While scrolling on social media, I noticed that there seems to be a lot of opinions swirling around about baseball statistics. Some people like to completely write off advanced statistics, opting for a very traditionalist view of the sport.
This advanced analytics movement has been seen as being harmful to the game, and makes the game more about numbers on a computer than results. This can be true, but to an extremely limited degree. While there are some modern trends that I think do fit this type of thinking, these advanced metrics and analytics give us a greater understanding of what’s happening on the field, and can be used to predict future outcomes.
Today, I want to take a look at a number of baseball statistics, and rank them based on how useful they are in scoring runs, preventing runs, and winning games. There will be five grades I will choose from to rank each statistic: vital, important, neutral, non-essential, and useless. With each grade, I will also give an explanation to hopefully shed some light on the vast world of baseball statistics.
So, let’s take a look at what statistics stand the test of time, which you should allow to change your perspective on the sport, and which should be entirely fazed out of the game.
Batting Average: Non-essential
This one will be very controversial. For as long as the game has existed, batting average has been the measuring stick in separating good hitters from bad hitters. The reason is simple, if you get a lot of hits, you’re getting on base and batting in more runs.
However, batting average is inherently flawed for one reason: all hits are measured equally. In judging the quality of batters against one another, batting average would have you believe that someone hitting 10 home runs in 20 at bats is the same as hitting 10 singles in 20 at bats.
Is 10/20 phenomenal any way you look at it? Absolutely. But batting average merely reflects the success of more consequential batting measurables. Let me illustrate this by examining some other batting statistics.
On Base Percentage (OBP): Important
As the 2012 movie “Moneyball†states, “He gets on base a lot, do I care if it’s a walk or a hit?†On base percentage gives us a more accurate picture of how much value a batter brings to the team.
It’s not overly complicated, if a player gets on base, he is helping the team score runs. Whether he gets a hit, a walk, or gets hit by the pitch, getting on base is what leads to runs.
Although it’s more substantial for grading how players set themselves up to score runs, on-base percentage can’t be considered vital because it does fall victim to the same thing that batting average does: home runs are as valuable as walks. This is obviously not the case.
Walks score runs, but not in as efficient of a manner as extra base hits. In both cases, a player has at least a chance to score a run, but only one completely guarantees it. Sure it is better to get on base at a high percentage, but hitting for power is what helps teams score runs.
So on base percentage is an advanced look at batting average, giving us the most efficient look on how much a player gets on base, but not necessarily scoring runs. There is one scenario where on base percentage is vital, however: the top of the order.
Yes it’s great to hit three home runs at the top of the lineup, but a far more achievable scenario is a pair of walks and then a home run. This is where on base percentage becomes so important. It doesn’t matter how many bases you get, if you can get on base with less than 2 outs, it gives the team a much easier chance of scoring runs.
So if batting average is outdated, and on base percentage is only situationally important, then what measurement gives us the best look across all scenarios for all hitters?
On Base Plus Slugging (OPS): Vital
OPS gives us the best indication of how good a batter is. It takes a player’s on base percentage, a measure of how efficient a player is at setting up runs to be scored, and mixes it with slugging percentage, an altered version of the batting average statistic that differentiates the amount of bases earned on a single hit. When added together, OPS gives you the total picture of how valuable a batter is at scoring runs and thus winning games.
There are many ways in which OPS can illustrate different batting outputs. A player with a good on-base percentage but below average slugging is going to be reflected as an average hitter. Same thing if a player has a good slugging, but struggles to get on base. Either a player gets on base less with better volume, or more often with less volume.
The beauty of this stat is that the cream still rises to the top. The best batters both get on base a lot and are able to get extra base hits quite frequently. These results will be reflected with a high on base percentage, a high slugging percentage, and in turn a high OPS.
Runs Batted In (RBI): Useless
That brings me to another controversial take: RBI’s are not an effective way of measuring batter success. Sure they are essential to winning games, but in measuring individual player performances, they don’t paint a good picture in isolation.
This is because RBI’s are really a measure of team success. Whether or not a player bats well, he can’t ensure that his teammates will set him up to secure RBI’s. A player can bat extremely well but not rack up RBI’s simply because he teammates are batting poorly. In vice versa, a player can groundout and score an RBI simply because a teammate did the heavy lifting to put themselves in scoring position.
Now this isn’t to say playing team baseball isn’t important. Sacrifice flies and bunts are extremely crucial, as they trade less valuable outs for extremely valuable runs. However, sac flies and bunts don’t count as at-bats, and therefore, they don’t count towards on base percentage or OPS.
RBI’s are completely a team statistic. It allows bad batters that produce bad outcomes to be more valuable than good batters that reach base more effectively.
Weighted Runs Created Plus (wRC+): Vital
This will be our first dip into advanced statistics. I will spare you the grand details that lead to the calculation of wRC+, but it essentially replaces the arbitrary RBI statistic.
What wRC does is measure a player’s batting quality against the rest of the league. This creates a more predictive stat, since it doesn’t measure any actual tangible runs and RBI’s. Rather, it shows how valuable each player is at scoring runs for the team in equal RBI opportunities. It takes out the reliance of teammates to get in scoring position which hinders the effectiveness of the RBI statistic.
