## Bunt it Like Barton

Daric Barton, first baseman for the Oakland Athletics, is currently tied for the Major League lead in sacrifice bunts. And a lot of people really do not like that.

Over at Athletics Nation, an A’s fan site, statistics-savvy contributors have been calling for manager Bob Geren’s head for months. Joe Posnanski agrees. He wrote a column the other day suggesting that, among other things, “[s]omebody tell that man to stop doing that immediately.” Matt Klassen at FanGraphs also agrees, arguing that every single one of Barton’s bunts has been a bad idea. How could the team that led baseball’s statistical revolution in the late-1990s and early-2000s be so stupid? How can Billy Beane sit back and let his manager throw away out after out by allowing Barton, a good on-base hitter, to sacrifice his plate appearances?

As Tom Tango explains, it is not so simple. Tango makes two points: 1) Barton may have a chance to reach base when he bunts; and 2) all the bunting may force infielders to play in, giving him more hitting room and making him more successful when he does choose to swing.

The latter point is difficult to measure, but Tango has provided help with the former. His run expectancy calculator is a wonderful tool that allows some analysis of Barton’s bunts. It is based on the idea that every combination of baserunners and outs has a certain average “run expectancy.” There can be zero, one, or two outs in the inning, and there are eight possible configurations of baserunners (empty, first, second, third, first and second, first and third, second and third, loaded). Multiply the three out states by eight baserunner states, and there are 24 different situations that can come up in an inning. For each of these states, a team can expect to score, on average, a certain number of runs to the end of the inning — the run expectancy. Input a batting line into the calculator, and you get a table that shows the run expectancy for all 24 states.

One more consideration before we plug in some numbers: the current A’s team is not good at hitting. Since they score fewer runs per game than most teams (in other words, fewer runs per 27 outs), each out is worth a little less than it would be for an average team. Their lack of offensive punch also magnifies the value of a runner moving 90 feet closer to home.

I plugged the A’s season batting line through Monday into the calculator, and all run expectancy numbers come from the resulting tables. Let’s first look at the numbers when Barton bunts with a runner on first and no outs. On average, the A’s should expect to score 0.873 runs between this situation and the end of the inning. If Barton successfully bunts the runner to second, the state changes to a runner on second and one out — a situation which yields an expectation of 0.648 runs. So by successfully bunting in this situation, it would appear that Barton has cost his team, on average, about a quarter of a run. However, a successful sacrifice bunt is not the only possibility. Barton could reach base, resulting in runners on first and second with no outs (run expectancy: 1.493). The bunt attempt could also fail, resulting in a runner on first and one out (run expectancy: 0.499). Barton is a good bunter and always bunts with the speedy leadoff batter on first, so his chance of failure is probably very low. For the sake of argument, let’s say he can expect to pop his bunt up or fail in some other way only about two percent of the time. What about reaching base? Using all of these numbers, a little algebra can tell us how much of a chance Barton needs to have to make this a good play.

P(Bunt Fails) * .499 + P(Bunt Succeeds) * .648 + P(Barton Reaches) * 1.493 = .873

I suggested that P(Bunt Fails) is perhaps .02, so we can set P(Barton Reaches) = X and P(Bunt Succeeds) = .98 – X to make the probabilities add up to one. Solving for X gives about .27, or 27 percent. This means that if Barton has a greater than 27 percent chance of reaching base when he bunts with a runner on first with no outs, then he is actually increasing the number of runs his team should expect to score. If he has a less than 27 percent chance of reaching base, he costs his team runs and would be better off simply swinging away.

Reaching base could include a bunt hit or a fielder error, but a 27 percent chance still seems like a stretch. How about when there is a runner on second and no outs, the situation in which Barton has most often been successful? Posnanski specifically blasted the decision to bunt in that situation, but the numbers are actually a bit better. Here is the equation:

P(Bunt Fails) * .648 + P(Bunt Succeeds) * .895 + P(Barton Reaches) * 1.715 = 1.044

With a runner on second and no outs, again assuming a two percent chance of total failure, the threshold is 19 percent — if Barton has better than a 19 percent chance of reaching, he is helping his team score more runs. The number still seems high, but, contradicting Posnanski, it appears that bunting in this situation is a better play than when there is a runner on first.

Barton has appeared to be bunting for a hit on many of his sacrifices, and though he has not succeeded, he must believe there is some chance he will get on base. And there are two other factors at work. First, the fielders must play further in if he is likely to bunt, making his non-bunt appearances in these situations far more valuable. Second, Tango’s tool also gives the chance of scoring at least one run for each state, and this value stays constant at about 41 percent when Barton successfully bunts a runner to second, and actually rises from 58 percent to 65 percent when he bunts a runner from second to third.

