One of the challenges in trying to have a general, but meaningful discussion of bunting by the St. Louis Cardinals – or any other Major League Baseball team for that matter – is a lack of good data. While play-by-play detail from every game exists, how might that huge volume of raw data be mined for this specific information?
I asked researcher Tom Orf that question, and is seemingly always the case, he was up for the challenge. Tom extracted all 1,731 bunt plays by the Cardinals since the opening of the 2000 season and summarized them by year.
This data is not the be-all, end-all. It is sourced from all plays that mention “bunt” in the play description. For example, if a player had to switch off from the bunt because he was unable to get it down, it would not be included.
The key columns are highlighted. They are PA (plate appearances), AB (at-bats) and SH (sacrifice hits or more appropriately, sacrifice bunts). Because of the goose eggs in several other columns, a simple formula can be used: PA = AB + SH, where AB is not a sacrifice bunt and SH is a successful sacrifice bunt, advancing the runner(s) on base.
I then created a new column, which I called SH/PA. That is the rate of successful sacrifice bunts per bunting plate appearance.
Though I may have implied above that AB represents unsuccessful bunts, that is not entirely the case. In fact, along with the outs that did not result in the runner(s) advancing, those at-bats include the cases in which the batter bunted for a base hit. That is reflected in the standard BA/OBP/SLG/OPS columns. Obviously, not making an out while bunting is even better than a productive out made in advancing the runner(s).
So, in my thinking, a quick way to gauge bunting success is to add the number of bunts for hits (H) to the number of successful sacrifice bunts (SH) and dividing that by the number of bunting plate appearances (PA). That is the far right column I called “Positive outcome”.
I split the summary data into two sections, the La Russa (2000-2011) and Matheny (2012-2013) years. I did that to provide a comparison since the new skipper has come under criticism from some for his bunt deployment.
St. Louis Cardinals, bunting, 2000 through April 18, 2013
|La Russa||G||PA||R||AB||H||2B||3B||HR||RBI||BB||IBB||SO||HBP||SH||SF||ROE||GDP||BA||OBP||SLG||OPS||SH/PA||Pos outcome|
A few things jumped out at me.
Note the sheer number of bunt attempts by Matheny’s hitters, 119, in his first season. That is 14 less than La Russa’s teams averaged during his final 12 years at the helm of the Cardinals.
However, there was a major spike that elevated TLR’s average. During the 2001-2003 years, his clubs averaged a whopping 166 bunt attempts per season.
Over his final six seasons, La Russa’s teams averaged 118 bunt attempts per season. In other words, that is almost identical to Matheny’s 119 in 2012.
Look at the number of games in which bunts were attempted. La Russa’s teams averaged bunts in 90 contests each season, or about 56 percent of the games. In 2012, Matheny called bunts in just 82 games, barely half of the total.
Bunting seems to be clustered. In the games which they attempted any bunts, the Cardinals have averaged just under 1.5 bunts per game.
In terms of bunting for base hits, La Russa’s 2000-2004 clubs were amazingly proficient, ranging from a batting average of .345 to .489 in those situations during that five-year period.
That took a dramatic downturn in recent years, however. It is worth noting that Matheny’s 2012 club’s .240 batting average while bunting is higher than that of three of La Russa’s last four clubs (2008-2011).
Looking at the SH/PA numbers suggests the years when the batting average for bunt hits is higher, the success rate in sacrificing was a bit lower. That is not particularly surprising to me.
Putting it all together, Matheny’s “Positive outcome” bunting rate of .681 last season (or 68.1 percent of the time) is below La Russa’s average of 71.4 percent from 2000 through 2011.
In only two of those 12 years did TLR’s clubs come in below 68.1 percent. However, those were both in recent seasons, 2008 and 2010.
Of course, this summary data just scratches the surface. Some of my follow on questions include:
– When was the bunt called – in terms of number of outs, inning and score?
Now, one might argue that not bunting at all (not giving up an out) and having the batter hit away could offer a greater chance of success. In order to understand that, one would want to know who the batters were. After all, a pitcher, for example, is going to have a lower batting average than most all position players.
– Who bunted – pitchers versus position players and how did their success vary?
Then, it might lead to wanting to know who bunted the most often and was best at it. Perhaps the recent downturn in results is personnel-related?
– Who were the most frequent and best bunters?
Answering these and other questions may require manipulation of a 1,700-plus line spreadsheet, so it could take considerable time and effort.
Still, do you have other bunting-related questions? Let’s discuss this below as I am learning as I go. Thank you for reading and hopefully commenting.
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