As kind-of-requested in the comments section of a recent Mike Trout-centric article, here are some fun Mike Trout facts!
***all statistics, ages, etc., are as of May 13, 2015***
1. From May 21-24, 2013, Mike Trout had four consecutive multi-hit games. Over that stretch, he went 10-for-17 (.588) with a walk, double, two triples, and two home runs. In the first game of that stretch, Trout hit for the cycle. In this four-game multi-hit streak, Trout accumulated 19 total bases in 18 plate appearances. This was one of Trout’s two career streaks of four consecutive multi-hit games; the other was just a month earlier.
2. Mike Trout has 107 home runs in 526 games, and is still just 23 years old. But Mike Trout did not hit two home runs in the same game until homers #77 and #78.
3. Mike Trout has 107 home runs. If he plays in as many games as did all-time home runs leader Barry Bonds (2,986), and homers at his current rate the whole time, Trout will finish with 607 home runs, good for 9th all time.
4. Mike Trout has 109 steals. If he plays in as many games as did all-time steals leader Rickey Henderson (3,081), and steals at his current rate the whole time, Trout will finish with 638 steals, good for 15th all time.
5. Bearing in mind facts #3-4, this is a complete list of all the players in the top HUNDRED all-time for both home runs and steals: Barry Bonds.
6. Mike Trout has 607 hits in 526 games. If he plays in as many games as did all-time hits leader Pete Rose (3,562), and gets hits at his current rate the whole time, Trout will finish with 4,110 hits, good for 3rd place all time. Rose and Ty Cobb are the only players to ever get more than 4,000 hits.
7. Mike Trout is 23 years, 9 months, and 6 days old, and has 607 hits. At that exact age, Pete Rose had 309 hits.
8. After reaching an 0-2 count, Mike Trout reaches base successfully 27% of the time (career). This year, it’s 35%. Mike Trout’s on-base percentage in 0-2 counts this year is better than the on-base percentages, in all counts, of 29 entire major league teams.
9. Mike Trout has 8 bunt attempts in his career and reached base safely in 4 of 8.
10. In his last three months of regular-season play, the longest Mike Trout has gone without a hit is 2 games.
11. The longest Mike Trout has ever gone without a hit is 4 games. This has happened three times. Two of those three times were in Trout’s first full month in the major leagues, in 2011. He has only done it once in the last four seasons.
12. When he pulls the ball, Mike Trout has a career batting average of .488. When he hits the ball to center, Mike Trout has a career batting average of .443.
13. Give or take a few tenths of a percent, the percentage of balls hit by Mike Trout which are classified as “hard-hit” has increased every year of his career, to 2015’s 41.6%. (That ranks 9th in the MLB this year.)
14. Inside Edge classifies all defensive plays based on whether they are Impossible (0% chance of being made), Remote (1-10% chance of being made), Unlikely (10-40%), Even Odds (40-60%), Likely (60-90%), or Routine (90% chance). Since 2012, Mike Trout ranks 10th on converting Remote chances, 1st on making Unlikely plays, and 9th on converting Even chances.
15. Last year’s two Rookie of the Year winners were, respectively, three and four years older than Mike Trout. Only one of the four Rookies of the Year elected since Trout is younger than he is. (Of course, Bryce Harper, elected at the same time as Trout, is the youngest of all. Harper has yet to face a single MLB pitcher younger than he is. But this isn’t Bryce Harper Facts.)
16. Measured by Wins Above Replacement (WAR), Mike Trout is responsible for 95.8% of the offensive value of the 2015 Angels roster. This is partly because Matt Joyce, C.J. Cron, Drew Butera, and Chris Iannetta have provided negative value by hitting a combined 41-for-270 (.152).
17. Measuring again by Wins Above Replacement (WAR), and bearing in mind that hitters can give their team negative value: in 2013, Mike Trout was more valuable (10.5 WAR) than all the hitters on the Mariners, Marlins, White Sox, and Astros, COMBINED (10.4 WAR).
18. Over 2012-15, Mike Trout is in the top ten players for home runs (#6), triples (#1), hits (#6), stolen bases (#7), batting average (#8), on-base percentage (#2), weighted on-base average (wOBA) (#2), isolated power (#6), batting average on balls in play (#1), and plays made in the outfield (#2).
The Washington Nationals, FanGraphs staff unanimous picks to be NL East champions, are off to a rough 7-12 start. Whether those struggles will continue is a matter for another post.
We are not here to talk about what ails the Nationals, or how to fix it. We’re here for a curious hypothetical: what if the Nats’ collapse continues? What if they are below .500 at the All-Star break and become trade deadline sellers?
We’re going to examine four questions. Who would the Nationals sell, how much would the team’s core change, how much money does this save them in 2016, and when would the team contend?
1. Who would the Nationals sell?
Jordan Zimmermann, Doug Fister, Ian Desmond, and Denard Span are impending free agents. Those are four very big names. The Nationals would be poised to offer two of the most valuable starting pitchers on the summer market; Zimmermann and Fister might be rentals, but they also don’t come with Cole Hamels’ massive contract. I think the team could also deal two players who will be free agents after 2016: Stephen Strasburg and Drew Storen.
The potential return here is, obviously, massive. We’re talking about trading away three members of a pitching rotation some analysts thought would be historically great. Strasburg clocked in at #23 on Dave Cameron’s offseason trade value rankings, just behind now-injured Yu Darvish. Although it would be frivolous to speculate on trading partners, given that our scenario is already far-fetched to start with, Ian Desmond and a starting pitcher could go a long way toward solving the Padres’ roster issues.
There are probably only two or three teams in the league that could meet an asking price for Strasburg. Maybe one of them gets desperate. If so, the Nationals probably gain at least one long-term core player. It won’t be Mookie Betts, but then, most good major league regulars aren’t Mookie Betts.
