# Bases Created, Outs Made, OPS, and the Phillies (and You!)

One of the tricky parts about my job is straddling the line between accuracy and accessibility when using statistics. A lot of people know what OPS means and what it represents. But a lot of people don't, and both groups of people want to read about the Phillies. Sometimes I get emails complaining about my use of RBIs and pitcher wins in a story. Other times, I get emails complaining about my use of OPS and WHIP. Sometimes, I get both types of emails in the same day.

The problem with "counting" stats like RBI and hits and strikeouts is the fact that they do not consider the big picture, like how many runners a hitter had on base in front of him, or how many plate appearances the hitter had. The problem with a lot of percentage stats is that they are not intuitive. The difference between a .260 batting average and .300 batting average is four hits for every 100 at-bats, which is maybe 24 hits over the course of a season. What, exactly, does that mean in the context of an individual plate appearance? Try explaining the same for on base percentage and slugging percentage. Fast forward all the way up to a less accessible stat like Wins Above Replacement and you can understand why a lot of people just don't want to be bothered with it.

But what if there was away to lessen the disconnect by finding a way to quantify the events that really impact the outcome of a game in an intuitive fashion? Linear weights, the backbone of WAR-related stats, just aren't intuitive enough for a lot of people.

Here's my attempt. It comes with a disclaimer: I am not a math whiz. In fact, I hated math all the way up through college. But the following makes sense to me, and from my perspective it provides a relatively accurate and intuitive measurement of offensive performance. Maybe some form of this already exists. Whatever the case, it killed some time.

1) Outs, not hits, define success and failure.

Part of our problem lies with our desire to measure a player's success at the plate. But baseball is a game of failure. A game is not decided by a team's batting success. It is decided by a team's batting failure. A hit does not bring a game closer to its conclusion. An out does. Every out that a hitter makes brings his team closer to defeat. So why don't we measure performance with outs as baseline?

2) Two potential outcomes

Every time a hitter steps to the plate, he can create one of two outcomes: out creation, or base creation. This is the basic concept behind OPS: add the percentage of plate appearances that a hitter reaches base to the number of bases he creates per at-bat (single equals 1 base, double equals 2, etc.) and you get his OPS. The flaw, of course, is the fact that you are adding two fractions with different denominators (Times on Base divided by Plate Appearances, and Total Bases divided by At Bats).

Or. . .

TOB/PA + TB/AB

The basic rules of math say that we are not allowed to do what we do when calculating OPS. Which is why it is a flawed statistic.

3) Outs as the common denominator

To me, the simple solution is to use the one potential outcome that is common for all hitters as the denominator. In other words, the solution is to measure a hitter's production, or the bases that he creates, against the outs that he creates. After all, every out is worth the same amount: 1/27th of a team's allotted time at the plate. When a player doesn't make an out, he both creates offense and extends the amount of time his teammates have to score. When he makes an out, he decreases the amount of time his teammates have to score.

A player's value, then, is the offense he creates, or the bases he accumulates, measured against the outs he makes. The question every general manager should ask himself when he adds a hitter is, "Are the bases that this player creates worth the outs that he makes?"

Or, "How many bases-per-out does this player create?"

To answer the question, you simply divide a player's Total Bases Created by his Total Outs Made.

Think about it in this light: In the first inning of a game, Ryan Howard and Pete Orr both make outs during their at-bats. Both at-bats result in the elimination of 1/27th of the outs the Phillies are allotted for the game. But sheer intuition tells you that Ryan Howard is more valuable to a lineup than Pete Orr. And when you measure the offense he produces against the outs that he makes, the result tells you the same thing.

4) Calculating Bases Created

Total Bases is already a common statistic, one that counts a single as one base, a double as two, a triple as three, and a home run as four. But it doesn't include walks and hit-by-pitches. So just add a player's BBs and HBPs to his TBs and you get the total bases he has created.

