Explanation of Sabermetrics - Power Hitting

(NOTE: I realize a small error in my queries, so some of the numbers I had posted were incorrect. I fixed the error and corrected the numbers, but there was little difference in the results.)

Ask almost any sabermetrician what the most difficult facet of baseball to predict is. You will hear one answer from almost every single one: season to season pitcher performance. While I will certainly agree that this is a very difficult thing to predict, I have found trouble in predicting something else, something from the other side of home plate: power hitting.

While contact hitting remains fairly constant over the years, a hitter's ability to hit for power is always fluctuating. Younger guys are developing power, older guys are losing power. Contact hitting is much more basic. Either you are a good contact hitter or you are not. Sure, you can change your swing or learn more about it as you mature, but overall the ability to hit for contact is fairly linear. A poor contact hitter one year isn't going to become a good one the next. But a player who is a poor power hitter can become a good one the next year, which is what makes power hitting such an interesting - and difficult to study - topic.

So how do you predict power, and why is it so difficult? The most basic way is to use Doubles, Triples, or a combination of the two. The thinking behind this is that as a player matures and gets stronger, these Extra Base Hits will have enough power behind them to clear the fence instead of staying in the yard for a multi-bagger. I tested this theory among players with at least 200 At-Bats in 2004, 2005, and 2006. 73 of these players increase their AB/2B from 2004 to 2005 by more than 1.5 points. From 2005 to 2006, just 27 of these players increased their AB/HR. That’s just 37%. If 2Bs are supposed to predict power, why were they only successful 37% of the time?

Doubles and Triples, I believe, are not the best source for power prediction. Approximately 14% of all doubles are groundballs, and as we know groundballs can never be converted into a home run. Doubles are especially tricky when looking at hitters who have some speed. They may hit a line drive or a bloop into the shallow part of the outfield that would be a single for slow batters, but because of their speed are able to turn it into a double. This is nice to be able to do, but it has nothing to do with potential future home run power. Or, these same players may actually hit a ball well, but because of their speed turn their double into a triple.

This begs two questions. One, what if we exclude fast players from our sample? I took out any player who had 20 or more steals in any of the 3 years, and the percentage actually decreased to 35%.

The second question is why don’t we include triples? Well, because triples are even more flawed than doubles are. Triples are almost the sole property of fast players. Slower players will very rarely hit a triple and will almost never hit more several in a season. Again though, why not include them? They just seem to be an extension of doubles for fast players. The problem is that 42% of triples are groundballs, usually hit down the first base line and into the corner in right field so that the fast runner has a chance to make it to third. This has nothing to do with the type of power we are talking about.

If we do include 3Bs and exclude fast players, we get 59 players increasing their AB/(2B+3B) from 2004 to 2005 and 19 increasing their AB/HR from 2005 to 2006. That's about 32%.

If the flaws with doubles and triples aren't enough to persuade you, there is a whole other category of hits that prove troublesome that you won't be able to find in any box score or stat sheet. Thus far I have ignored the most important condition of a double... that it is a ball in play. Balls in play are never to be entirely trusted because once they are put in play, they are out of the control of the pitcher and the batter and put into the hands of luck and defense, a sabermetrician's biggest adversary. There are plenty of well-hit balls that do not fall for hits because of bad luck or amazing defense. On the flip-side of the coin, there are plenty of balls that fall for hits that don't deserve to because of that slow, injury-ridden left fielder that happened to be playing at the time the ball was put into play. Essentially, because doubles and triples are balls in play, they will never be capable of being fully trusted.

So basically, a plethora of stats seem to be either flawed or meaningless that were otherwise thought to be useful… some even considered to be "sabermetric" in nature. Here is a list of a few common ones:

• Doubles
• Triples
• Total Bases
• Slugging Percentage
• Isolated Power
• On-Base Plus Slugging Percentage (OPS)
• Secondary Average

Now I realize I have done a good job bashing doubles and triples, but the fact remains: they are our only guide to go on for predicting power. So how should we go about prediciting power if 2Bs and 3Bs aren’t very accurate? The answer to that, right now, is that we can't - at least with the primitive stats that we have to work with. With access to batted ball data for every player, we would be able to set parameters for what is considered a well-hit ball, add up all of these for each player, and defining power could conceivably be quite easy from there. This seems to be the only sure-fire way to see who the players who have a true chance of developing - or losing - power are.

Hit Tracker is a service that seems to have realized exactly what I am talking about. Last year they tracked every home run hit by every player and, using physical science, determined each Home Run’s “True Distance,” in addition to a number of other bits of information about the hit. We use this data to determine our “True Home Run” stat. We take each home run’s true distance and the location where it went over the fence and place it into a theoretical, Average MLB Ballpark. From there, we can determine how many would have actually gone out in this ballpark and which wouldn’t have.

The problem with this is that only Home Runs are included by Hit Tracker. To get a true sense of a hitter’s power, we’d need this data on all airballs, not just the ones to clear the fence. What about the ones that should have but didn’t? Hit Tracker will be correcting this in 2007 by tracking all airballs, but unless they do this for past years, it may be a while before we can develop a very accurate power prediction system.

Explanation of Sabermetrics - Contact Hitting and On-Base Skills

Continuing my explanation of Sabermetrics principles and stats, we move on to the hitting side of the coin. Bill James defined Sabermetrics as "the search for objective knowledge about baseball." James is considered to be the pioneer of Sabermetrics, beginning to publish his work in the 1970s. It wasn't until recently - with the publication of Michael Lewis's #1 National Bestseller Moneyball - that Sabermetrics have become more mainstream.