2. How much would the team’s core change?
They would still have Bryce Harper, Anthony Rendon, and Ryan Zimmerman batting, and Gio Gonzalez, Tanner Roark, and Max Scherzer on the mound. You can do worse. 2016-17 will bring Michael Taylor to the outfield, Trea Turner to shortstop, and a number of pitchers into the majors, perhaps including Lucas Giolito, Reynaldo Lopez, Joe Ross, and/or A.J. Cole.
That does not a championship 2016 roster make, but GM Mike Rizzo can demand near-league-ready talent in exchange for half his rotation, his center fielder, his shortstop, and his closer. That’s a lot of bargaining chips, and Rizzo is historically good at extracting trade value. (Wilson Ramos, Tanner Roark, and Doug Fister were acquired for players who contributed a combined -1.6 WAR to their new teams. I am not making that up. Negative 1.6. This excludes Steve Lombardozzi, who never played for Detroit, but posted -0.3 WAR for Baltimore.)
Funnily enough, if this is an imaginary July 2015 where the Nationals are already struggling to reach .500, I don’t think trading everyone away would make the team much worse. The infield can limp to the offseason with Danny Espinosa and Dan Uggla; Michael Taylor can return to center field; and Tanner Roark would step back into the rotation. It’s clearly a less talented roster with less awe-inspiring pitching, but they won’t fall to the cellar, either.
3. How much money does this save in 2016?
Stephen Strasburg and Drew Storen are both entering arbitration, after earning a combined $13.1M in 2015. With Zimmermann, Fister, Desmond, and Span coming off the books, the team doesn’t exactly need to worry about money. Those six players represent $61M of the 2015 payroll. They can also buy out Nate McLouth.
Remember, though, that Rendon enters arbitration in 2016, and Harper a year later.
The only long, potentially burdensome contracts on the club belong to Scherzer (not yet a problem), Ryan Zimmerman (a few years of on-field value remain), and Jayson Werth (ditto). That could be a lot worse. The team does not have an albatross yet.
4. When would the team contend?
With the new wild-card game, the imaginary blown-up Nationals would be contending again in 2016. You still have the core talents of Scherzer, Harper, and Rendon; Gio Gonzalez and Tanner Roark eating innings; and several useful prospects for the outfield and rotation. Surround them with a raft of young talent acquired at the deadline, cross your fingers Lucas Giolito doesn’t blow out his shoulder, and the team would have playoff upside in 2016, with a chance at a division title in 2017.
The Nationals should be fine for 2015. This is still the best and most talented club in the NL East.
But if the Nationals implode? They have a real chance to rebuild very quickly indeed. The Red Sox just went worst-to-first, then back to worst, and now they’re bidding for first again. The “to first” part of that trajectory will be the Nats’ inspiration. If 2015 does become a nightmare in D.C., the Washington front office can use speedy recognition, honest self-assessment, and savvy trading to rebuild a new contending team, and quickly.
In the June 26 Nats-Cubs broadcast, Washington announcers Bob Carpenter and F.P. Santangelo had a conversation about how managers use statistics, and in particular how Matt Williams managed a 16-inning epic against Milwaukee.
“He was relying on batting average with runners in scoring position,” Santangelo said, “and to me that’s the best stat going.” They added that Cardinals manager Mike Matheny uses it, and Matheny told them that “it was a lot of managers’ favourite stat.”
Go ahead and freak out a little. But I’m curious. If you were judging hitters based on batting average with RISP, how different would your judgments be than if you judged them based on AVG, wOBA, or wRC+?
I can’t figure out how to insert a table, so here is a handy and also dandy chart for your surveyal, with helpful, pretty colors! You shall behold the 2013 leaders – minimum of 100 plate appearances, to include pinch-hitters who might pop up in a 16-inning game – for average, wOBA, wRC+, and BARISP. Hitters who appear in all 4 columns are colored peach, and hitters who appear in 3 of the 4 columns are colored blue. (Note: Hanley Ramirez should have been in the fourth column, too. Somehow the leaderboard I pulled left his name out.)
What do you notice? Well, yes, there is a lot more overlap between the first three columns than the last one. I might be counting wrong, but it looks like over half of the BARISP leaderboard does not appear in a single other column. (Many of them are Cardinals.) And yet, the truth is, almost all of the top 25 BARISP leaders were, in fact, good hitters in 2013. The three worst hitters on the list, by wRC+, are Michael Brantley (104), Manny Machado (101), and Brandon Phillips (91). That’s not a terrible bench. (On the other hand, Pete Kozma looms.)
The truth is, good hitters are good hitters. A manager relying on BARISP would not suddenly disregard Josh Donaldson, Miguel Cabrera, or Paul Goldschmidt.
Who would lose the most from a reliance on BARISP instead of advanced stats? Arguably, the guys who appear in the wOBA and wRC+ columns, but not the BARISP one. There are 15 of those players, favored by advanced numbers but not by “the managers’ favourite”. Of those 15, 8 still have BARISPs above .280. Here are the bottom five:
5. Khris Davis, .250 (43 PA)
4. Shin-Soo Choo, .240 (144 PA)
3. Joe Mauer, .239 (113 PA)
2. Yasiel Puig, .234 (99 PA)
1. Jeff Baker, .162 (44 PA)
On my custom BARISP Snub Leaderboard, there are only a handful of players a real manager might pass over. (Who would bet against 2013 Joe Mauer?)
In other words, even though a true stathead might yelp in terror at the thought of his team’s manager using BARISP to select a hitter, the process does not actually yield many bad results. Good hitters will be good hitters, even if your measure is slightly faulty. Your coach might bench Yasiel Puig for Brandon Phillips, which obviously would be bad. It’s also unlikely. More likely might be benching Khris Davis for Michael Brantley, and would you truly be that offended?
On the other hand, Pete Kozma looms.
A few days ago Dave Cameron published a post outlining some wild new rules for an alternative baseball. I missed it at the time, since I am on holiday in Sweden, but one Wi-Fi hotspot later, I was walking the streets of Stockholm thinking about the Dave Cameron Rules.
