in Baltimore exceptionalism?
16 March 2017
The Orioles Outfield And Catch Probability
The newest tool created by the people that brought us Statcast is Catch Probability. Catch Probability attempts to determine the difficulty to catch each ball hit into the outfield based on how far the fielder had to run to catch the ball and how long he had to get there. Based on the ability to quantify each play, they’ve put many catches into five categories:
5 Star Plays: Converted between 0 to 25 percent of the time and require a speed of 30 feet per fastest second.
4 Star Plays: Converted between 26 to 50 percent of the time and require a speed of 29 feet per fastest second.
3 Star Plays: Converted 51 to 75 percent of the time and require a speed of 28 feet per fastest second. 2 Star Plays: Converted 76 to 90 percent of the time while requiring a speed of 27 feet per fastest second.
1 Star Plays: Converted 91 to 95 percent of the time and require a speed of 26 feet per fastest second.
MLB has also created a 2015 and 2016 Statcast Catch Probability Leaderboard on their data portal at Baseball Savant. For each outfielder in these years, Baseball Savant tells us, the number of opportunities in each of these five categories that an outfielder had and how many times he converted an opportunity. Using this data for each outfielder with at least 50 opportunities, it’s possible to determine the league average in a category and how many catches above or below average an outfielder is presuming he faced an average difficulty of catch in each category.
There are at least four reasons why such a metric will be imperfect. Statcast doesn’t provide position information, so I’m comparing corner outfielders to center fielders even though center fielders likely have better range. This likely overvalues center fielders and undervalues corner outfielders. Such a metric presumes that each catch has equal value, but some catches are more likely to prevent extra bases than others. This metric tells us nothing about a fielders’ performance when fielding a pitch likely to be caught 96 to 100% of the time. Finally, if a fielder faces easier or harder opportunities in a bracket, then their value will not be valued properly. Note that this mostly doesn’t even take into account the positional problem that Statcast says exists. Still, even if this metric is flawed, it’s likely to have some value.
Jeff Sullivan from Fangraphs found average catch probabilities and frequencies for each of the five categories that Statcast created. The highest frequency of opportunities are 1-star plays despite the fact that this category only covers balls that are caught 91-95% of the time. One would expect balls caught 50-75% of the time to have a higher frequency of opportunities. The next highest frequency are 5-star plays which are converted only 8% of the time. These results are similar to the data collected by Inside Edge. If the data continues to be similar, then the overwhelming amount of chances will be in the 96-100% bucket and will be largely converted by all outfielders with minimal defensive competence. Given that in a full season, an outfielder has about 300 putouts, and the highest number of opportunities on this list is around 170, it’s safe to say that the data will continue to be similar.
This suggests that outfield defense follows something akin to the Pareto principle. Elite outfielders that can cover a lot of ground are significantly more valuable than average outfielders because they can convert tough plays. Terrible outfielders that can’t cover any ground are significantly less valuable than average outfielders. But most outfielders are more or less interchangeable --- especially in the corners. This is because there are relatively few plays that a good outfielder can make that just a bad outfielder can’t.
In 2016, out of 162 total outfielders with 50 or more opportunities, 115 (70%) were between -5 to 5 catches above average. Per 77.6 opportunities (average opportunities per outfielder in the sample) ranked in one of the categories quantified by Statcast and shared with the public, 93 were between -5 to 5 catches above average. In 2015, 120 out of 162 outfielders were between -5 to 5 catches above average (74%). On a rate basis, 102 were between -5 to 5 catches above average. Again, elite outfielders are extremely valuable and terrible outfielders are a liability, but there’s little difference between good defensive outfielders and bad ones.
There are a number of interesting players. As Jeff Sullivan stated, Mark Trumbo was terrible in 2016. He only converted 11 of 19 1-star plays good for a 58% rate. On a rate basis, Trumbo was easily the worst outfielder in 2016. It is likely that there was some bad luck involved, as Trumbo had nearly the same conversion rate on 1-star plays and 2-star plays, but Trumbo’s inability to make difficult plays further shows his lack of range. Trumbo wasn’t as bad in 2015, but was still one of the worst outfielders whether considering rate stats or his actual performance. Statcast suggests that Trumbo is best at either first base or DH which is problematic given that the Orioles already have Chris Davis.
