Slugging percentage is TB/AB. TB stands for "total bases", meaning all the bases accumulated from a player's hits. For example, a single and a homer is five TB, for a player goes 1 base on a single and 4 bases on a homer. AB obviously stands for at bat. On paper, the idea of the amount of bases per at bat makes a lot of sense as an overall player rater. But the main issue with slugging percentage is the fact that it is too harsh on the leadoff man. A leadoff man like Michael Bourn has very low slugging percentage, despite the fact that he is the best player on the Astros. Bourn's slugging percentage last year was a meager .384. The major league average is around .415. Bourn's slugging percentage is low for two reasons: 1. People say that a walk is just as good as a hit. Slugging percentage does not credit Bourn for having such a high walk rate last year. 2. Bourn doesn't have a lot of power. He played in 157 games last year and only got 3 homers. He also lacks the power to frequently drive the ball to the wall and get a double or a triple. So almost every hit he got last year was a single. But the thing is Bourn got 131 singles last year, but he also stole 61 bases. A single and a stolen base is just as good as a double. If you treat every stolen base as a double, then more than half of Bourn's hits are for extra bases, which would give him an extremely high slugging percentage. So the fact that stolen bases and a high walk rate isn't factored into the equation of slugging percentage makes a flawed statistic.

On-base percentage is exactly what it sounds like: the percentage of the time a player gets on base (excluding reaching on an error). Personally, I think On-base percentage is a better stat than batting average. A walk is just as good as a hit and walks are included in On-base percentage. But, On-base percentage is clearly not a perfect measure of a player's production because a single is treated the same way homer is treated; even though a homer is more valuable than a single.

OPS is On-base plus Slugging. It is simply adding on-base percentage to slugging percentage. The main issue with OPS is the fact that it is a random combination of the two stats. A player's slugging percentage happens to almost always be higher than his on-base percentage. In a way, it's like adding batting average and homeruns together. If a player has 40 homeruns and a .230 bating average, then if you add it together you get 40.230. Compared to a player with 39 homers and a .360 batting average, the player with more homers wins, simply because the homers are weighted more heavily than the batting average. To a lesser extent, the same thing happens in OPS. Last year, the major league average OBP was .331, while the slugging percentage was about .416.

I decided that I wanted to create a stat that is better than these. A stat that combines everything that makes a player offensively efficient. I wanted to beat the conventional stats in baseball

So what is the stat that I created? (TB+BB+(SB-CS))/(PA-SH-SF-HBP)=OER. For those who don't know all the abbreviations, BB stands for walks, CS stands for the amount of times caught stealing a base, PA stands for plate appearances (which, unlike at-bats, includes bunts, sacrifice flies, times hit by a pitch, and walks), SH stands for sacrifice hits (meaning bunts), SF stands for sacrifice flies, and HBP stands for the amount of times hit by a pitch. As of May 25, this is everyone's numbers under the statistic, and every team.

So how accurate is the stat? Well, I decided to rank the teams offensively based on my stat and see how well it corresponds to the amount of runs that team has scored, and then add the difference to the total. For example, the Diamondbacks are 1st in my stat. They are 4th in total runs scored on the season. 4-1=3, so that's 3 points of error for my stat. I added the amount of points for all teams, and my stat got 72 points overall. That means there were 72 points of error for my stats I then compared my stat to OPS, OBP, BA, and SLG, by figuring out all of their point totals, and the stat with lowest amount of error points wins. Here are my results:

Fortunately, my stat won comfortably, beating BA 72 to 164, OBP 72 to 148, OPS 72 to 96, and SLG 72 to 88. I was happy that OER won comfortably, but I was also happy to see OBP beat batting average. It proves that a walk is just as good as a hit and that it was a good idea to factor walks into the equation.

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