The Mistake Index

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Scott%20Lindholm%203By Scott Lindholm

Consider these facts:

1. From 2000-2012, NFL teams with fewer turnovers than their opponents won 79.6% of games (2133-548)

2. In 2013, NBA teams with fewer turnovers than their opponents won 60.7% of games (678-439)

There isn’t a football or basketball pregame show in which one of the “keys of the game” WON’T be to “win the turnover battle.” Turnovers reduce opportunities to score and give additional chances for opponents to score. They’re MISTAKES—and it’s the same in baseball. Baseball mistakes allow extra base runners or extra bases at no cost and make it easier for opponents to score.

I update the Mistake Index on my blog Beyond the Scorecard daily. This is through Thursday, July 25th:


I quantify baseball mistakes using play-by-play data and use a very simple measure:

Opponent Mistakes – Team Mistakes

If a team makes fewer mistakes than its opponents, I believe they have the opportunity to win more games. Using my measure:

Positive Value=team makes FEWER mistakes than opponents (GOOD)

Negative Value=team makes MORE mistakes than opponents (BAD)

The White Sox are ranked #1 by making 114 more mistakes than their opponents. Teams want to be at the BOTTOM of this list, not the top.

The Mistakes

I break my mistakes into three broad categories:

Pitching—Blown Saves (BS), Hit by Pitch (HBP), Balks (BK), Wild Pitches (WP), Passed Balls (PB), Errors in Pitching (EP) and 2-Out Runs (2oR)

Fielding—Errors (E) and Unearned Runs (unER)

Base Running—Errors in Base Running (eBR) and Errors in Bunting (eBU)


Blown saves are a true mistake, since by definition a team was in position to win and pitched itself out of it. HBP, balks, wild pitches and passed balls are exactly what they are and are measured because they allow opponents to either reach or advance a base(s). There is a very direct relationship between total bases and runs scored—historically, runs scored are 30-34% of total bases:


Errors in pitching are any of these events that DIRECTLY allow a run to score, such as a walked hitter forcing in a runner from 3rd. 2-out runs are a personal pet peeve that you can read more about in this post.

Putting it all together:


Even with the overall effectiveness of the Cubs pitching staff, they lead the majors in blown saves and errors in pitching. The Cubs made 25 pitching mistakes (eP) that directly led to 25 runs(R) and another 86 mistakes (xB) that allowed a base runner to advance which translated into approximately 25 more runs (xBr). Their opponents only allowed 12 runs to score on pitching mistakes and gave up 73 additional bases, or around 21 runs, a difference of 17 runs to the negative for the Cubs. This table summarizes these facts:


Sabermetricians state that around 10 runs equals a win, meaning those 17 runs might have cost the Cubs two wins. Consider this:

Actual record                                       45-55

Pythagorean Wins                             48-52

A difference of three wins from what the Pythagorean Runs formula predicts—tracking pitching mistakes helps illuminate why.


Errors and unearned runs are never seen side-by-side. These are 2013 values (data through Thursday, July 25th):

Errors     1,749                                         Unearned Runs     979

Dividing unearned runs by errors shows that 56% of errors result in an unearned run, in line with historical standards:


Over time, the incidence of errors has decreased greatly to around one every two games (red columns and right axis). Just as steady has been that 55-57% of errors result in unearned runs (blue line and left axis). Reducing errors reduces runs allowed—when half of ANYTHING results in a score, teams benefit by eliminating it.


Base Running

When a base runner is out on a forceout or a GDP, it’s not his fault. What I measure are attempts to stretch a hit or advance on the bases and the runner is out. Bunting by itself is an excellent strategy—teams bat .400 when attempting to lay down a bunt for a hit. What is measured are failed sacrifice bunts, foul outs, pop-ups or double plays. If a player tries to bunt with the bases empty and makes an out, it is NOT measured.


Most of these measures can be found with a little digging at but play-by-play data is required to determine opponent mistakes. Mistakes individually won’t make or break a team, but their cumulative effect can be the difference between making the playoffs…and watching them.

But does it work?


Horizontal axis—Team Mistake Index

Vertical—Winning Percentage

This data is from 2009 through mid-July and plots the correlation between winning percent and the Mistake Index. Here’s how to view the quadrants:

Upper Right—team plays ABOVE .500 and makes FEWER mistakes than opponents

Upper Left—team plays ABOVE .500 and makes MORE mistakes than opponents

Lower Right—team plays BELOW .500 and makes FEWER mistakes than opponents

Lower Left—team plays BELOW .500 and makes MORE mistakes than opponents

If the index is valid, we’d expect to see most teams in either the upper right or lower left quadrants. Out of the 150 data points, only about 11 represent outliers that don’t conform to this general pattern.

It’s not perfect, but the Mistake Index takes different measures and puts them together in one place for easy comparisons. Look at the teams with the largest negative values, the White Sox and Astros–no one considers them the class of the Major Leagues. The teams at the top, Minnesota and St. Louis, prove the index isn’t perfect—the Cardinals are one of the best teams in baseball, and the Twins…aren’t. But baseball is like every other sport—the fewer the mistakes, the better the OPPORTUNITY to win.

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