ORA is a stat calculated by a computer program that can tell you the average number of runs a player would score in a nine inning game. The simplest way to picture it is that if every player in baseball were the player you are evaluating then ORA would be the average MLB pitcher's ERA. For more info on how it works click read more at the bottom of this entry, or the button below.

I created this stat earlier this year, and just created a page explaining it. On this page I released the top 97 ORAs of 2014. I will be releasing all 2015 qualifying players a few days after the end of the season. My sneak preview here is that Bryce Harper will runaway with a ORA that is currently 10.91 and will certainly not change to much. That crushes Victor Martinez's league leading ORA last season which was 7.88. The stat has some similarities to OPS in that it incorporates the different values of getting on base and how far around the bases your hit gets you. However the way in which ORA is calculated gives every kind of hit (or walk) the value it deserves and has an applicable meaning behind the stat, in the form of a run value instead of just a meaningless value from 0.ooo to 5.000. |

__Below is how the program works:__Basically it says if this player were to bat the odds of him getting any result would be

__Result X occurences__

Plate Appearances

This makes sense, if a player has 50 doubles in 500 plate appearances you could assume that when he's up you have a 1/10 chance of seeing another double. So then you could find the odds of scoring a run by hitting two doubles in a row if every player in the lineup were this guy would be 1/10*1/10 = 1/100 per two plate appearances. You could try to calculate the odds of every way of scoring a run (or not scoring a run) in an inning, but there are literally an infinite number. This program instead says that this player will bat until he makes three outs and then to simply submit the resulting number of runs. It then repeats this over and over again until it has submitted 1 million inning results. Then the average number of runs simulated to score in those million innings multiplied by 9 is telling you

**the number of runs expected to score per game if every batter in the lineup were the given player.**