This post will make no sense to you unless you read the idea for “Daveball”, so go do that now. In it he asked a number of questions about what managers would do. This is my reply.
Overall Season Strategy
If every current game is divided by 3, the season schedule will be 486 games long. Playoff teams will lose 200 contests a year. The dramatically lower stakes make it easier to deliberately lose games.
Suppose you are facing Jose Fernandez. He will start Game 1 and probably continue to Game 2. Your own available pitchers are a mixed bag, so you save the best ones until the game(s) after Fernandez departs. As with bunts, every manager will need to calculate the risk and reward of trading unlikely wins for increased odds in another.
I also see a need for a new rule restricting roster moves to one time per day. (Not one move; one time.) This closes a new loophole wherein teams can call up a player for one three-inning game only. Not many teams have minor leaguers nearby to do this, but Texas, for example, could have an AA player report to Arlington instead of Frisco, call him up for Game 2, and have a spent pitcher hide in the clubhouse being “demoted”. This would give an unfair advantage to the few teams for whom this possibility exists.
I see options for a manager under these rules. Broadly speaking, there are three. The first is only modest changes to status quo, such as bringing high quality relievers in at the sixth inning as well as the ninth.
The second option is to convert current mediocre starters into one-game pitchers. Consider the Washington Nationals, who have four pitchers capable of throwing two games in a day, and five pitchers, either borderline starters or long relievers, who could pitch one game a day well (Tanner Roark, Ross Detwiler, Taylor Jordan, Craig Stammen, Blake Treinen). Especially if you believe the weakness of a borderline starter is getting through a lineup the second time, they can suddenly become very valuable.
Here’s how to do it. (Listen up, Astros.) Convert a few of your guys and trade for some more. You could have around seven or even eight of these starters, plus relievers for the other innings and for getting out of trouble. The shorter starts will make these pitchers more effective. Today’s market for mediocre one-inning relief will transform into high demand for mediocre five-inning guys who can pitch effectively for three.
The third option is extreme: all short-outing guys, all the time. Every day, every pitcher only goes four or five outs. This would lengthen the games considerably, but on the other hand, fans could see a barrage of 98 mph high heat.
The major change to mound strategy will be an increased reliance on strikeouts and the near death of the intentional walk. I will explain this shortly.
Dave Cameron already pointed out several key changes to batting strategy: put all the best hitters at the top of the order, and pinch-hit early and often. (The pinch-hitter would actually function like a movable DH.) Sometimes it will be advantageous to work counts, but sometimes the short games will call for aggressiveness. Either way, the run-scoring environment will be very different. With a sudden surplus of decent pitching, and probably a slight increase in average velocity, batting will become harder.
Scoring, however, could be easier.
Under Dave Cameron’s rules, Billy Hamilton would become the most valuable player in baseball.
Here’s how it works. The logic of pinch-hitting for weak defenders, then returning them to the next game, applies to pinch-runners, too. If your slugger draws a walk, put in Billy Hamilton. Every time.
Let’s assume your team is fairly good, and has at least one baserunner in 95% of games. Billy Hamilton has scored about 62% of the time he reaches base, with an 83% steal success rate. To compare, Mike Trout has scored about 42% of the time he reaches. There are other factors at work, but I’m on holiday, so ignore them. Hamilton should be running for any player, if the situation demands it, but for sale of argument (and of me writing this on a phone) assume that in 95% of 486 games, Billy Hamilton increases your odds of scoring by 20%. That’s 92 additional runs per year, and not over replacement level, either. Suddenly an elite runner becomes the most valuable weapon in the game.
Three factors could limit the damage. First, managers could be dumb or unlucky and use runners at the wrong times. Second, defenses could invent some kind of wild new “no steals defense”. I have no idea what this would look like, but teams would be forced to try.
Finally, every team will acquire their own super-runner. (Currently a running-only player is a waste of bench space, but the opportunity to use him or her three times per game without penalty would change the math.) Oakland would call up Billy Burns. Some teams would sign actual Olympic sprinters, train them in fundamentals like pitch recognition and sliding safely, and set them loose. (This is how we would acquire the first female player.) If Usain Bolt breaks for second base, a catcher will throw to third to limit the damage.
More than anything else, the runners will change baseball. Intentional walks will never be used with one or zero men on base. Unintentional walks will force wild pitchers out of the league. Strikeouts will be a priority as the third-inning hitting strategy is simply to get on first base.
I couldn’t think of much here, except for almost universal use of the no-doubles defense (especially once the enemy has used his runner). Probably shifts would be more common.
Dave Cameron’s rules would accelerate some trends we already see in baseball: more strikeouts, more speed, more reliance on defense. But it would also inspire madness, like nine-man starting rotations comprised of suddenly valuable borderline starting pitchers, and female sprinters charging toward home plate on squeeze plays. The game would be unrecognizable and loony, but also a lot of fun. And Billy Hamilton would punch a ticket to the Hall of Fame.
On April 24, Danny Espinosa had a remarkable game. He bunted for a hit and had a solo home run to the left-field corner. The bunt was the remarkable part.
Danny Espinosa has seven (7) bunt hits so far in 2014. That’s more bunt hits than 28 MLB teams, in a tie for first place with the Marlins and Danny’s D.C. teammates. In fact, Espinosa’s bunts account for 35% of his total hits (7/20), and he’s only failed once.
This is so unprecedented that a better word would be “outrageous”. In 2013, Leonys Martin led the MLB in bunt hits with just 12. And Martin only succeeded 40% of the time that he tried getting on base with the bunt. I had to go back to 2011 to find a guy who pulled off the base-on-bunts 20+ times in a season: Juan Pierre attempted 62 and succeeded with 23.
