Here are some quick explanations of the possibly unfamiliar statistics used for the Simple WAR Calculator. For more information I would suggest a trip to the much more thorough FanGraphs Saber Library (I’ve provided links to the relevant sections throughout this glossary).

What is WAR?

Wins above replacement is an approximation of a player’s value, expressed as an approximation of how many more wins his team won with him than it would have with a “replacement-level” player (i.e., a waiver-wire claim or a Quad-A player).

For reference, a league-average player will be worth about 2.0 WAR over a full season, and a replacement-level player’s WAR is defined to be zero. So a team with a 5.0-WAR player at a given position would win three more games than they would if they replaced him with an average player, and five more games than if they used an emergency fill-in. (Saber Library)


  • BABIP: Batting average on balls in play, also known as hit rate. This is the measure of how often a batter gets a hit (or a pitcher allows one) when he makes contact and the ball stays inside the park. It’s basically batting average that leaves out home runs and strikeouts. The league-average BABIP is right around .300, though that can vary by player: powerful line-drive hitters (Miguel Cabrera or Joey Votto) and speedy groundball hitters (like Ichiro) tend to do better than slower, weaker-contact or flyball hitters (Rafael Palmeiro had sub-.260 BABIPs in each of his last five seasons). But it’s one of the slowest stats to stabilize. if a batter has an extremely high (or low) hit rate in a season, it’s probably due to luck unless he has a history of high (or low) hit rates. If not, for the purposes of projection you should assume that a player’s BABIP will be right around the mean. (Saber Library)
  • Home runs, walks, strikeouts, stolen bases plate appearances, games played: These should all be fairly self-explanatory.


  • OPS+: On-base plus slugging percentage plus is a means of measuring offensive ability through OPS. It adjusts for differing run environments, making it is a much more accurate way to compare  hitters in different leagues, parks, or seasons. As Tom Tango noted, it is roughly interchangeable with wRC+. (Saber Library)
  • FIO: Fielding Independent Offense, developed by Bradley Woodrum, is what made the first calculator possible—it was the spark, the giant leap for mankind, the primordial ooze from which my creation sprang. FIO is a simple estimator of wRC+ (Weighted Runs Created-plus, a measure of a player’s relative hitting skill in terms of runs created per plate appearance) based solely on home runs, strikeouts, walks, and BABIP. (Saber Library)
  • Hitting: The number of runs a hitter creates above (or below) what a league-average hitter would produce in the same number of plate appearance. It’s calculated in with OPS+ and PAs in version 2.0 and with FIO and PAs in version 1.1. (Saber Library)
  • Fielding: One of the great advances of the sabermetric movement is the development of fielding statistics based on how many runs players save (or allow) with their gloves relative to their peers. The specifics differ for each system—UZR, DRS, TZR, FRAA—and the results don’t always line up, but they’re all generally in agreement about what defines a good fielder (or a bad one). This is an approximation of whatever metric you prefer. These numbers are scaled so that zero indicates an average fielder for each position, not all of baseball. So if hypothetical shortstop “Vomar Izquel” is a +15 fielder, that means he’s 15 runs better than the average MLB shortstop, not the average generic fielder. (Saber Library)
  • Baserunning: The ability to steal bases and leg out extra-base hits is lumped in with hitting, but wRC doesn’t measure a player’s ability to move up an extra base on someone else’s contact when a lesser runner would hold up—or worse, get thrown out. This is the least important factor in that the differences between the best and worse baserunners is smaller than the stratification of hitting and fielding talent, but it still matters. (Saber Library)
  • Position: It’s a lot harder to play catcher than it is to play left field. A shortstop should be able to play a pretty good first base once he learns the intricacies of the position, but the average first baseman would be a butcher at shortstop. This number serves a handicap for players at premium defensive positions and a means of comparing players at positions with differing levels of “average” via a common baseline. (Saber Library)
  • Replacement: Offensively, a “replacement-level” player (i.e., a waiver-wire claim or a Quad-A player) is defined as being approximately 20 runs below average per 600 plate appearances. This is what turns runs above average to runs above replacement: by crediting the hitter with a run every 30 plate appearances just for showing up, we move our baseline lower. Note that a replacement-level player will see his positive score here perfectly negated by his negative Hitting runs. (Saber Library)
  • RAR: Runs above replacement is the sum of a player’s Hitting, Fielding, Baserunning, Position, and Replacement runs. If you were to replace a player with a minor-league scrub, this is a measure of how much your team’s run differential would fall. (Saber Library)
  • WAR: Wins above replacement is calculated by divided RAR by a constant conversion rate for position players (for simplicity’s sake the calculator assumes a conversion rate of 10 runs per win, though that can vary slightly depending on the run environment) and an adjustable conversion rate for pitchers. (Saber Library)
  • Value: The amount a team would have to spend in order to replace or replicate a player’s production on the free agent market. Right now the market values marginal wins at about $5 million apiece (the calculator assumes one WAR is worth $5 million), but remember that not all teams are alike. The Yankees might value an additional win at (say) $8 million if they’re in a close race for a playoff spot at the trade deadline, while a small-market cellar-dweller might not want to raise payroll by even $3 million to win 61 games instead of 60. (Saber Library)

If you have any questions, problems, or suggestions, please let me know!