Nick Markakis also had bad results using this method. He ranked 154th in rate stats in 2015 and 112th in 2016 but 171st in 2015 and 148th using actual counting stats. This method likely underestimates Nick because it doesn’t take into account his sure hands when fielding balls hit near him nor his strong arm. However, it is another data point that supports the sabermetric consensus that his range is terrible.
Andrew McCutchen ranked 160th in 2016 and 164th in 2015 looking at his counting stats. Part of that is due to the fact that he had a lot of chances, but he was still worse than 5 catches above average in both 2015 and 2016. This could suggest that he’s a worse fielder than normal metrics suggested and therefore his value may be limited. This could be why he is being moved from center field to right field next year.
Adam Jones ranked 28th in 2016 with 4.5 catches above average (actual result) and 10th in 2015 with 11.2 catches above average. This suggests that Adam Jones does indeed have above average range. However, this leader board doesn’t tell us how many of the catches he misses go over his head and therefore result in extra bases for the hitter. Still, it’s likely that Adam Jones has been underestimated by the statistical models.
Joey Rickard ranked 26th in 2016 with 5.3 catches above average. While he struggled to make two-star catches, he converted all of his one-star opportunities and was surprisingly successful with three-star and up catches. With a slight improvement in his route running, Rickard may just be able to become an elite outfielder. Pairing him with Adam Jones next year could pay significant dividends defensively although whether or not he can hit is another question.
Mr. Kim had especially interesting results. His rank was 145th in 2016. However, he was as good as the average outfielder on one-star and two-star plays. He was only slightly below average on three-star plays, which given that he had only eight opportunities may just be due to small sample size. However, he was 0-23 for four-star and five-star plays. This suggests that his fielding skills are acceptable, but his range/speed isn't good enough to play in the majors without significant help from Adam Jones. On the other hand, it may mean that an outfield of Kim/Jones/Rickard may be successful defensively because the other outfielders could cover for Kim's lack of range.
This data seems to suggest that most outfielders perform reasonably similar to each other but a few outfielders can be outliers. Outfielders with elite speed can be considerably more valuable than the average fielder. Outfielders with poor speed can be considerably worse, suggesting that the lower bound for acceptable outfield defense is higher than I might have suspected. This also suggest that trying to use players like Alvarez, Mancini, Walker and Trumbo in the outfield is a bad idea that will likely fail.
Statcast defines a one-star play as one that requires a player to reach a peak speed of 26 feet per second. Players that can’t successfully convert these plays the vast majority of the time will likely be unsuccessful outfielders. If so, it’s safe to say that teams can determine whether a player is fast enough to be an outfielder if he can reach a peak speed of 27 or 28 feet per second when trying to field a ball. If a player isn’t that fast, then using him in this capacity is a waste of time. Obviously, players like Nick Markakis with especially good hands and a strong arm, or players that are able to run good routes can be acceptable with a slightly lower speed. Players that run bad routes need to be able to go somewhat faster than that. It seems fair to argue that slow players could indeed be legendarily bad if they’re put in the outfield.
My understanding is that Statcast will continue to roll out and improve this metric over the 2017 season. If they include this data in their play-by-play datasets, then this will significantly advance our understanding of outfield defense and allow us to learn what it takes to be successful in the outfield.
5 Star Plays: Converted between 0 to 25 percent of the time and require a speed of 30 feet per fastest second.
4 Star Plays: Converted between 26 to 50 percent of the time and require a speed of 29 feet per fastest second.
3 Star Plays: Converted 51 to 75 percent of the time and require a speed of 28 feet per fastest second. 2 Star Plays: Converted 76 to 90 percent of the time while requiring a speed of 27 feet per fastest second.