Indeed, Barton’s bunts are far more complicated than some commentators have made them out to be. As Mitchel Lichtman explained during the playoffs last year, when a few Yankees sacrifices left viewers baffled, we cannot simply analyze the before and after state of a “successful” sacrifice bunt. The range of possible outcomes includes the bunter reaching safely; the effect on the fielders should the batter choose to swing is also a factor. The A’s may actually know what they are doing here.

This post originally ran at Ball Your Base.

## Ichiro, Grounded

Ichiro Suzuki is a singular talent. He is fast, seeming to fly all over the outfield. He steals bases with great success — 45 while being caught only twice in 2006. He has a legendary cannon for a right arm. And he hits like a machine. He racked up over 2,000 hits in his first nine major league seasons, and was the second fastest to that milestone (to Al Simmons, who reached it in 12 fewer games). He does not hit many home runs or a particularly impressive number of doubles or triples. He piles up his hits by putting the ball on the ground and running to first base. Joe Posnanski recently explored Ichiro’s hitting prowess, coming to the conclusion that he is one of the few truly unique players in history.

What if Ichiro were slow? What type of player would he be if he were not able to knock out so many ground ball hits? For one possible answer to this question, I compared the rate at which Ichiro reached base on ground balls to the American League average. Baseball Reference lists batting average splits by hit trajectory, and I compiled the league numbers from 2003 through 2009. The league statistics for the first two years of Ichiro’s career, 2001 and 2002, differ significantly from the next seven, possibly due to different methods of categorizing ground balls. I omitted those two years, as well as this season’s small sample. During the seven seasons from 2003-2009, American League players consistently reached base at a .240-.245 average on grounders. Ichiro beat the average in every year, with a high of .368 on ground balls in 2007.

To get an idea of what type of player Ichiro would look like without all those extra hits, I normalized his ground ball hit rate to the league average for each season and recalculated his batting totals. This adjustment cost him 42 hits in 2007 and 44 in 2004, and no less than 14 in any of the seven seasons. For simplicity, I removed only singles from his batting line. I then searched for a player with career statistics similar to Ichiro’s adjusted totals and came up with an interesting candidate. The following table displays Ichiro’s statistics over the past seven years (again, discarding 2001 and 2002) without his extra ground ball hits, side by side with Curt Flood’s career averages.

 Adj. Ichiro Curt Flood Table: Curt Flood versus Adjusted IchiroStatistics Per 600 Plate Appearances Doubles 19 23 Triples 6 4 Home Runs 8 7 Walks 37 38 Strikeouts 56 53 Average .291 .293 OBP .338 .342 Slugging .391 .389 OPS .729 .732 BABIP .313 .314

This adjusted version of Ichiro is a near statistical clone of Flood, who played center field in the 1960s for the Cardinals. Flood was also a great fielder, winning gold gloves in each of his last seven full seasons. He is most famous, however, for starting a chain reaction that led to the free agency system when he refused a trade to the Phillies after the 1969 season. It marked the effective end of his career at just 31, as he played only 13 games in a comeback attempt in 1971. Despite now being inextricably linked with baseball labor history and not often mentioned for his playing ability, Flood was actually a surprisingly valuable hitter. He played in the offensively-challenged 1960s and was significantly above average with the bat for most of his career. Ichiro’s adjusted stats, in today’s era of power and on-base percentage, would be far less impressive.

Of course, this is all merely a thought experiment. Ichiro probably does have some control over where he hits the ball, as his New York Times profile explains. FanGraphs’s Jack Moore also explored Ichiro’s propensity to hit grounders to the opposite side of the infield at an abnormal rate. Thus, simply removing some of Ichiro’s hits does not show us the player he would actually be if he were not so fast. If he could not get on base so often on this type of batted ball, it is likely he would adjust his approach and that his numbers would reach a different equilibrium. What removing all of the extra singles does show us is just how much value those ground ball hits supply. Without them, Ichiro’s numbers look fairly pedestrian, especially in the era in which he has played. With them, Ichiro is Ichiro, and he will go down as one of the greatest and most dynamic hitters in baseball history.

## Saving Baseball’s Charm

Tom Verducci recently published a column lamenting the lack of contact in modern baseball. He cites rising walk and strikeout rates and lower numbers of balls in play as reasons the game is steadily losing an essential part of its charm. He makes some good points; it is immensely more enjoyable to watch Ichiro slap and run than to see Kevin Youkilis take a six-pitch walk without removing the bat from his shoulder. When my friends and I are watching a game, we refer to the walk as “the most boring play in baseball.” The pitcher misses his spot, and the hitter drops his bat and trots to first base. It is good for the team that is batting, but it is not fun to watch.