Where the “plus†comes in is quite simple. It takes a player’s total weighted runs created, and once again compares them league-wide by providing a number that is easier to conceptualize. On this scale, 100 is league average, so a player with a 90 wRC+ is 10 percent worse at creating runs than the league average.
There are many statistics that use the “plus†in order to simplify numbers as well as compare players across generations who may have produced the same numbers in more difficult eras to score runs. OPS itself can be figured into OPS+ for this exact reason.
Pitching Record: Useless
Moving to pitching statistics, a pitcher’s tally of wins to losses is once again arbitrary and useless. Just like RBI’s, wins are largely out of the control of the pitcher. A pitcher can hypothetically pitch an entire game, allow just one run and lose the game.
Pitching record is therefore another measure of team success. It doesn’t give us any greater of an understanding of how good a pitcher is in a vacuum.
Earned Run Average (ERA): Neutral
ERA is a tough one to examine for one simple reason: what do we consider a hit versus an error in baseball? A lot of well hit balls are turned into outs for the pitcher thanks to stellar defense. Poorly hit balls can create base runners because of poor defense. All the while, there is no exact science on what is a hit and what is an error.
Whether or not a player reaching base is considered a hit or an error is completely up to the score keeper. There are general rules in deciphering between the two, but no exact science. This leaves an unclear picture of whether a pitcher is responsible for hits allowed, and ultimately runs allowed.
What gives this statistic merit is the fact that pitchers do retain a lot of control in every scenario. Even if a pitcher gives up three straight singles, he can still strike out three straight batters without having to rely on any defense. Conversely, he can also pitch in a way that puts the ball in play, but in a fashion that allows the defense to get outs and prevent runs.
ERA is as good of a measuring stick for on field results as we currently have. It is the only stat that accounts for all scenarios and all outcomes, regardless of whether or not those outcomes were the pitcher’s intention.
Fielding Independent Pitching (FIP): Important
ERA is best understood when married to a statistic known as FIP. FIP is expressed in the same way as ERA (0.00), except FIP only accounts for outcomes in which the pitcher has complete control over. Those outcomes being a walk, a hit by pitch, a strikeout and a home run. In all of these scenarios, everyone in the field is completely irrelevant to the outcome of the at bat.
This statistic shows us how effective a pitcher is in getting outs on his own. It gives some quite simple results; players that get strikeouts and don’t allow base runners will have better FIP’s.
However, FIP on it’s own doesn’t get us very far in our understanding of pitcher performance. Pitchers are indeed responsible for a lot more of the game than just those four scenarios. Pitchers are responsible for forcing weak contact that can be easily turned into outs in the field. Things like routine fly balls and weak groundouts, caused by pitchers keeping batters out of rhythm, are not accounted for in FIP.
Instead, FIP and ERA are statistics best assessed together. A player can have a really good ERA thanks to great defense but a bad FIP because he doesn’t get enough results outside of his defense. The same is true in the opposite scenario, where the pitcher is able to keep runners off base by himself but ultimately loses out thanks to the bad defense. Neither statistic can effectively exist without the other.
Fielding Errors: Non-essential
Finally, let’s take a look at some fielding statistics. These statistics are the absolute hardest to quantify.
Fielding errors are a bit outdated once again because they are left up to the decision of the scorekeeper. A fielder can get eaten up by a tough ground ball and be given an error for even being in the vicinity of making the play. A lesser fielder wouldn’t even come close to making the play, and therefore would not be given an error.
A good fielder could also turn said plays into outs, which in turn gives them one put out on one chance. However, this looks all the same in the fielding errors statistic, because whether or not a fielder gets an out is different from if he “should’ve†gotten an out.
Outs Above Average: Essential
So how should we measure defensive performance? There are a number of statistics similar to it, but the most comprehensive of the bunch is outs above average.
Outs above average is one of the most fundamentally misunderstood statistics in baseball. It is calculated based on a number of factors, including defensive positioning, how far the defender had to move to make the out, how quickly the defender reacted, how hard the ball was hit, the launch angle the ball was hit at, etc. It isn’t perfect, as there are an endless amount of factors that can make the difference between an out and a baserunner, but outs above average gives us as extensive of a result as we currently have.
Outs above average is measured by Statcast, a computer system used by the MLB to gather a bunch of on-field data. Statcast takes into account all the factors it is programmed to, compares them across all similar plays across it’s database, and figures how likely it is that the result will be an out.
Based on that number, players then have their total outs above average added or subtracted to. This means that players who turn unlikely plays into outs are more rewarded than players who turn more expected plays into outs.
These plays look really different depending on the defender. The best defenders in the league will make extremely difficult plays look routine, while bad defenders will make in-between plays look very difficult. This is obviously dependent on that defender’s speed, arm strength, reaction time, and many other factors as was mentioned.
Like many defensive stats before it, outs above average will likely be replaced with something more comprehensive in the future. For now, it’s the best measuring stick for defense the major leagues have to offer.
There you have it. Hopefully this gives you more of an understanding behind the direction that baseball is moving in, and why certain trends are moving the way they are.
While you may still feel skeptical towards this new perspective, most of these stats just illustrate concepts that have always been understood to baseball players, coaches and fans: baserunners score runs, more power scores more runs, good defenses produce more outs, and good pitchers produce less runs.