1 Star Plays: Converted 91 to 95 percent of the time and require a speed of 26 feet per fastest second.
MLB has also created a 2015 and 2016 Statcast Catch Probability Leaderboard on their data portal at Baseball Savant. For each outfielder in these years, Baseball Savant tells us, the number of opportunities in each of these five categories that an outfielder had and how many times he converted an opportunity. Using this data for each outfielder with at least 50 opportunities, it’s possible to determine the league average in a category and how many catches above or below average an outfielder is presuming he faced an average difficulty of catch in each category.
There are at least four reasons why such a metric will be imperfect. Statcast doesn’t provide position information, so I’m comparing corner outfielders to center fielders even though center fielders likely have better range. This likely overvalues center fielders and undervalues corner outfielders. Such a metric presumes that each catch has equal value, but some catches are more likely to prevent extra bases than others. This metric tells us nothing about a fielders’ performance when fielding a pitch likely to be caught 96 to 100% of the time. Finally, if a fielder faces easier or harder opportunities in a bracket, then their value will not be valued properly. Note that this mostly doesn’t even take into account the positional problem that Statcast says exists. Still, even if this metric is flawed, it’s likely to have some value.
Jeff Sullivan from Fangraphs found average catch probabilities and frequencies for each of the five categories that Statcast created. The highest frequency of opportunities are 1-star plays despite the fact that this category only covers balls that are caught 91-95% of the time. One would expect balls caught 50-75% of the time to have a higher frequency of opportunities. The next highest frequency are 5-star plays which are converted only 8% of the time. These results are similar to the data collected by Inside Edge. If the data continues to be similar, then the overwhelming amount of chances will be in the 96-100% bucket and will be largely converted by all outfielders with minimal defensive competence. Given that in a full season, an outfielder has about 300 putouts, and the highest number of opportunities on this list is around 170, it’s safe to say that the data will continue to be similar.
This suggests that outfield defense follows something akin to the Pareto principle. Elite outfielders that can cover a lot of ground are significantly more valuable than average outfielders because they can convert tough plays. Terrible outfielders that can’t cover any ground are significantly less valuable than average outfielders. But most outfielders are more or less interchangeable --- especially in the corners. This is because there are relatively few plays that a good outfielder can make that just a bad outfielder can’t.
In 2016, out of 162 total outfielders with 50 or more opportunities, 115 (70%) were between -5 to 5 catches above average. Per 77.6 opportunities (average opportunities per outfielder in the sample) ranked in one of the categories quantified by Statcast and shared with the public, 93 were between -5 to 5 catches above average. In 2015, 120 out of 162 outfielders were between -5 to 5 catches above average (74%). On a rate basis, 102 were between -5 to 5 catches above average. Again, elite outfielders are extremely valuable and terrible outfielders are a liability, but there’s little difference between good defensive outfielders and bad ones.
There are a number of interesting players. As Jeff Sullivan stated, Mark Trumbo was terrible in 2016. He only converted 11 of 19 1-star plays good for a 58% rate. On a rate basis, Trumbo was easily the worst outfielder in 2016. It is likely that there was some bad luck involved, as Trumbo had nearly the same conversion rate on 1-star plays and 2-star plays, but Trumbo’s inability to make difficult plays further shows his lack of range. Trumbo wasn’t as bad in 2015, but was still one of the worst outfielders whether considering rate stats or his actual performance. Statcast suggests that Trumbo is best at either first base or DH which is problematic given that the Orioles already have Chris Davis.
Nick Markakis also had bad results using this method. He ranked 154th in rate stats in 2015 and 112th in 2016 but 171st in 2015 and 148th using actual counting stats. This method likely underestimates Nick because it doesn’t take into account his sure hands when fielding balls hit near him nor his strong arm. However, it is another data point that supports the sabermetric consensus that his range is terrible.
Andrew McCutchen ranked 160th in 2016 and 164th in 2015 looking at his counting stats. Part of that is due to the fact that he had a lot of chances, but he was still worse than 5 catches above average in both 2015 and 2016. This could suggest that he’s a worse fielder than normal metrics suggested and therefore his value may be limited. This could be why he is being moved from center field to right field next year.
