## Batting Average Calculator (Plus Definition)

Baseball Batting Average Calculator: How to turn baseball batting average into a metric for hitter success.

Batting average is one of the most important statistics in baseball. How well you hit the ball (how many hits divided by how many times you go up to bat) determines whether or not your team wins, and it can be a very telling statistic about what kind of player you are. The best hitters have batting averages over 300; below that, and they’re usually at risk for getting benched (or worse). To calculate your own batting average, all you need is a calculator–and this blog post!

## 1. What is a batting average?

Batting average, or the percentage of at-bats that result in base hits, has been a way for baseball fans to evaluate the hitter success since the sport was played without gloves. Simply put, if a player has 100 at-bats and gets 50 hits then his batting average is .500 or 50%. A perfect score is 1.000 or 100%.

## 2. How do you calculate Baseball Batting Average?

There are several ways to calculate batting average, but all of them come down to runs divided by at-bats minus strikeouts divided by plate appearances. The calculations have evolved because simple math did not take into consideration walks, hit by pitches, and sacrifices. Runs Batted In (RBIs) was added in 1856 when Henry Chadwick invented the box score. Sacrifice bunts were added to the calculation in 1894 by Henry Nathaniel Wing, a minor league player/manager from New York. In 1920 sacrifice flies were added and finally, in 1988 a tenth of a point was added to better reflect hitters’ contributions as compared with their peers.

## 3. What is an OPS?

OPS or on-base plus slugging is another way to evaluate hitters. To calculate OPS, you first need to determine a player’s On Base Percentage and Slugging Average. A hitter’s OBP (On Base Percentage) is calculated by adding his walks and hit by pitches, then dividing that number by his at-bats plus walks and HBP. His SLG (Slugging %) is calculated by multiplying singles, doubles, triples, homers and dividing that number by AB + BB + HBP all divided by plate appearances. Once you have those numbers simply add them together and divide the sum into 1 to get an OPS. If two players had an OBP of .400 and a slugging percentage of .500 their combined OBP would be .900 and their combined slugging percentage would be 1.000 for an OPS of 1.910 which is better than a player with a .450 OBP and a .550 SLG or an OPS of 1.960 who has the same number of hits but fewer walks and more extra-base hits.

## 4. How to convert batting average into runs created

The batter’s batting average (BA) is converted to runs created by dividing the player’s total bases by their plate appearances. Using our example above where a hitter gets 50 hits in 100 at-bats if 28 of those were for extra bases they would have counted as 56 total bases divided by 100 plate appearances which equals .560 or 56%. Using the same example you, could also say that .560 of the player’s total plate appearances were used to get hits or 56% of their plate appearances. Going back to our original example where the hitter gets 50 hits in 100 at-bats, if 28 of those were for extra bases they would have counted as 56 total bases divided by 100 plate appearances which equals .560 or 56%. Therefore, you could also say that .560 of the player’s total plate appearances were used to get hits or 56% of their plate appearances.

## 5. Why the MLB only uses decimal numbers for their stats?

In 1984 the MLB decided to keep track of play by only using whole numbers and decimals. By doing so they eliminated errors that were not being caught at first or second base due to a lack of accuracy. In high school and college, coaches will use calculators to determine if a player is safe at first on a ground ball as long as the number returned has 4 digits after it which eliminates most human errors from slipping through.

## 6. The history of the batting average stat?

The use of the batting average to gauge a player’s offensive performance has been around since the 1800s. At the time, it was one of the more popular gauges of a hitter’s success because it was easy to calculate and understand. There are some accounts, however, that suggest Henry Chadwick, an English sportswriter who introduced baseball in America in 1856, didn’t invent the statistic, but made it popular by publicizing it in his account of the matches.

## 7. How do you convert runs created into wins?

It’s important to note that while runs created might give you a good idea of how many runs a player is responsible for or contributes to their team, that doesn’t necessarily mean that it’s a good statistic for evaluating an individual player or how many wins they contributed to the team. For example, if Albert Pujols has 100 runs created and hits 40 home runs that give him a 4.0 RC/27 (Runs Created per 27 outs). With those numbers, you can see that he is responsible for scoring or driving in over 4 runs per game. That is a great figure for someone who gets 600 plate appearances in a season or about 150 games if they don’t get on base at all during the other innings. However, what does that number mean to your team? Does Pujols contribution of over 4 runs per game help your team win games? What you have to look at is what the average runs per game are for a team during that season. The Los Angeles Angels of Anaheim finished 4th in the AL West in 2008 with 725 runs scored which comes out to only 3.80 runs per game or about 1/3 of what Pujols contributed in his own. That means Pujols is responsible for a little less than 2 games won during the 81 game season. That’s impressive, but that doesn’t necessarily translate to his team winning more games because there are other factors besides runs created when it comes to evaluating how many games a player contributes to their team winning. In this case, Pujols was only responsible for about one extra win for the Angels which would have put them in third place behind the Oakland Athletics that year.

## 8. Why do some hitters have more than one number that they are known for, like Babe Ruth’s .342 and .714 averages?

In Babe Ruth’s case, his infamous .342 batting average may have been a bit misleading. In 1921 when he hit 41 home runs and batted in a league-leading 127 runs he finished with a .378 BA which was a 58 point increase over the previous year. He also had an on-base percentage of .545 because he walked 154 times and struck out only 35 times. So when looking at the two numbers, it’s clear that he didn’t get this number simply by hitting singles or doubles, but also by avoiding strikeouts, which allowed him to draw walks and be intentionally walked a league-leading 22 times in 1921.

One of the biggest misconceptions that people can have about statistics is that they are objective and impartial. This could not be further from the truth because all statistics must be interpreted by someone to give them meaning. There’s no magic formula behind many statistical equations, there is simply a group of people who made what they think are reasonable assumptions to come up with an equation or set of formulas that provide results that tell them how likely certain events or scenarios may play out based on their inputted data. If you’re using the wrong data for your inputs, then your results will suffer accordingly. So just remember, all stats are just another tool to use when making decisions, but it doesn’t mean they’re always right or that you should put too much trust in them.

The second misnomer people might have about stats is that they provide an unbiased depiction of what happened during a certain period. This again, couldn’t be further from the truth. All statistics are subject to bias depending on how you collect your data and determine certain statistical calculations. The sample size you use means everything when it comes to developing an accurate measurement or number. When a statistician calculates a stat based on a standard deviation or something similar, they’re assuming that sample of data is from what is called a normal distribution which means that roughly 68% of the data is from one side of the mean and 95% of the data will fall within 2 standard deviations from the mean. In this case, that means if we were to create a stat that gave us a batting average for players, we would assume that 3 out of every 4 players hit around .260, and 95% of all player’s averages would be between roughly .210 and .350. But how often do you see numbers like this in reality?

## Final Words

A hitter’s batting average is the number of hits divided by at-bats. A high batting average means that a player gets on base more often than not, which can lead to him scoring runs for his team. If you’re looking to get better at baseball or just want an idea if your current stats are good, give this a shot and see how it impacts your game!

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