Only one qualified hitter in recent (batted-ball data) history has done anything even slightly similar to what Espinosa is doing so far. Fully 20% of Willy Taveras‘ career hits were bunts; he succeeded nearly half (46%) of the time, racking up a total of 130 bunt hits, including 38 in the year 2007, which is the single-season record, even though he only played in 97 games (!!). Only Juan Pierre has more bunt hits in the batted-ball-data era, but he’s much less successful on a percentage basis.
There are many reasons to think Espinosa won’t follow in their footsteps. For one thing, he’s a very different hitter: not a powerless center fielder who relies solely on speed, but a homer-happy middle infielder with a dangerous strikeout tendency.
In fact, therein might lie an explanation. Last year, Danny Espinosa hit rock-bottom, plagued both by injuries and the stupid belief that he could play through his injuries. His collapse was uglier than Ron Burgundy’s, and he put up a .280 OBP in the minors. Now he’s on the comeback trail. The power is back. The strikeouts are back. The batted-ball profile in general is back to pre-2013 numbers.
With one big exception: the bunts.
I believe this is deliberate. Espinosa is trying to get on base, he’s trying to cure a predilection for infield pop-ups, he’s trying to re-establish himself against major-league pitching, and he’s trying to re-establish himself in a lineup where he’s currently filling in for an injury. He likes unorthodox approaches to reaching base, leading the NL in hit-by-pitches in 2011.
Given Jeff Sullivan’s recent series of posts about bunts, bunting is a tougher skill than we’d think. Danny Espinosa was always good at bunts. (Maybe we can convince Jeff to make GIFs of all seven bunt hits so far.) In 2011 and 2012 his bunt hit attempts succeeded about 43% of the time, nearly as good as Willy Taveras. He chipped in a few sacrifices, though not too many. He might commit to this stratagem until teams start expecting the bunt every time he steps in.
If Danny Espinosa wants to set records, the records are there for him to take. If he succeeds on even half his attempts, that’s a season record. If he succeeds 32 more times, that’s a season record. You’d be crazy to believe he will break those records. But you’d have been crazy to believe, a month ago, that he would have even had a chance.
Once upon a time there was a 31-year-old right-hander who spent years toiling as a fifth or sixth starter for the Rangers. But then one year he signed with a new team who thought he could be their ace, and so an ace he became. Or did he?
Scott Feldman is off to a remarkable start. He’s pitched 20.2 innings in three starts, and allowed a grand total of 1 run, and only 7 hits. Of the 7 hits, 6 were singles.
Unfortunately, it’s a little too early to believe fairy tales can come true. Let’s find out why.
First of all: Scott Feldman is not striking guys out. Of the 79 batters he’s faced, he’s struck out just 7, which is the second-lowest K rate of any starting pitcher, behind only Brett Anderson. In fact, Feldman is walking (8) and plunking (5) more guys than he strikes out. That does not inspire confidence.
So what’s his secret? Well, opposing batters hit the ball a lot against Feldman, but they don’t reach base safely. When opponents swing and put the ball in play, their batting average (BABIP) is .119. The league average BABIP is about .300, because when you hit the ball at professional defenders, there’s about a 70% chance they will get you out. Several factors influence this average: pitchers causing weak contact, hitters having natural talents (or lacks thereof), hitters being fast enough to beat throws to first, defenses of varying qualities, and just plain old luck.
Holding opposing hitters to a .119 BABIP screams “luck.” But there are other things we can check first.
Let’s look at Feldman’s arsenal. Is it different? Yes. For the first three years of his career, Feldman leaned on his fastball; from 2010-13 he replaced the traditional fastball with a sinker and a cutter. So far in 2014 Feldman’s primary pitch has been his curveball, which he throws 37.7% of the time; after that comes the cutter, with his changeup and sinker used very rarely.
Here is a list of the top three curveball throwers in 2013, and what % of their pitches were curvaceous:
1. Jose Fernandez (33.6%)
2. Scott Feldman (27.5%)
3. Adam Wainwright (27.3%)
So is Feldman ditching the sinker and leaning on the curve because that will give him better results? Maybe, but if that’s the case, he should have ditched the cut fastball instead: in 2013 his sinker and curve generated ground balls more than half the time, but many cutters went for line drives, including over half of the doubles and triples he gave up. Unfortunately, that’s not the pitch he replaced. It’s the pitch he kept.
So far this year, Feldman’s efficiency as a ground-ball pitcher has actually taken a hit. But it’s too soon to make sense of the data, or at least too soon for me, because the data is confusing. Maybe Feldman is deliberately trying to generate fewer groundballs, or maybe random things are happening and other teams are hitting the ball everywhere.
Either way, the Astros defense has had to work almost every time a batter steps in against Feldman. And not a single Astro has committed an error while he’s pitching. There are a few good defenders on Houston’s team (Jason Castro, Jose Altuve, Matt Dominguez, and Dexter Fowler). But there are also plenty of not-good defenders. One surprise is that shortstop Jonathan Villar, whom I have seen make some bone-headed plays in the past, has so far reversed course from being a bad defender to a good one. But it’s only been two weeks; time will tell.
Indeed, looking at the fairy-tale start to Scott Feldman’s year, “it’s only been two weeks” is the best explanation. He does not strike batters out; he leads all the MLB in hit-by-pitches; his fastest pitch so far has been exactly 90 mph; and he is relying on a patchy defense which has yet to fail him once. The curveball is pretty good, but no starting pitcher can rely on a curve as a primary pitch. And that .119 BABIP is a fluke. Last year Feldman’s opponents went .258 when they put the ball into play, which put him in the top ten among all pitchers. But even if Feldman has a real skill for making the ball go to his defense, .119 is crazy, and he will soon be dealing with twice as many baserunners.
One of these days, the clock will chime midnight and the balls opponents hit off Feldman will start getting past defenders, dropping into the outfield grass, popping out of gloves, or going over the fence. That’s not bad; that’s normal. When midnight tolls, he won’t turn into a pumpkin. But he will turn back into Scott Feldman.