Adam Jones ranked 28th in 2016 with 4.5 catches above average (actual result) and 10th in 2015 with 11.2 catches above average. This suggests that Adam Jones does indeed have above average range. However, this leader board doesn’t tell us how many of the catches he misses go over his head and therefore result in extra bases for the hitter. Still, it’s likely that Adam Jones has been underestimated by the statistical models.
Joey Rickard ranked 26th in 2016 with 5.3 catches above average. While he struggled to make two-star catches, he converted all of his one-star opportunities and was surprisingly successful with three-star and up catches. With a slight improvement in his route running, Rickard may just be able to become an elite outfielder. Pairing him with Adam Jones next year could pay significant dividends defensively although whether or not he can hit is another question.
Mr. Kim had especially interesting results. His rank was 145th in 2016. However, he was as good as the average outfielder on one-star and two-star plays. He was only slightly below average on three-star plays, which given that he had only eight opportunities may just be due to small sample size. However, he was 0-23 for four-star and five-star plays. This suggests that his fielding skills are acceptable, but his range/speed isn't good enough to play in the majors without significant help from Adam Jones. On the other hand, it may mean that an outfield of Kim/Jones/Rickard may be successful defensively because the other outfielders could cover for Kim's lack of range.
This data seems to suggest that most outfielders perform reasonably similar to each other but a few outfielders can be outliers. Outfielders with elite speed can be considerably more valuable than the average fielder. Outfielders with poor speed can be considerably worse, suggesting that the lower bound for acceptable outfield defense is higher than I might have suspected. This also suggest that trying to use players like Alvarez, Mancini, Walker and Trumbo in the outfield is a bad idea that will likely fail.
Statcast defines a one-star play as one that requires a player to reach a peak speed of 26 feet per second. Players that can’t successfully convert these plays the vast majority of the time will likely be unsuccessful outfielders. If so, it’s safe to say that teams can determine whether a player is fast enough to be an outfielder if he can reach a peak speed of 27 or 28 feet per second when trying to field a ball. If a player isn’t that fast, then using him in this capacity is a waste of time. Obviously, players like Nick Markakis with especially good hands and a strong arm, or players that are able to run good routes can be acceptable with a slightly lower speed. Players that run bad routes need to be able to go somewhat faster than that. It seems fair to argue that slow players could indeed be legendarily bad if they’re put in the outfield.
My understanding is that Statcast will continue to roll out and improve this metric over the 2017 season. If they include this data in their play-by-play datasets, then this will significantly advance our understanding of outfield defense and allow us to learn what it takes to be successful in the outfield.
14 March 2017
Step 1: Find a Box. Step 2: Is Chris Davis in that Box?
Over the past few weeks, Patrick Dougherty and I have been throwing lineup optimization regression models at you. I introduced the decade old lineup model identifying run value on a positional basis and introduced a new model that identified runs batted in on a co-dependent positional basis. Patrick then did a thoroughly best fitting of the new model and found that Chris Davis leading off was the best iteration of the starting nine we evaluated. However, it is easy to note that Chris Davis is an atypical leadoff hitter, so how atypical is he?
A best fit line on a scatter plot is an easy visual to understand. You can observe the range of data on the x-axis and on the y-axis. You have a decent handle on whether a new data point is found within that range of data points or if it is an exceptional outlier. Intuitively, the degree to which a data point is an outlier, the more and more your concern rises about whether this model can realistically handle your new data point.
David Freedman, an economist, is known is some circles for his cheeky Conservation of Rabbits Principle. He states that in order "to pull a rabbit from a hat, a rabbit must first be placed into the hat." In other words, a model outcome that is different from the model input should be highly questioned, so let us explore Chris Davis as a leadoff hitter.
We shall ignore the seven, eight, and nine hitters. A quick glance over them shows us that they are reasonable bottom third lineup hitters. Chris Davis at the top of the order feels a bit more peculiar. The model considers walk rate, strikeout rate, doubles rate, and home run rate. Those metrics were the most relevant based on significance testing.