However, Verducci’s claim that walks and strikeouts have been on the rise for decades is only partially true. An article by Sky Andrecheck from the offseason demonstrates that walk rates have fluctuated over the past 30 years but have not shown a general upward trend. And while Verducci correctly points out that walks have risen for five straight years, they actually dropped every year during the first half of the decade and are no higher now than they were in the mid-1980s. Strikeouts have certainly climbed steadily, going from 12.5 percent of plate appearances in 1980 to about 18 percent today. As I described in my posts on high-strikeout players, the main ways to overcome a ton of whiffs are to walk a lot and to hit home runs. Walk rates have not changed a whole lot, so as the game has allowed in more high-strikeout players, home run hitting has increased to compensate. This increase is necessary to balance the negative effects of strikeouts, because players without power who strike out a lot cannot provide much value. However, while high-strikeout sluggers have been on the rise for a while, Verducci’s calls for changes to the game may be premature.

This type of play may just now be reaching its peak. As Moneyball explained, Billy Beane and the Athletics realized in the late-1990s that on-base percentage was vastly undervalued, and they set out stacking their team with flawed castoffs who were undesirable to other teams but could get on base. Today, a sort of boomerang effect is occurring. Teams such as the Athletics, Red Sox, and Mariners realized this past offseason that, as the rest of the league had caught up to the on-base bandwagon, it was the traditional baseball skills—speed and defense—that had now become undervalued. The Athletics and Mariners, in particular, set out acquiring these undervalued players, and both teams now find themselves with rosters full of excellent defenders who save runs with their gloves. Both teams also suffer from a severe lack of power.

Perhaps, as player valuation continues to evolve, the mix of skills in the pool of major league players will fluctuate and recalibrate around an equilibrium. Teams may value low-power speedsters more and more, until there is a better balance between fleet-footed defenders like Franklin Gutierrez and lead-footed sluggers like Adam Dunn. And as recalibration happens and players with speed and a lack of power become more prevalent, strikeouts and walks may begin to come down some.

Changes are not only happening on the position player side. Pitchers, too, have evolved in recent years. Velocity and the ability to miss bats have been highly valued commodities for decades, and as I detailed in my post on the fireballers of today’s game, great velocity often comes with great wildness. Many pitchers who can blow hitters away also have trouble throwing strikes. And as with walks and power, this skill set has become extremely expensive. Some teams, particularly the St. Louis Cardinals, are turning to a new formula to get maximum value from their pitchers: control and groundballs. Pitching coach Dave Duncan, as has been widely documented, has rescued careers by converting pitchers into strike-throwing groundball machines. Joel Pineiro is the most extreme example. Last year, as a 30-year-old journeyman, he posted the lowest strikeout rate of his career—105 in 214 innings pitched—while also putting up, by far, the best season of his career. He did this by walking almost nobody and keeping the ball on the ground, allowing very few home runs.

Pitching to contact is not a good strategy for players who allow a lot of fly balls. When batters put the ball in the air, a good number will leave the park. This is especially true in an era when shortstops can slug 40 home runs. Thus, fly ball pitchers must strike batters out, limiting those balls in play, to succeed. Groundball pitchers prevent hitters from lofting the ball, minimizing the threat of the home run. They can afford to let the batter put wood on the ball and count on the infielders to make outs. Many ground balls get through for singles, so to be successful with this strategy pitchers must hold down walks to limit the number of baserunners. With this formula, Tim Hudson and Derek Lowe have had many years of success despite below-average strikeout rates. Pineiro and now Brad Penny are veterans that have recently converted, and young groundballers like Doug Fister of the Mariners and Nick Blackburn of the Twins are carving out spaces for themselves in the majors with miniscule strikeout numbers.

While it is certainly true that hitters are putting balls in play at historically low rates, it is not entirely clear what the exact causes are. It may be that batters are better trained to work the count and wait for good pitches to drive, and that they consequently strike out more. Teams may be selecting for these skills more vigorously. It may be that lineups with power from top to bottom have forced pitchers to move to the edges of the zone, limiting their ability to keep walks down. Whatever the reasons, it also is not clear that current trends will continue. Verducci mentions potential tweaks to the game, such as expanding the upper limits of the strike zone, but changes are likely to have unintended consequences. Enlarging the strike zone, for example, might not actually increase the number of balls in play.

Perhaps before changing the game, MLB’s bosses should consider the latest developments in player evaluation and wait to see whether the game is changing itself. For hitters, walks and power are here to stay, and for pitchers, velocity and whiff-inducing stuff will always be prized traits. But the mix of skills may be shifting as teams learn to better quantify all of the ways they can score and save runs. Perhaps recent trends will be counterbalanced as teams copy the money-saving measures of innovative teams—the Athletics and Mariners with their light-hitting fielders and the Cardinals with their groundballers. While balls in play may be at an all time low, one thing we can be sure of is that the game will continue to evolve, with or without drastic action by the people in charge.