Advanced statistics in baseball have an image problem. A romance problem, if you will. Specifically: the idea of a grizzled scout looking out onto the battlefield and seeing the kind of gritty player who wins ballgames, well, that has romance. A dude plugging wOBA and wRC+ into a spreadsheet? In the words of ESPN, “We’re all gonna go dateless!”
A point must be made: the opacity of the acronyms themselves is a major factor in the perceived complexity of the statistics. Imagine integrating them into regular conversations, if you don’t already do so (and still have friends). “He’s above average as a hitter. You can tell from his double-you are see plus.” “Whoa, dude, that sounds too damn complicated.” “The guy’s got terrible range at shortstop, though. That’s why he can make highlight-reel plays with a terrible UZR.” “Oozer? I hardly know ‘er!” And so forth.
We statheads, cocooning ourselves in things like RA-9 WAR and expecting our friends to catch up, might make it easier on them by explaining what we measure in plain English. There are FanGraphs writers who are very good at this; it’s why they get paid money for what they do. Some other folks need a little help.
My modest proposal is to revise the acronyms we use to signify some of our favorite statistics. With a little luck, a little savvy, and a medium-height English literature graduate, we can create new terms which both summarize the needed statistic and are catchy to say aloud. For example:
– isolated power (ISO). ISO is used to show a hitter’s raw power. Batting average is hits divided by chances for hits; ISO is extra bases taken divided by chances for hits. And we can make that even more clear by calling it Hitting Ultra Long, Knowledgeable Statistic Measuring Ability to Stroke Homers (HULKSMASH).
EXAMPLE: “Jose Bautista was a pretty unremarkable hitter for most of his career, until September 2009, when he came out of nowhere with an amazing HULKSMASH.”
– weighted runs created plus (wRC+). What lies behind this dorky name? Well, we first measure roughly how many runs a player creates with his bat, using hits, walks, and so on. Then we create a putative average and set that at 100. Then everything’s scaled so that, for instance, 120 means you’re 20% better and 5 means you’re 95% worse than average.
Wouldn’t it be useful if the name wRC+ explained itself in plain English? For instance, we might explain that we’re comparing runs added by a player to a putative average. In other words, Comparing Runs Added to Putative Mean of All Players (CRAPMAP).
EXAMPLE: “The New York Mets lineup is all over the CRAPMAP. Last year David Wright’s CRAPMAP coordinate was 155 but Kirk Nieuwenhuis was way down at 72.”
In light of the negative connotation of “crap,” we might consider reversing the scale so that higher numbers mean more crappiness.
– ultimate zone rating (UZR). This measures how good you are at defense, but I don’t know how it works. The proposed replacement acronym reflects this central mystery, but it also describes the statistic much better than UZR, which for all I know could measure how “in the zone” somebody is. Let’s change it to Fielding: Official Numerical Descriptive Utility of Excellence (FONDUE).
EXAMPLE: “Last year, with all his throwing issues, Ryan Zimmerman was one of the worst defenders in baseball as measured by FONDUE.”
– baserunning (BsR). Okay, this one’s pretty simple, so simple I don’t even know why we gave it such a silly abbreviation. Was BSR taken? Or just BR? Anyway, we don’t need to worry about it anymore, because now we’re checking on Hitters Effectively Running Bases, Assessed Logically (HERBAL).
EXAMPLE: “The Colorado Rockies are hoping that outfielder Charlie Blackmon will supply them with a lot of HERBAL this year.”
– batting average on balls in play (BABIP). Simple, you think. But more descriptive yet is Batting Average Regarding Fair Contact Only if Playable (BARFCOP).
EXAMPLE: “I don’t think he can sustain that success going forward. No hitter, no matter how good, can escape the consequences of having such an erratic BARFCOP.”
– weighted on-base average (wOBA). First of all, what’s with the lowercase W? Is wOBA the iPad of stats? Second, this is another term whose meaning is unclear. We could explain to readers that wOBA weighs various outcomes (single vs. home run) and makes the more important outcomes a more important part of the equation.
Or we could go with the coolest acronym and call it Weighted Hitting Assessment Measuring Meaningful Outcomes (WHAMMO).
EXAMPLE: “Joey Votto is a great guy. He’s always going to have his WHAMMO sitting among the very best.”
And finally, the most important stat of all:
– wins above replacement (WAR) or victories over replacement player (VORP). To the average baseball fan, WAR is a bit of a nebulous concept. “Mike Trout is worth ten wins.” “Uh, whaddya mean?” Now, if you explain it for twenty more seconds, they’ll understand just fine. But wouldn’t you rather we had something everyone can understand and get behind? Wouldn’t you rather have it that nobody would dare speak an ill word about WAR?
Well, that’s possible. We just call it Baseball Excellence Exceeding Replacements (BEER). Same concept. Same math. Same powerful analysis. Just measured in BEER.
“Well, it’s like this. Imagine if the average AAA guy was worth zero BEERs, and the average major leaguer was worth, say, two BEERs.”
“Mike Trout is worth ten BEERs.”
“I’ll be damned.”
Before you know it, everyone in baseball will be talking the language of statistical analysis. And we won’t all be going dateless. We’re the ones with the BEER.
Mea culpa. After posting an in-depth look at Albert Pujols‘ lone sacrifice bunt, readers both friendly and unfriendly pointed out to me that there is record of three more major-league Pujols bunt attempts, two for hits and one a squeeze (but no other known sacrifice attempts). The only satisfactory way to own up to my mistake is to follow up with a new essay asking: why did Pujols bunt those other times? Any errors in this new post are the responsibility of Session Lager the author.
Bunt No. 2: May 23, 2003
What was the bunt? Albert Pujols had a good day. He struck out in the first inning and then racked up five hits (two doubles), including one in the top of the tenth inning. It’s the 10th inning we’re looking at here.
With two outs and a runner on second base, J.D. Drew hit a triple to deep center field; the runner scored, giving the Cardinals a 9-8 lead. Next, Albert Pujols singled on a bunt to third base, scoring Drew and making the lead 10-8. The Pirates couldn’t recover in the bottom of the inning.
