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# A better stat than OPS

### BPO is the ideal measure of a batter’s full abilities, and it’s easy to understand, too

I referred to a stat abbreviated as BPO in three recent installments of Baseball’s Best (and Worst).

“This requires some explanation. It might, in fact, be worthy of a future column by itself,” I wrote on the first occasion, October 13, when discussing my procedure for determining **the best players of the 21st century.**

But I didn’t go into much detail then or when I again mentioned BPO **on October 16** (releasing my rankings of top catchers) or **four days after that** (comparing the best seasons of Joe Morgan and other all-time greats).

So let me devote a few hundred words now to making the case for BPO.

The object, of course, is to score more runs than your opponent, but the name of the game is *base*ball, not *run*ball. We’re blessed with a plethora of run-related statistics — runs scored, runs allowed, runs batted in, earned runs, earned run averages — but virtually nothing for bases.

It’s a mystifying omission. We all know the importance of reaching as many bases as possible, even if the impact hasn’t been quantified. I’ve always liked this quote from Doug Melvin, former general manager of the Milwaukee Brewers and Texas Rangers: “You can’t win the game without moving the pieces on the board. It’s all about capturing bases.”

That’s why I developed my formula for BPO — bases per out — while preparing my 2016 book, **The Best (and Worst) of Baseball’s Modern Era.**

There are three steps involved in calculating BPO. **Step One** is to add up a batter’s bases:

**B = TB + BB + HBP + SB + SH + SF**

TB, of course, is total bases generated by hits. But there are several other ways to accumulate bases for your team, whether by walking, being hit by a pitch, stealing a base, laying down a sacrifice bunt, or swatting a sacrifice fly. They’re all added to the mix.

**Step Two** is to count a batter’s outs:

**O = AB - H + CS + GDP + SH + SF**

The obvious start is to subtract hits from at-bats. Additional outs are produced by being caught stealing, hitting into a double play, and sacrificing by bunt or by fly. (The latter two are included in both formulas above, since they involve the trade of an out for a base.)

That leaves a simple matter of division for **Step Three:**

**BPO = B / O**

Let’s put the formula into action, comparing 2020’s leaders in batting average, New York’s D.J. LeMahieu in the American League and Washington’s Juan Soto in the National League. Which of these two stars generated the most bases per out?

**Step One.** Add the bases:

**B = TB + BB + HBP + SB + SH + SF**

LeMahieu = 115 + 18 + 2 + 3 + 0 + 1 = 139

Soto = 107 + 41 + 1 + 6 + 0 + 0 = 155

**Step Two.** Add the outs:

**O = AB - H + CS + GDP + SH + SF**

LeMahieu = 195 - 71 + 0 + 3 + 0 + 1 = 128

Soto = 154 - 54 + 2 + 1 + 0 + 0 = 103

**Step Three.** Calculate bases per out:

**BPO = B / O**

LeMahieu = 139 / 128 = 1.086

Soto = 155 / 103 = 1.505

Both players enjoyed outstanding seasons. Batting average, the traditional benchmark, gives a healthy advantage to LeMahieu, .364 to .351. But BPO deems Soto to have been the more effective batter in 2020. The Nationals outfielder generated a base and a half for every out that he made (1.505), compared to slightly more than a base per out by the Yankees infielder (1.086). That’s a huge difference.

Yet we shouldn’t overstate the disparity. The BPO figures for both players above are outstanding. Any batter who produces more bases than outs is highly effective at his job.

The standard tends to be in the range of .700, the equivalent of seven-tenths of a base per out. Leaguewide averages were .698 in the AL and .716 in the NL this year. The highest figure since the turn of the century was posted in the very first year, .768 by American League batters in 2000. The worst drought was .642 by National League hitters in 2014.

BPO’s strength is its reflection of a player’s ability to reach as many bases as possible — hitting for average, hitting for power, coaxing walks, flashing speed on the basepaths, giving himself up to advance a runner. It’s all there in a single number.

Compare it to OPS, the sport’s current darling. The benign abbreviation for OPS hides a clunky name — on-base-plus-slugging percentage — and an illogical formula.

OPS is calculated by adding a player’s on-base and slugging percentages, a dubious concept at best. The two components of OPS have wildly different ceilings (1.000 for OBP and 4.000 for SLG), so it makes no sense to assign equal weight to both. They also have different denominators — the sum of AB, BB, HBP, and SF for OBP; only AB for SLG — and any sixth grader knows that you can’t add fractions unless their denominators are the same.

A batting average of .300 means that a batter produces three hits for every 10 at-bats. A BPO of .700 equals seven-tenths of a base per out. But what does an OPS of .800 mean? Absolutely nothing. It truly doesn’t translate to anything.

The defenders of OPS insist that it just seems to work — somehow, some way — so we should ignore its weak mathematical foundation. I intend to go one step further and ignore it completely. You will never see me cite the OPS for any batter, simply because the resulting number lacks any true meaning.

As for BPO? That’s an entirely different story. It’s easy to calculate, easy to understand, and reflective of all aspects of a batter’s performance. I’ll be citing it a great deal — and now you know why.