The movie and especially the book Moneyball details how the Oakland Athletics (A’s) helped pioneer the use of statistical data in making player decisions, from which players to acquire to who to play in the field on a daily basis. Their reason for doing it was primarily financial, i.e., they didn’t have the same kind of money to spend on well-known high-performers in order to compete so they had to look for the “hidden gems” – under-valued players who would deliver results while costing less.

The A’s had some very smart people (including a Harvard business grad) who wrote computer programs to help them parse through the mountains of data on every player in the league to find the ones who best fit the system they planned to use while still being within their price range. So you might think, well, ok for them but I don’t have those types of resources so what good does knowing all that do me?

In reality, though, most coaches today do have a lot of that type of information at their fingertips, at least about their own players. It’s contained within the GameChanger (or similar) apps the coaching staff or parents use to score and share game results with those who can’t be there.

On the home page for the team, the very last tab is labeled Stats. If you as a coach click on it you’ll see the cumulative statistics for all the games in hitting, pitching, and fielding.

Now, I understand that the stats aren’t always accurate since some people will score every ball that’s hit and gets someone on base a hit, even if an error was involved. But if you really want to take advantage of the value of stats, coaches, you can quickly train whoever is using on how to keep score properly so you can rely on the data that’s there.

The National Fastpitch Coaches Association also has online courses available for $9.99 that can teach this skill.

So how can having and using accurate statistical data help you as coaches win more games? Here’s an example, drawn from an actual team that apparently isn’t using the data at their disposal.

We will look at the hitting statistics for seven batters. We’ll just call them Player A, Player B, Player C, etc. We’ll look at batting average (BA), on-base percentage (OBP, which is how often they get on base through hits, walks, or hit by pitch), slugging percentage (SLG, the average number of bases a hitter gets each at-bat), and on base plus slugging (OPS, the sum of the on-base percentage plus slugging, which is a great measure of total productivity of the hitter).

Here are those stats for our seven players. The players are currently presented in a random order:

Player	BA	OBP	SLG	OPS
A	.222	.333	.278	.611
B	.167	.250	.167	.417
C	.462	.562	.538	1.101
D	.286	.400	.429	.829
E	.278	.381	.333	.714
F	.200	.294	.200	.494
G	.250	.429	.312	.741

Ok, based on those numbers and a general understanding of how to put a lineup together (which I covered a couple of posts ago), how would you structure your batting order? Take a few moments to write it on a piece of paper without looking below; I’ll wait.

Let’s see how what you did compares to the actual lineup that was used when I pulled these stats. If you’re using a traditional lineup, it would probably look something like this:

• Player D
• Player E
• Player C
• Player G
• Player F
• Player A
• Player B

If you’re using a more modern approach that says put your best bats at the top so they come to bat more often, the lineup would probably look like this:

• Player C
• Player D
• Player E
• Player G
• Player A
• Player F
• Player B

Ok, now here’s what the actual lineup is:

• Player D
• Player A
• Player E
• Player G
• Player B
• Player F
• Player C

Do you see a problem here? The player with by far the highest batting average, on base percentage, slugging percentage, and on base + slugging (Player C) is hitting seventh, where she likely will get one at-bat per game, or two at most if the players ahead of her hit above their averages. In the meantime, Player B whose stats can only be called anemic at-best is hitting in the five slot, and Player A whose hitting line isn’t a whole lot better is in the two slot.

Is it any wonder that this team is struggling to score runs, much less win games?

Why would the lineup be structured this way? I can only guess, but that guess is the coach is relying on his “gut” or long-solidified impressions of who his top hitters are rather than taking the time to look at which players are actually producing statistically, game after game.

(It could also just be plain old playing favorites, but hopefully that’s not the case.)

If you want to win games you can’t and shouldn’t rely on your “gut” anymore. It’s like the the old scout thinking mentioned in Moneyball that so-and-so “looks like a ballplayer.”

That type of thinking is a dead end, whether you’re looking at the pro, collegiate, or youth level. You need instead to look at what is actually happening on the field, in the game, to determine which lineup is going to produce the most runs, which is a major key to winning ballgames.

The same is true for pitching and fielding too. You may think Pitcher A is your Ace, but if you look at the cold, hard stats you may find that Pitcher B does a better job of getting outs without giving up runs.

You may think Fielder A is your best bet at shortstop, but the stats could tell you Fielder B makes fewer errors while contributing to more “caught stealing” outs on throws from the same catcher.

All this information is there for you to use. All you have to do is click on it now and then to look at it.

Your eyes and your guts can lie. Statistics, if they’re properly kept, don’t.

Use the data you have to make better decisions and you’re likely to find you win more games. Or at least can justify your decisions should anyone ask, which in this day and age is a nice thing to have in your back pocket.

Statistics photo by Burak The Weekender on Pexels.com