Was it a good idea? This was a squeeze play with two outs. In the tenth inning. Using a batter who had only bunted once before. On the other hand, the Cardinals already had the lead they needed. It was a daring mad-scientist gamble. The bunt had to be perfect.
Did it work? The bunt was perfect.
Bunt No. 3: July 27, 2003
What was the bunt? Only two months later and against the same Pirates, Pujols attempted to bunt for a hit and failed in the 8th inning. His Cardinals were losing 3-1, and there was one out and no runner on base.
Was it a good idea? Albert Pujols was facing Brian Boehringer (5.41 FIP, 4.33 BB/9, -0.7 WAR that season). He may have been emboldened by the memory of his recent success, but given how good Pujols was at not-bunting, and how bad Boehringer was at pitching, this attempt is only understandable if it was an attempt to take the enemy by surprise. Pujols bunted on 0-1; whether he showed bunt on the first pitch (a called strike) is lost to the sands of time.
Did it work? No, but in the next (9th) inning, with two outs, Pujols had a walk-off single to win the game.
Bunt No. 4: August 25, 2004
What was the bunt? It came on another good day: Pujols singled, doubled, and homered. And the single was a bunt to third base on a 1-0 count in the 8th.
Was it a good idea? See, this is the thing with bunt-for-hit attempts; without seeing the defense at work, and without understanding the state of play, all we have to go on is hindsight. John Riedling was another troubled pitcher, almost identical to Boehringer (5.24 FIP, 4.64 BB/9, -0.7 WAR that year); both also suffered from inflated home run rates. They were, presumably, easy pickings. And, indeed, Jim Edmonds brought Pujols home on a game-tying line drive over the fence.
Did it work? Yes.
What can we learn, aside from that the author needs to be a little more diligent? That Albert Pujols has done okay as a bunt artist. His first try, as a rookie, remains incomprehensible, but he then executed a flawless two-out squeeze play and went 1-for-2 in tries for a hit. I’m inclined to believe that the tries for hits represent opportunism, and that the lone sacrifice and the squeeze play represent Tony La Russa’s management philosophy at work. On my last post, reader Tim A wondered if that first bunt was La Russa simply testing Pujols’ ability to lay the ball down.
It’s still kind of weird that the then-best (or best non-Bonds) hitter in baseball tried a squeeze bunt on two outs. It’s definitely weird that a rookie with 20 homers would be called upon to bunt from the cleanup spot. But hey, we discovered a new wrinkle: Pujols is pretty good at yet another part of baseball. And in games in which Albert Pujols bunts, his team is 4-0.
Possible Teasers if I Decide to Write More of These at Some Point
According to the batted ball data (except where this data is incomplete, starred*), here are some more career bunt attempt totals: Adam Dunn 3, Manny Ramirez 2*, David Ortiz 11. In 2009 Jack Cust went 3-for-3 on bunt hit attempts. That same year, 3 successful bunt singles were laid down by Pablo Sandoval.
One time, Albert Pujols bunted.
If we include minor-league play, he’s bunted twice in his professional career. But in the major leagues, the major leagues where he’s played for 12.5 years and hit (as of July 10) 489 home runs, 523 doubles, and on average 1.198 hits per game, the major leagues where his career batting average is .321 and he hits twice as many doubles as double plays, Albert Pujols has bunted once.
It was in his rookie season, of course. But what exactly happened? Why did he bunt?
Theory #1: Pujols was an untested rookie.
Strike one. Albert Pujols bunted on June 16, 2001. When the baseballing world awoke that day, he was a rookie batting .354/.417/.654, with 20 home runs. He’d already been intentionally walked three times. (Compare to our latest Rookies of the Year: Mike Trout was intentionally walked four times in all of 2012; Bryce Harper, zero.) Pujols had 11 hits in the previous seven games, including four homers.
Now, this was only two and a half months of gameplay, a small track record. But if you’re savvy enough to realize that ten weeks is not enough time to assess a player’s quality, you’re probably also savvy enough to realize that this is not the type of player who should bunt.
Unless, of course, it’s a critical situation in the game.
Theory #2: Pujols was bunting at a time when the Cardinals really needed a bunt.
Strike two. Albert Pujols bunted in the bottom of the seventh inning, with the Cardinals ahead 6-3. In the top of the same inning, the White Sox had scored two runs, but St. Louis’ win probability was a healthy 96% when Pujols came to the plate. After he bunted, their odds of winning were still 96%.
Now, in some ways it was a textbook bunt situation. The Cardinals had two men on base. They also had zero outs. No outs and two on is a good time to bunt. But they also had a three-run lead in the seventh. And Albert Pujols was batting cleanup. He bunted.
Theory #3: Pujols was facing a pitcher against whom he might have trouble.
Strike three. The White Sox did bring in a new pitcher to face Albert Pujols, a thirty-year-old right-hander named Sean Lowe.
Now, Sean Lowe was pretty good against right-handed hitters. In 2001, righties hit .233 off him. They didn’t strike out much, but they didn’t walk much either, and they made unusually weak contact. We can suppose this because when lefties put balls into play against Lowe, their batting average was .308, but righties’ batting average on balls in play against Lowe was only .243.
On the other hand, the Sox didn’t trust Lowe that much. According to Baseball Reference, he was placed into low-leverage situations more than half the time in 2001. In 17 of his 34 relief appearances, the Sox were already losing–as they were on this day, losing by three runs with only six outs left. (That’s 17 of 34 in a year when the team had a winning record.)
Oh, and there’s another thing. Albert Pujols was killing right-handed pitching; when 2001 was over, his AVG/OBP/SLG against righties was .342/.408/.624.
No, the White Sox brought Sean Lowe into the game not as a magic bullet, but as something simpler: a Band-Aid. Ken Vining had allowed two runners to reach base without getting the inning’s first out. They simply needed somebody new.