Chris Davis is projected by ZIPS to walk 11.6% of the time he is up at the plate. Of the 300 data points over the past ten years for a team's leadoff hitter, 15 are within 10% of Davis' projection. In total, that rate would be the 17th best and on par with excellent walk rates put forth in 2007 and 2008 by the Orioles' own Brian Roberts. Anyway, a top ten percent walk rate certainly stretches the model, but stays within the boundaries set by the data. With doubles, Davis is well within the model variables with his 3.7% projected rate. That, however, is certainly not very impressive among the data points in the data set. He would be 248th out of 300 positions.
Davis also has a projected 33.6% strikeout rate. That is off the model radar. As noted, the model has 300 team entries and the highest rate is the 2016 Brewers with 26.5%. Davis' rate would be a 30% increase over that. Davis is also projected to have a very impressive 6.6% home run rate. That is also about a 30% increase of the next closest number, which is the 2016 Twins. With respect to these metrics, we are in an area that the model is not well supplied to use that information.
What about the aforementioned Mark Trumbo? For home runs, he is 10% over the extent of the data in the model. His doubles are right smack dab in the middle. His strikeout rate would be third worst in this dataset. His walk rate would also be in the middle. As a whole, we should feel more comfortable with Trumbo's projection as a leadoff man than Chris Davis', but both are so unconventional that a regression model like this might be extrapolating effects beyond where we should feel comfortable.
The lesson here really should extend beyond the exercise Patrick and I have been performing. It is important to understand causality and the limitations placed upon us to be able to determine what exactly causes anything else. Certainly, I would think that we all agree that induction is useful to determine a better grasp on causation, but that we must be quite transparent and acknowledge the uncertainty involved in our methods of induction.
When we put forward such unconventional answers to well trodden fields, we must note that we have certainly extended ourselves beyond practiced reality. True, this extrapolation may one day be shown to be true, but this is more of a leap of faith than any sober trust put into our methods. And, that is really the crux of it. When our universe is limited to what we have experienced, our intellectual foundation beyond that scope is weak. No, I do not think Trumbo or Davis are ideal lead off men, but I would suggest that it is a perfectly good hypothesis to offer that they might well be ideal lead off men.
I doubt when tens of millions of dollars are at play though that we will be able to fill in our data set.
A best fit line on a scatter plot is an easy visual to understand. You can observe the range of data on the x-axis and on the y-axis. You have a decent handle on whether a new data point is found within that range of data points or if it is an exceptional outlier. Intuitively, the degree to which a data point is an outlier, the more and more your concern rises about whether this model can realistically handle your new data point.
David Freedman, an economist, is known is some circles for his cheeky Conservation of Rabbits Principle. He states that in order "to pull a rabbit from a hat, a rabbit must first be placed into the hat." In other words, a model outcome that is different from the model input should be highly questioned, so let us explore Chris Davis as a leadoff hitter.
We shall ignore the seven, eight, and nine hitters. A quick glance over them shows us that they are reasonable bottom third lineup hitters. Chris Davis at the top of the order feels a bit more peculiar. The model considers walk rate, strikeout rate, doubles rate, and home run rate. Those metrics were the most relevant based on significance testing.
Chris Davis is projected by ZIPS to walk 11.6% of the time he is up at the plate. Of the 300 data points over the past ten years for a team's leadoff hitter, 15 are within 10% of Davis' projection. In total, that rate would be the 17th best and on par with excellent walk rates put forth in 2007 and 2008 by the Orioles' own Brian Roberts. Anyway, a top ten percent walk rate certainly stretches the model, but stays within the boundaries set by the data. With doubles, Davis is well within the model variables with his 3.7% projected rate. That, however, is certainly not very impressive among the data points in the data set. He would be 248th out of 300 positions.
Davis also has a projected 33.6% strikeout rate. That is off the model radar. As noted, the model has 300 team entries and the highest rate is the 2016 Brewers with 26.5%. Davis' rate would be a 30% increase over that. Davis is also projected to have a very impressive 6.6% home run rate. That is also about a 30% increase of the next closest number, which is the 2016 Twins. With respect to these metrics, we are in an area that the model is not well supplied to use that information.
