Building on Youth

I hate comparisons in sports. Not all comparisons, mind you, as it’s fun to compare players across eras and such. I just don’t like comparing teams. It always suggests to me that a team can’t be their own selves and have their own identity. Of course, every team is unique and you can’t say one team is the same as another. Making such comparisons always seems to restrain a team to being like another team. I just don’t like it.

So, logically, I’m going to make a loose comparison between teams.

There have been seemingly infinite mentions of the Royals average age this season. According to Baseball-Reference, their average age was 26.04 years in 2011, which incorporates every player that’s been with the team this season. The next closest team was the Cleveland Indians, who checked in at 27.28 years of age. If it wasn’t clear by the players on the field, this is a team full of youth. And those young players gained their experience in preparation for their next season as Kansas City fans hope to see an extreme change in results.

But what does that really mean? Is youth an indicator of the right direction? What does history tell us about the progress of young teams? As you might have guessed, I’m about to give it a look.

Let’s get some perspective first. The Royals, while young, aren’t even close to the youngest team since 1960. Why that time span? Honestly, dragging it out longer is quite a bit of data and this range (51 seasons) seems to give reasonable data. Anyway, the 2011 Royals are the 43rd-youngest team since ’60, according to Baseball-Reference’s ages. They are, however, the youngest team since the 2006 Marlins (25.70 years), so they’re in good recent ground. And although 43rd-youngest doesn’t sound like much, that’s out of 1342 samples. So, yes, they are quite young.*

*Oddly enough, three of the twelve youngest teams were from Kansas City: 1966/67 Athletics and 1969 Royals.

Since there are 210 instances of teams with average ages under 27, there’s a good group to work from as far as progression from season to season. To make it easier to read the data and to interpret, I’m just going to show you some results from the AL, in which the Royals are the 21st-youngest since 1960. If you want more data from both leagues, let me know in the comments and I can work on it.

Basically, what I want to see is what this youth means for the Royals future success. And since 2013/14 is the widely-accepted starting range for true playoff contention, that’s what I’ll look to. So, I took general data for all current franchises from 1960 through 2011 and used it to make a group of scatter plots based on the data. Here’s an example so you understand what I’m working with (Royals seasons highlighted in blue):

So, yeah, it’s sort of all over the place. The line you see attempts to assign a trend to the scatter, which is semi-visible to the naked eye. And the equation in the bottom left describes the trend line. For those that don’t enjoy stats, the “R-squared value” describes how the trend line fits the data. A line of perfectly-aligned points would yield an R-squared of one. As you can see, the fit here is considerably less than one. This just means we have to keep in mind that it’s a very loose interpretation of the data.

Rather than giving you a bunch of dense plots, I’m going to give you simply the trend lines and then elaborate on what each set of trend lines means for the Royals moving forward. It’ll give us a starting point from which to work.

First, average age versus win percentage from the year of age measurement (Year 0) to the third year following (Year 3):

Second, average age versus run differential for the same range (Year 0 to Year 3):

Now, before you start thinking that the line angle change absolutely means something, let me make a point. The R-squared value decreases with each year forward, meaning that we can’t lean on it as concrete information. Since the values in Year 0 are around 0.13, all of this has to be taken with a few of the atoms composing a grain of salt.

Still, the data is interesting. If you have a team with an average age of about 20.5, your winning percentage would be roughly 0.35 on average. A few years later, that winning percentage rises to about 0.49. On the other hand, if your team has an average age over 29, it’s more likely that your number of wins will decrease in the years following.

We can look at run differential the same way. In you have a run differential of about -225 with an average age of 20.5, it will, on average, climb to about -20 within a few years. Like winning percentage, for those teams with an average age over 29, their success will decrease based on past results.

Of course, as I said, this is all fuzzy and doesn’t necessarily imply anything. It’s simply interesting to note that a very rough trend exists in the data that seems to suggest improvement of a young team over the following few years.

Well, that’s all well and good. It’s really interesting to note how much that can influence the future. However, I really wanted to get a bit further than just the numbers and see some examples. So, I took the 10 AL team seasons ranked immediately above and below the 2011 Royals in terms of average age and looked at the results in the following three (and in one case, four) years, giving 20 example seasons. I’ll divide them up into the good implications, the bad, and the so-so to get a feel for what we’re dealing with. I’m going to focus more on the good teams to see what the teams did that made them succeed and what players were involved in that success. The full descriptions of those teams are on the following page. Feel free to skip that page and go to the next to get the summary of what those teams’ futures suggested to me.