Take a player's plate appearances and subtract the number of times he has earned his way onto base (Hits + BBs + HBPs) and you get the number of outs he has made.

Just divide. So, for example, Carlos Ruiz has creates 129 bases while making 125 outs this season. Divide 129 by 125 and you find that he has created 1.032 bases-per-out. Now take Pete Orr, who has created 19 bases while making 32 outs for a .594 bases-per-out ratio. In other words, for every out that Carlos Ruiz has made, he has created 1.032 bases, while Orr has only created .594 bases. Which, layman's terms, means an out by Carlos Ruiz is almost as justifiable, or almost as easy to swallow, or almost half as detrimental, as an out by Orr. Assuming, of course, they maintain their respective ratios.

The number looks similar to OPS, but in my mind it more accurately combines a player's on base percentage (or out-avoiding ability) with his slugging percentage (or base-creating ability). Ruiz, for example, has a .982 OPS against a 1.032 BCOM, which suggests that OPS undervalues Ruiz, while Orr has a .731 OPS against a .594 BCOM, which suggests that OPS overvalues Orr. The difference, in this case, lies in their on base percentages: Orr's is .302 while Ruiz's is .416.

7) A quick test

Obviously, a pitcher's success is based on the same two principles as a hitter's. Except the goal is to make as many outs as possible while allowing as few total bases as possible. To judge the accuracy of our little formula, I took the hitting and pitching performances of each team in the National League from 2011 and subtracted their Bases Allowed/Out Made (pitchers) and their Base Created/Out Made (hitters) and compared the result against their winning percentage. To give us a number that is easier to compare, I multiplied both sides by 27 outs. In other words, the table below shows the total bases an offense created over 27 outs (the average game, in other words), and the total bases a pitching staff allowed over 27 outs. I then compared their NL rank in that category to their NL rank in winning percentage.

 Team BA/27 Outs BC/27 outs Difference Win Perct. NL WP% Rank 1. Phillies 15.309 17.665 +2.356 .630 1 2. Brewers 16.486 18.537 +2.051 .593 2 3. Cardinals 17.306 19.140 +1.834 .556 4 4. DBacks 17.657 18.438 +0.782 .580 3 5. Braves 16.116 16.809 +0.693 .549 5 6. Dodgers 16.447 16.774 +0.328 .509 7 7. Giants 15.759 15.957 +0.198 .531 6 8. Nationals 16.826 16.681 -0.145 .497 8 9. Reds 18.437 18.157 -0.279 .488 9 10. Marlins 17.525 17.231 -0.294 .444 12 11. Mets 18.303 17.911 -0.392 .475 10 12. Rockies 19.179 18.391 -0.788 .451 11 13. Padres 16.705 15.515 -1.190 .438 14 14. Cubs 18.720 17.314 -1.406 .438 15 15. Pirates 18.516 16.113 -2.403 .444 13 16. Astros 19.452 16.088 -3.363 .346 16

So no team's rank in the difference between Bases Allowed and Bases Created per 27 outs (which is the same as their rank in the difference between their BAOM and BCOM), was more than two slots better or worse than their final rank in overall record.

This year? The Phillies' differential ranks 11th. Which should jibe with what you've seen.

8) The Phillies' offense in 2012

Here is the rundown of the BC/OM of each Phillies hitter (min. 60 PA), with their OPS in parentheses:

1. Carlos Ruiz 1.032 (.982 OPS)
2. Jim Thome .857 (.844 OPS)
3. Hunter Pence .799 (.822 OPS)
4. Shane Victorino .665 (.721 OPS)
5. Ty Wigginton .658 (.715 OPS)
6. Juan Pierre .624 (.734 OPS)
7. Brian Schneider .596 (.675 OPS)
8. Jimmy Rollins .575 (.688 OPS)
9. John Mayberry Jr. .560 (.652 OPS)
10. Placido Polanco .545 (.617 OPS)
11. Freddy Galvis .507 (.617 OPS)