What about the aforementioned Mark Trumbo? For home runs, he is 10% over the extent of the data in the model. His doubles are right smack dab in the middle. His strikeout rate would be third worst in this dataset. His walk rate would also be in the middle. As a whole, we should feel more comfortable with Trumbo's projection as a leadoff man than Chris Davis', but both are so unconventional that a regression model like this might be extrapolating effects beyond where we should feel comfortable.
The lesson here really should extend beyond the exercise Patrick and I have been performing. It is important to understand causality and the limitations placed upon us to be able to determine what exactly causes anything else. Certainly, I would think that we all agree that induction is useful to determine a better grasp on causation, but that we must be quite transparent and acknowledge the uncertainty involved in our methods of induction.
When we put forward such unconventional answers to well trodden fields, we must note that we have certainly extended ourselves beyond practiced reality. True, this extrapolation may one day be shown to be true, but this is more of a leap of faith than any sober trust put into our methods. And, that is really the crux of it. When our universe is limited to what we have experienced, our intellectual foundation beyond that scope is weak. No, I do not think Trumbo or Davis are ideal lead off men, but I would suggest that it is a perfectly good hypothesis to offer that they might well be ideal lead off men.
I doubt when tens of millions of dollars are at play though that we will be able to fill in our data set.
13 March 2017
Another Idea on Speeding Up Games
My friends and acquaintances know at least in a general way that I work for the Norfolk Tides, and so we talk about baseball a lot. During this past offseason, the big topic were the proposed rule changes intended to speed up play. Most of the media coverage focused on two topics. One is the automatic intentional walk rule, in which managers can signal for an intentional walk. The batter will be awarded first base without the pitcher having to throw four pitches out of the strike zone. The other is the proposal to start extra innings with runners on base, a rule perfectly suitable for low-level developmental leagues but not - and not likely to be implemented any time soon - for major-league games.
In my jobs as MLBAM datacaster and BIS scorer, I see forty or more AAA games a season. Unlike most fans, I don't have the options of changing the channel or getting up and leaving. And, I must admit, that I wish many of the games I see would end sooner. But the problem isn't that the games take too much clock time - at least in most cases. A tense, seesaw game or a well-played game with spectacular offensive and defensive plays - those games are never too long.
For me, there are two real problems with games taking too long. There's nothing can be done about the first, which is that inevitably some games are going to be boring. The last three innings of a 17-2 blowout are not interesting, and no one- probably not even Joe Maddon - wants more of that. The second problem is when there's too much dead time, with batters stepping out of the box to re-tighten their wristbands after every pitch and mound conferences after every batter.
It's striking how few limits there are on conferences. The only limit I am aware of is that a pitcher must be relieved if a manager or coach has a second conference in the same inning with a given pitcher. There are no limits on the number of conferences among players. And these conferences are the equivalent of "time-outs" in other sports in which the coach discusses tactics or designs a play. Every other sport puts a limit on time-outs.
While it is true that in baseball these conferences do not stop a running time clock in the way time-outs do in the other sports, they certainly do interrupt the game flow. That's not always a bad thing - when a team is in the middle of a rally, it's a valid strategy to go to the mound and settle the pitcher or get the pitcher focused. That frequently happens in basketball, for instance. But to have strategy conferences before every batter is overkill. No one I've talked to has ever said "I want to see more conferences among players or among players and a coach."
Before almost every college basketball game was televised, each team was allotted five time-outs per game. Televised games provided the "TV time-outs" every four minutes, but the teams were still allotted their five time-outs. Coaches hoarded their time-outs, saving them for the last minute or two of a game. And, the last couple of minutes of close games became unwatchable, as coaches called a time-out after every play and sometimes multiple times during a play. Eventually the NCAA reduced the number of time-outs and required one to be used in the first half.
