Most people who play fantasy baseball participate in leagues which count basic statistical categories. Although actual league formats may differ (head-to-head, rotisserie, points leagues being among the most popular), the categories in which your teams compete are generally the same.

Most fantasy baseball leagues will consider the following categories for batters: Runs, Home Runs, RBI, Batting Average and Stolen Bases. Often for pitchers, the important categories are often comprised of the following: Wins, Saves, ERA, WHIP and Strikeouts. However, when evaluating players for your team (at either the draft table or when considering in-season trades and waiver wire moves), it isn’t always enough to concentrate on these categories alone.

Bill James and the statistical pioneers at the Society for American Baseball Research (or SABR, the acronym in which sabermetrics draws its name) have created a series of empirical methods for player evaluation that can be a fantasy baseball owner’s best friend. Although the categories discussed previously continue to account for the statistics by which most fantasy baseball owners are ultimately compared, by using key sabermetrics, one can get a better idea of which players may deliver traditional stats to your fantasy team. As any baseball manager or fantasy baseball owner knows all too well, each and every little bit of useful information may help in giving you a slight ‘edge’ and help you to pick the right player at the right time.

To help ‘de-mystify’ some of the key sabermetrics statistics which may be of importance in evaluating fantasy baseball players, the following is a run-down for the uninitiated:

FIP – “Fielding Independent Pitching”. At its most basic, FIP takes into consideration the factors that a pitcher can control (home runs, hits and walks) and doesn’t consider the factors that a pitcher can’t control (how well his fielders actually field balls in play). It’s basically a version of ERA which considers how well a pitcher actually pitched. One of the nice uses of FIP is when pitchers change teams or see their current teams change defensive players behind them. The FIP stat can help you see how pitchers can be expected to perform independent of their teammates on the field around them. As the Hardball Times says, “”FIP helps you understand how well a pitcher pitched, regardless of how well his fielders fielded.”

xFIP – “Expected Fielding Independent Pitching”. This is a version of FIP which ‘normalizes’ the home run component of the equation based upon league averages. Since home runs are basically related to fly balls allowed and home park differences, xFIP can be used to help determine a pitchers future ERA. This is particularly valuable to fantasy owners looking for an edge.

BaBIP – “Batting Average on Balls in Play”. Whereas batting average takes into account the percentage of at bats which become hits, BaBIP takes this a step further to determine the percentage of balls hit into play which become hits. By removing strikeouts from the equation, BaBIP can be a good indicator of how “lucky” either a pitcher or hitter has been, based upon the number of balls the opposing defence was able to handle (or mishandle as the case may be). Since baseball is comprised of a long season where statistics often regress to the mean, BaBIP can often be used to predict a player’s future statistics. For a hitter with a BaBIP much higher than the league average, it may indicate a dip in batting average is due. Conversely, a pitcher with a low BaBIP rate may be predicted to see an increase in hits allowed in upcoming games.

OPS – “On-Base Percentage Plus Slugging Percentage”. One of the most popular sabermetrics statistics in use today as well as one of the simplest, OPS combines two of the best metrics in determining a hitter’s value to his team. On-Base Percentage (OBP) is the ability of a player to get on base and Slugging Percentage (SLG) is the ability of a player to hit for power. As a point of reference, .728 was the average OPS for MLB in 2010. In his essay titled, “The 96 Families of Hitters”,

Bill James devised the following categories for OPS:

Great-               .9000 and Above A
Moderate-          .8333 to .8999 B
Above Avg-         .7667 to .8333 C
Average-            .7000 to .7666 D
Below Avg-         .6334 to .6999 E
Terrible-             .5667 to .6333 F
Atrocious-           .5666 and Lower G

For the sake of comparison, the Toronto Blue Jays’ Jose Bautista has a current OPS of 1.147.

Chicago White Sox slugger and key offseason acquisition Adam Dunn’s current OPS is .592.

VORP – “Value Over Replacement Player”. This statistic measures the total number of runs a player contributes to their team compared with a “replacement level” player at the same position. This can be a good point of reference in determining a player’s value to his team and thus see which players can be expected to get the lion’s share of playing time at a position. For hitters, the ‘counting stats’ of fantasy baseball (Runs, Home Runs, RBI, SB) are directly related to playing time. For pitchers, VORP is determined as a measure of how many runs that pitcher has prevented being scored against his team (in comparison to a replacement level pitcher). In either case, a player’s value to his team is the key measurable involved and can be useful in determining which players are more valuable than others on draft day or at the trade table.

WAR – “Wins Above Replacement”. Similar to VORP, WAR takes into account the value a player has to his team. However, instead of using runs as the measureable statistic, WAR takes into account how many WINS a player contributes to his team in comparison to a replacement level player at his position. It can be useful in comparing players WAR metrics in determining how valuable a player is to his team (and thus how likely he is to receive playing time).

ISO – “Isolated Power”. A rather simple metric, ISO is calculated by subtracting batting average from slugging average. This statistic represents a measure of a hitter’s raw power, or extra base hits per at bat. As a point of reference, Jose Bautista currently leads LB with a .356 ISO. The light-hitting Juan Pierre has a current ISO of .049.

Whether or not you perceive the alphabet soup of newfangled sabermetrics as being of any value to you in your fantasy baseball analysis, the bottom line is that these statistics certainly can’t hurt your chances. In fact, when it comes to competitive leagues…. each and every little bit helps.