Put-in-Play Percentage: A “Great Metric” for Youth Baseball?
By Tim Wilson on in Metrics with 2 Comments
My posts have gotten pretty sporadic (…again, sadly), and I’ll once again play the “lotta’ stuff goin’ on” card. Fortunately, it’s mostly fun stuff, but it does mean I’ve got a couple of posts written in my head that haven’t yet gotten digitized and up on the interweb. This post is one of them.
As I wrote about in my last post, I’ve recently rolled out the first version of a youth baseball scoring system that includes both a scoresheet for at-the-game scoring, as well as a companion spreadsheet that will automatically generate a number of individual and team statistics using the data from the scoresheets. The whole system came about because I’ve been scoring for my 10-year-old’s baseball team, and I was looking for a way to efficiently generate basic baseball statistics for the players and the team over the course of the season.
The Birth of a New Baseball Statistic
After sending the coach updated stats after a couple of games mid-season, he posed this question:
Do we have any offensive stats on putting the ball in play? I’m curious to know which, if any, of the kids are connecting with the ball better than their hit stats would suggest. That way I can work with them on power hitting.
How could I resist? I mulled the question over for a bit and then came up with a statistic I dubbed the “Put-in-Play Percentage,” or PIP. The formula is pretty simple:
Now, of all the sports that track player stats, baseball is at the top of the list: sabermetrics is a term coined solely to describe the practice of studying baseball statistics, Moneyball was a best-selling book, and major league baseball itself is fundamentally evolving to increase teams’ focus on statistics (including some pretty crazy ones — I’ve written about that before). So, how on earth could I be coming up with a new metric (and a simple one at that) that could have any value?
The answer: because this metric is specifically geared towards youth baseball.
More on that in a bit.
Blog Reader Timesaver Quiz
Question: In baseball, if a batter hits the ball, it gets fielded by the second baseman, and he throws the ball to first base and gets the batter out, did the batter get a hit?
If you answered, “Of course not!” then skip to the next section in this post. Otherwise, read on.
One of the quirks of baseball — and there are many adults as well as 10-year-olds on my son’s team who don’t understand this — is that a hit is only a hit if:
- The player actually reaches first base safely, and
- He doesn’t reach first base because a player on the other team screwed up (an error)
“Batting average” — one of the most sacred baseball statistics — is, basically, seeing what percentage of the time the player gets a hit (there’s more to it than that — if the player is walked, gets hit by a pitch, or sacrifices, the play doesn’t factor into the batting average equation…but this isn’t a post to define the ins and outs of batting average).
PIP vs. Batting Average
Batting average is a useful statistic, even with young players. But, as my son’s coach’s question alluded to, at this age, there are fundamentally two types of batters when it comes to a low batting average:
- Players who struggle to make the split-second decision as to whether a ball is hittable or not — they strike out a lot because they pretty much just guess at when to swing
- Players who pick good pitches to swing at…but who still lack some of the fundamental mechanics and timing of a good baseball swing — they’ll strike out some, but they’ll also hit a lot of soft grounders just because they don’t make good contact
(Side note: I’m actually one of the rare breed of people who fall into BOTH categories. That’s why I sit behind home plate and score the game…)
What the coach was looking for was some objective evidence to try to differentiate between these two types of players so that he could work with them differently. Just from observation, he knew a handful of players that fell heavily into one category or the other, but the question was whether I could provide quantitative evidence to confirm his observations and help him identify other players on the team who were more on the cusp.
And, that’s what the metric does. Excluding walks, hit by pitches, and sacrifices (just as a batting average calculation does), this statistic credits a player for, basically, not striking out.
But Is It a Great Metric?
Due to one of those “lotta’ things goin’ on” projects I referenced at the beginning of this post, I had an occasion to revisit one of my favorite Avinash Kaushik posts last week, in which he listed four attributes of a great metric. How does PIP stand up to them? Let’s see!
|Attribute||Summary (Mine)||How Does PIP Do?|
|Uncomplex||The metric needs to be easily understandable — what it is and how it works||PIP works pretty well here. While it requires some basic understanding of baseball statistics — and that PIP is a derivation of batting average (as is on-base percentage, for that matter) — it is simply calculated and easy to explain|
|Relevant||The metric needs to be tailored to the specific strategy and objectives they are serving||This is actually why PIP isn’t a major league baseball stat — the coach’s primary objective in youth baseball is (or should be) to teach the players the fundamentals of the game (and to enjoy the game); at the professional level, the coach’s primary objective is to win as many games as possible. PIP is geared towards youth player skill development.|
|Timely||Metrics need to be provided in a timely fashion so decision-makers can make timely decisions||The metric is simple to calculate and can be updated immediately after a game. It takes me ~10 minutes to enter the data from my scorecard into my spreadsheet and generate updated statistics to send to the coach|
|“Instantly Useful”||The metric must be able to be quickly understood so that insights can be found as soon as it is looked at||PIP met this criteria — because it met the three criteria above, the coach was able to put the information to use at the very next practice.|
I’d call it a good metric on that front!
But…Did It Really Work?
As it turned out, over the course of the next two games after I first provided the coach with PIP data, 9 of the 11 players improved their season batting average. Clearly, PIP can’t entirely claim credit for that. The two teams we played were on the weaker end of the spectrum, and balls just seemed to drop a little better for us. But, I like to think it helped!