I would like to see baseball start reducing the number of allowable conferences. Ideally, I'd like the reduction to apply to conferences among players only, but that's hard to enforce and, frankly, hard to devise an appropriate rule. I do have a proposal for limiting the number of coach visits to the mound.
Essentially, a team would be limited to three "visits to the mound" without being required to remove the pitcher. And, one of those mound visits would have to be in the first six innings. They wouldn't have to be the first three visits - a team could remove a pitcher after its first visit and still have the three - but once you've used your three visits, you have to relieve a pitcher if you visit the mound. (I'm flexible on adding more visits for extra innings, but I haven't thought about how to do so.)
Fewer stalls to give the relief pitcher more time to warm up. Fewer conferences to tell players what to do on a sacrifice bunt or whether to issue an intentional walk. Less dead time, and more action. And more strategy and potential controversy, too - the manager will have to be more judicious in sending a coach to talk to the pitcher. And it forces the players to play, to know what to do, rather than to be spoon-fed by coaches. I think it's time for baseball to join the other sports and limit how many times coaches and managers can talk to their players.
In my jobs as MLBAM datacaster and BIS scorer, I see forty or more AAA games a season. Unlike most fans, I don't have the options of changing the channel or getting up and leaving. And, I must admit, that I wish many of the games I see would end sooner. But the problem isn't that the games take too much clock time - at least in most cases. A tense, seesaw game or a well-played game with spectacular offensive and defensive plays - those games are never too long.
For me, there are two real problems with games taking too long. There's nothing can be done about the first, which is that inevitably some games are going to be boring. The last three innings of a 17-2 blowout are not interesting, and no one- probably not even Joe Maddon - wants more of that. The second problem is when there's too much dead time, with batters stepping out of the box to re-tighten their wristbands after every pitch and mound conferences after every batter.
It's striking how few limits there are on conferences. The only limit I am aware of is that a pitcher must be relieved if a manager or coach has a second conference in the same inning with a given pitcher. There are no limits on the number of conferences among players. And these conferences are the equivalent of "time-outs" in other sports in which the coach discusses tactics or designs a play. Every other sport puts a limit on time-outs.
While it is true that in baseball these conferences do not stop a running time clock in the way time-outs do in the other sports, they certainly do interrupt the game flow. That's not always a bad thing - when a team is in the middle of a rally, it's a valid strategy to go to the mound and settle the pitcher or get the pitcher focused. That frequently happens in basketball, for instance. But to have strategy conferences before every batter is overkill. No one I've talked to has ever said "I want to see more conferences among players or among players and a coach."
Before almost every college basketball game was televised, each team was allotted five time-outs per game. Televised games provided the "TV time-outs" every four minutes, but the teams were still allotted their five time-outs. Coaches hoarded their time-outs, saving them for the last minute or two of a game. And, the last couple of minutes of close games became unwatchable, as coaches called a time-out after every play and sometimes multiple times during a play. Eventually the NCAA reduced the number of time-outs and required one to be used in the first half.
I would like to see baseball start reducing the number of allowable conferences. Ideally, I'd like the reduction to apply to conferences among players only, but that's hard to enforce and, frankly, hard to devise an appropriate rule. I do have a proposal for limiting the number of coach visits to the mound.
Essentially, a team would be limited to three "visits to the mound" without being required to remove the pitcher. And, one of those mound visits would have to be in the first six innings. They wouldn't have to be the first three visits - a team could remove a pitcher after its first visit and still have the three - but once you've used your three visits, you have to relieve a pitcher if you visit the mound. (I'm flexible on adding more visits for extra innings, but I haven't thought about how to do so.)
Fewer stalls to give the relief pitcher more time to warm up. Fewer conferences to tell players what to do on a sacrifice bunt or whether to issue an intentional walk. Less dead time, and more action. And more strategy and potential controversy, too - the manager will have to be more judicious in sending a coach to talk to the pitcher. And it forces the players to play, to know what to do, rather than to be spoon-fed by coaches. I think it's time for baseball to join the other sports and limit how many times coaches and managers can talk to their players.
Subscribe to:
Posts (Atom)