Calculating Baseball Statistics - Fielding Percentage (FP)

In the world of baseball statistics, In addition to hitting and pitching statistics, there are several fielding statistics that are useful when evaluating a player. In this article, we'll take a look at one of the most common.

Fielding Percentage, or FP for short, is a statistic designed to show what percentage of plays that a fielder attempts to make that they completed successfully. In other words, of the balls the player attempted to catch, in what percentage did he not make an error.

To calculate Fielding Percentage, you need a fielder's Putouts, Assists, and Errors. A Putout is an instance in which a fielder makes an out by himself, for example, by catching a fly ball or fielding a ground ball and tagging a runner or base. An Assist is when a player is part of a play that creates an out, but does not create the out himself, such as a throw to a base that retires a runner or to another fielder that tags a runner. For example, on a ground ball to the shortstop, the shortstop fields the ball and throws to first in time to retire the runner. On this play, the shortstop gets an assist, and the first baseman gets a putout. An Error is when a player attempts to make a play, but fails to do so, either by failing to catch a ball or making a bad throw. An error is a physical error only - a mental error, such as throwing to the wrong base, is not counted in a players error count, although it can certainly hurt a team.

Once you have these fielding statistics, you calculate Fielding Percentage using this formula:

Fielding Percentage = (Putouts + Assists) / (Putouts + Assists + Errors)

For example, in 2005, Seattle Mariners Right fielder Ichiro Suzuki played 158 games in the field. In those games, he racked up 381 Putouts, 9 Assists, and 2 errors. Plugging those numbers into the formula, you get:

(381 Putouts + 9 Assists) / (381 Putouts + 9 Assists + 2 Errors) = 390 / 392 = .995 FP

Fielding Percentage is displayed as a decimal with three numbers after the decimal. A perfect Fielding Percentage (zero errors) would be displayed as 1.000. A .995 Fielding Percentage is very good, and Suzuki won a Gold Glove for his effort. In 2005, the average American League Right Fielder had a Fielding Percentage of .982, showing just how impressive Suzuki's numbers were. In recognition of his fielding prowess, Suzuki has won five Gold Glove awards in the last five years.

The average Fielding Percentage at each position is different, as each position presents it's own challenges. While the average American League Right Fielder fields at a .982 rate, the average American league First Baseman fields at a .994 rate, and the average American League shortstop fields at a .972 rate. This does not mean First Baseman are the best fielders, simply that on average, it is a position where fielders make a higher percentage of plays successfully.

Fielding Percentage is not an infallible statistic. Often the Gold Glove winner at a position is not the player with the highest Fielding Percentage. There are several reasons for this. Since FP only measures the percentage of chances a player attempts, it tends to hurt a player who attempts harder plays. A player with more range might get to more plays than a player with less range. If he makes ½ of those plays, he helps his team more than a player who gets to none of those plays, but it's counted against his Fielding Percentage. For this reason, it helps to look at a player's Total Chances (another way of saying combined Putouts, Assists, and Errors) and another statistic called "Range Factor" in conjunction with their Fielding Percentage.

Another reason that Fielding Percentage is not infallible is that Errors are decided upon by the Official Scorer at each individual game. Some scorers are more apt to give errors on some plays than others, and often you hear about an Official Scorer being a bit kinder to the home team's fielders than to the visitors. Since Errors are subjective to a degree, we must keep this mind when using Fielding Percentage to evaluate a player. As mentioned above, it is best to look at as many statistics are available to help make your evaluations more accurate.