Contact Hitting
While almost all sabermetricians agree hitting is more easy to predict than pitching, oddly enough I find hitting stats to be more flawed than pitching stats. This is pitching stats are limited and are more easily influenced by luck; they are more volatile. Hitters have more control over what happens to a ball once it is put in play, but stats that explain exactly what happens aren't readily available. So we do the best we can.

Ron Shandler, a genius when it comes to baseball, said that the mark of a true .300 hitter is a Contact Rate of at least 86% and a Walk Rate of at least 11%. We find that these stats certainly help a hitter, but we think there is a little more to it than that.

Contact is Good

The more balls your put in play, the more can fall for hits.

Strikeouts can kill a batting average
When you put a ball in play, there is always a chance it can fall for a hit. When you strikeout, there is no opportunity for this. The more you strikeout, the more it hurts your batting average. This directly correlates with Contact Percentage.

Not All Contact is Created Equal
There are varying degrees of how well a player hits the ball. How hard it is hit and at what precise angle and to what particular part of the field all play a part. But these stats aren't available in the quantities needed, so we have to generalize a bit. Line Drives fall for hits 74% of the time, on average. Therefore hitters with high Line Drive Percentages help their bid for a .300 average.

Walks measure selectivity
Ron Shandler uses walks to measure a hitter's selectivity. The theory is that the more walks a player takes, the less poor pitches he will actually swing at, making the ones he does swing at better pitches and more likely to fall for a hit once put into play. We at the Saberoticians are currently studying the types of pitches players see (swinging strikes, called strikes, balls, foul balls, etc.) and its relationship with selectivity and contact hitting. This will be incorporated in our 2008 projections.

Home Runs make up for Ks a little
Home Runs are always hits. The more Home Runs you hit, the more 'free hits' you get added to your batting average. Most power hitters trade Ks for HRs, which is a good trade as a complete player, but not as a contact hitter. We use True Flyball HRs (explained later) because we don't want to count Line Drive HRs twice (once as LDs and once as HRs).

Some players can make due with their speed
Speed players often contradict sabermetrics because speed is difficult to record in stat form. For contact purposes, we use Infield Hit Percentage. Players who get a high amount of Infield Hits are ones who use their speed to beat out groundballs. This also has a positive effect on batting average.

Putting all of these factors together, we get a somewhat crude, but complete sense of a player's contact hitting skill, which is exactly what we call our stat: Contact Hitting Skill. We then put it on a traditional batting average scale for easier understanding. When we predict a player's batting average, it is based on this.

On-Base Skills
This is very straight-forward once you understand the contact hitting concepts. All we do is take those and add in walks to get our Defense Independent On-Base Percentage stat. We put this on the traditional On-Base Percentage scale to make it easier to understand. As described in Moneyball, on-base ability is one of the most important skills in all of baseball.

Sources:
Batted ball data came from, as always, The Hardball Times.

Explanation of Sabermetrics - DIPS Theory

Since many of you reading this may not know much about Sabermetrics, I've decided to go over some of the basic principles so that you can better trust what we're saying. We'll start with DIPS Theory (Defense Independent Pitching Statistics). We'll look at hitting theories later today.

Pitching
Voros McCracken is thought of as the pioneer for Sabermetric Pitching Principles. It is now understood in the Sabermetric community that pitchers have little-to-no control over what happens to a ball once it is put in play. Due to this, strikeouts are the best outcome a pitcher can hope for as there is no opportunity for him to get unlucky, as he could get if the ball gets put in play.

Walks are another important stat for pitchers as they are also defense independent. Obviously, walks are a negative event for pitchers.

Home Runs were once thought of as a defense and luck independent outcome, but now there are some who think they are not luck independent. We agree. Too many conditions, such as differing outfield fence distances, wind factors, and other atmospheric conditions make it impossible to compare HR rates between two pitchers. Some pitchers also draw the unlucky assignment of facing the wrong hitter at the wrong time, and that hitter decides to hit a home run. Due to these factors, in our stats we don't use actual Home Runs rates. We calculate the rate at which Outfield Flyballs and Line Drives turn into Home Runs and then apply this rate to each pitchers Flyball + Line Drive Rate to get an 'Expected Home Run' total.

For a while this is where DIPS stopped. But now there are many sabermetricians who include all batted ball data in pitcher analysis. The infield flyball (or popup) is the most efficient as it almost never turns into a hit - just 3% of the time.

The groundball is the second most efficient as it never turns into a home run, despite being turned into an out at a slightly worse rate than flyballs (72%). It also has the added bonus of being turned into a double play at times.

Flyballs are the second worst outcome. While they turn into outs 75% of the time, they turn into home runs 12% of the time. Line Drives are the worst for pitchers because they turn into outs just 26% of the time. Because it is often difficult to tell which hits are flyballs and which are line drives, those who record these stats are making a subjective opinion on which are which. For this reason, we combine line drives and flyballs into one stat (airballs) in our pitching formulas.

And that's the basis of DIPS Theory. We use a complex formula using all of these factors to determine a pitcher's effectiveness.

Sources:
Batted ball percentages were found at The Hardball Times.

Coming Tomorrow...

A brief intermission from our Mets Analysis.

I realized today that some people reading this may be interested in improving their fantasy baseball team, but may not know the first thing about Sabermetrics. Tomorrow I will post a little bit about Sabermetrics and the types of theories people have developed about the game of baseball so that these people will understand what it is I'm talking about and be better able to trust it.

After saying that, we will get back to some more Mets analysis.