Theory #4: Bonus Dan Szymborski theory: the element of surprise.
I asked Dan Szymborski why he might have Pujols bunt in a FanGraphs chat. His reply: “It may be a good surprise play if he’s confident he can get it down and the 3B is super deep or is Mark Reynolds.”
Strike four. Pujols bunted successfully on the second pitch; the first was a foul bunt attempt, terminating the element of surprise and any super-depth on the part of the defense. The third baseman was Joe Crede.
Theory #5: We’re out of theories.
Let’s set the scene, shall we?
The game is in St. Louis. As the fans sit down after their seventh-inning stretch, the Cardinals are winning 6-3. They’re six outs from victory, with odds of 95%, and their 2-3-4 hitters are due up. Chicago reliever Ken Vining starts the inning by walking third baseman Placido Polanco on four pitches. Next J.D. Drew hits a line drive single to right field on a 1-2 pitch, and Polanco advances to second.
This brings up cleanup-hitting right fielder Albert Pujols. The White Sox replace the flailing Ken Vining with Sean Lowe, a middle relief righty who induces weak contact. (Within a month, Vining will pitch his last major-league game.) The Cardinals have their best hitter at the plate: he’s a rookie, but he’s batting fourth, already has 20 homers, and sees two runners on base with no outs.
On the first pitch, Pujols bunts foul. On the second pitch, Pujols bunts fair.
It works, technically. Polanco and Drew advance, and Bobby Bonilla steps up to the plate. This was the 38-year-old Bonilla’s final season, and at the time of this game, his triple slash was a pitiful .217/.321/.391. (It would get worse, but remember, this is who Pujols bunted in front of.) Bonilla has had four home runs all year, one of them the day previous.
Bobby Bonilla is issued the second-to-last intentional walk of his major league career. (Yes, there was another one; he drew three IBBs that year.)
This brings up left fielder Craig Paquette, staring down loaded bases. He delivers a two-run single, putting the Cardinals up 8-3. Sean Lowe gets Edgar Renteria and Mike Matheny out to end the inning. The Cardinals win the ballgame by the same score, and in the ninth inning the last White Sox hitter to go down is a pinch-hitter making his major-league debut, named Aaron Rowand.
So Why Did Pujols Bunt?
Pujols tried to bunt twice, once hitting the ball foul. This suggests that it wasn’t Albert’s idea but his manager’s. If Pujols was the kind of player who liked to bunt spontaneously, he might have done it again by now.
Why did Tony La Russa have Pujols bunting? His team up by three runs, late in the game, two runners, no outs, best hitter at the plate. Perhaps he was overly concerned about Sean Lowe’s ability to get righties out, but there weren’t any outs and a double play would still leave a baserunner. Perhaps he recognized a classic bunting scenario, but Pujols was his best hitter and Bobby Bonilla, with a slugging percentage .263 lower, may have been his worst. Maybe he wanted to spring a surprise, but then came the foul bunt.
The St. Louis Post-Dispatch archives don’t turn up any hits for “Pujols bunt.” One blog post about the bunt groundlessly speculates that Pujols was improvising. Googling “why did Pujols bunt” in quotation marks yields zero hits. And, looking at the evidence we have, there’s no rational explanation. I’ve hand-written Tony La Russa a letter asking about this, but that was over three months ago and there’s not much chance he writes back.
Aaron Rowand played for eleven seasons, was an All-Star, and won two World Series. His entire career has taken place since the last time Albert Pujols bunted. That’s interesting, but not surprising. What’s surprising is that the only time Pujols bunted, there was no reason for him to do so.
Albert Pujols bunted once. We may never know why.
Earlier this season I looked at the ten lowest BABIPs since 1945, investigating what, exactly, this statistic can teach us about hitters. The conclusions ranged from clear to not-so-much: your batting average on balls in play will be lower if you’re too slow to beat out infield grounders, if you hit an unusually low number of line drives, if you’re getting poor contact by swinging at bad pitches, and if you’re just plain unlucky. Sometimes players saw their power numbers drop along with their BABIPs, most likely because of an inferior approach at the plate which caused weak hits, but sometimes players saw their power numbers rise sharply: one of the ten lowest BABIPs ever belongs to Roger Maris, because he put 61 balls out of play and over the outfield fences.
Will our high scorers clear things up?
What is BABIP? (Copied from the First Post)
Batting average on balls in play is exactly that: when you hit the ball and it’s not a home run, what’s your batting average? Imagine you’d only ever batted twice; first you hit a single and then you struck out. Your BABIP would be 1.000. If a single and a groundout, .500. After seven games of the 2013 season, Rick Ankiel had two home runs but no singles, doubles, or triples, so his BABIP was .000.
Across any given season, the average BABIP tends to be about .300. All this means is that, when you hit the ball at professional defenders, there’s a 70% chance they’ll get you out.
The Ten Highest BABIPs Since 1945
10. Willie McGee, 1985 (.395). McGee’s presence here isn’t surprising, since his hallmarks, aside from excellent hitting skills (and not much power), were speedy outfield defense and quality baserunning. It’s easy to imagine McGee beating infield grounders, hustling out hits, or being above average at driving the ball, even though some of those statistics weren’t tracked at the time.
9. Derek Jeter, 1999 (.396). Jeter’s 2006 ranks 17th on the list, too. Jeter’s 266 infield hits since 2002, when batted-ball data started being counted, ranks second among all hitters in that decade-plus. First place? You’ll find out who that is in a minute (if you don’t know already).
8. Wade Boggs, 1985 (.396). Hey look, two top-ten BABIP seasons in the exact same year! Boggs edges McGee and the whole league with 240 hits in 161 games, 187 (77.9%) of them singles. During all his batting-title years, his BABIP was high, bottoming out at .361. Lucky? No: more like extremely good contact skills.
7. Austin Jackson, 2010 (.396). Jackson’s breakout season in center field for Detroit (that .396 BABIP led him to a .293 average) was followed by a breakup 2011 when his BABIP dropped 56 points (still above average!) and his batting average and on-base percentage fell 54 and 28 points, respectively. So far in 2013 Jackson’s at a career low on balls in play, but he’s also dramatically reduced his previously ugly strikeout rate, which has bolstered his return to the ranks of the truly outstanding.
6. Andres Galarraga, 1993 (.399). Before Galarraga cranked out 47 home runs at the age of 35, he had an also highly improbable 1993. Triple slash, 1989-1992 (509 games): .246/.301/.399. Home runs in those 509 games: 62. Triple slash in 1993: .370/.403/.602.
Three observations. First, Galarraga’s batting average never came within fifty (!) points of that again. Second, this was his first season in Colorado, although it wasn’t a full one, as he only played 120 games. The Coors boost to his power was minimal, at first. Third, the guy could not take a walk.
5. Ichiro Suzuki, 2004 (.399). Will anyone be surprised to see Ichiro here? Speedy, with a near-mythical gift for hitting, Ichiro also has a gift for avoiding fly balls (23.8% flyballs, fourteenth-lowest in baseball since we started counting in 2002). And another thing we’ve been counting since 2002: Ichiro has 463 infield hits, 40% more than second-place Derek Jeter. In 2004, Ichiro had 57 infield hits in 161 games, or about one every series. Since 2002, Mark Sweeney has 12 infield hits in 690 games.
4. Roberto Clemente, 1967 (.403). Clemente was in the middle of a run of six consecutive 6.0+ WAR years. His high batting average on balls in play made this one his most valuable of all (7.7), 40 points above his career average (which was identical to his BABIP the year before). Clemente hit six fewer homers and five fewer doubles but 19 more singles, explaining the paradox that his slugging percentage rose while his power actually dropped.
3. Manny Ramirez, 2000 (.403). This is one of seven seasons in which Manny posted a BABIP above .350. I looked at batted ball data, available from 2002 onward, and found that Manny’s 22.6% line drives ranked 31st among the 481 hitters who’ve racked up more than 1,500 plate appearances since. Of course, Manny was inconsistent in that stretch. His .373 BABIP in 2002 coincided (or not!) with a line-drive rate of 25.3%. (Mark Loretta sits at first since ’02, 26.0%, while at second with 25.2% is Joey Votto, more on whom shortly.)
2. Jose Hernandez, 2002 (.404). I was alive and watching baseball in 2002 and I had never heard of Jose Hernandez. The Brewers shortstop had four pretty good seasons (1998-99, 2001, 2004), three terrible ones (1996, 2000, 2003), and a rather miraculous 2002 which found Hernandez riding a tidal wave of good luck on balls in play. His average rose 39 points, and dropped by 63 the next season; he struck out in literally one-third of his at-bats (188 Ks); his power numbers were unchanged. But, aside from luck, there was another big change. This was the first year batted-ball data is available, and the only year where Hernandez’ flyball rate was below 30%. Between Hernandez, Ichiro, and Jeter, flyball rate is a significant predictor of BABIP.
1. Rod Carew, 1977 (.408). What does it take to have the highest career BABIP of any finished career since 1945? (“Hang on,” you say, “what’s with this ‘finished career’ business?” “Ah,” I say, “Austin Jackson and Joey Votto are in the lead.”) Carew’s career BABIP is .359. Carew’s 1974 ranks 19th on this list (.391). So the guy was a great hitter: but his 1977 was extraordinary. An 8.5 WAR season, it saw a dramatic spike in singles, plus career highs in doubles, triples, and (tied with 1975) home runs. There was also an MVP award.
Again, some of the things we learned are unsurprising: speed is good; being an all-time great contact hitter is good. But there’s a twist: Jose Hernandez benefited from a whole lot of luck, and Rod Carew had the year of his life, but most of the guys here are obviously disposed to high BABIPs based on their skills. We were able to blame a lot of the bottom-ten seasons on hard times and bad breaks, but most of these guys are exceptional hitters with speed and contact ability.
And there’s a new factor begging for our attention.
When we looked at the ten lowest BABIPs, we were unwittingly at a disadvantage, because only one of those low seasons took place while batted-ball data was documented. Three of our ten highest have happened since 2002, though, as well as #13, 14, and 17, which means we have evidence of a new factor.
Hit more line drives, and your batting average on balls in play goes up.
Hit more fly balls, and it goes down–fast.
As a Community Research writer, I can’t insert a chart here; as a lazy person, I don’t have a chart to insert. But the next step in our inquiry is very, very clear. Does fly ball hitting suppress BABIP? Is it because of the increase in home runs, the ease with which defenders catch the ball, both, or neither?
Even More Pertinent Conclusion
We live in the golden age of BABIP. If I had done this “Ten Highest” post including 2013, the present season would have accounted for 40% of the list.
Among the top 20 BABIP guys with more than 700 games played in their careers, there are some retirees: Rod Carew (#2), Ron LeFlore (#7), Wade Boggs, Roberto Clemente, Kirby Puckett, Tony Gwynn, Willie McGee, and John Kruk. But 12 of the top 20 guys are currently active: Joey Votto (#1), Derek Jeter (#3), Shin-Soo Choo (#4), Matt Kemp (#5), Joe Mauer, Miguel Cabrera, Ichiro Suzuki, Matt Holliday, Michael Bourn, Ryan Braun, Wilson Betemit, David Wright.
As commenter Ferd pointed out last time, the league average BABIP was .260 in 1968; when I started the series, I relied on research which assured me that BABIP was consistent over time, but this is clearly not true. This means that there are two more lines of inquiry we should follow.
1. Why are so many BABIP leaders currently active? Is it a change in hitting style? Is it a change in pitching style? Is it a change in the data being used or the calculations being made? Or is it simply because most of them haven’t gotten older, slower, and less talented at the plate, and once they all age and retire order will be restored?
2. Wilson Betemit? How did that happen?