Sabermetrics -- or analytics or advanced metrics or whatever you want to call it -- are an important and indelible part of baseball these days. They illuminate aspects of the game that traditional measures can't touch, and at least on some level they inform every front office decision.

For the uninitiated, however, advanced metrics can be confusing, intimidating and off-putting. This isn't a problem native to sabermetrics, though. For instance, try describing something as basic and traditional as ERA to a non-baseball fan. For us, it's familiarity disguised as simplicity.

So to advance our familiarity of these more advanced statistical gauges, let's embark upon a glossary of sorts. What follows is meant to explain, in simple terms, what these statistics measure, how they go about measuring those things and how well they do it. There's no such thing as a perfect statistic when it comes to baseball. When trying to peg a player's true value, you're putting together the pieces of a puzzle rather than eyeballing one number and declaring the discussion over. This, then, is a walking tour of those puzzle pieces (metaphors, mixed).

Below, I'll break the statistics down into categories: Total value statistics (those that measure a player's entire complement of contributions -- offense, defense and base-running), offensive statistics, pitching statistics and defensive statistics.

Let's light this candle, with major assists from FanGraphs and Baseball-Reference, where all the stats below can be found ...

TOTAL VALUE STATISTICS

Wins Above Replacement (WAR): Let's start with the statistic that has achieved a rather controversial prominence in recent years. WAR is an all-encompassing stat that attempts to measure a position player's or a pitcher's total value. For position players, this means hitting, base-running and fielding are taken into account.

WAR is measured in theoretical runs and tied to a "replacement level" base-line. A replacement-level player is any player type who's cheaply and widely available to major-league teams in a pinch. Examples of replacement-level players include some bench players, waiver claims or minor-league veterans -- i.e., the kind of stop-gap a team can scare up in an emergency situation. By definition, these players are not good; they are in a real sense the least an MLB team can do when it comes to filling a role on the fly.

By way of example, last season Adam Dunn checked in at 0.0 WAR according to FanGraphs. While Dunn was a regular and not one of the replacement-level prototypes listed above, he provided value as though he were just that. He hit a little bit, but he was a substantial defensive liability in his 275 innings in the field and also gave away runs while running the bases. As well, WAR builds in an adjustment based on the difficulty of a player's defensive position -- i.e., those capable of manning shortstop get a boost relative to those like Dunn who are confined to DH/1B/LF -- so that also brings down Dunn's overall value. Keep in mind, of course, that Dunn authored a darn good career -- 462 homers and a 123 OPS+ (more on OPS+ in a moment!) tell you that much. However, in his recently completed age-34 season Dunn was in essence a replacement-level player.

On the other end of the continuum, we have Mike Trout who in 2014 put up an MLB-leading WAR of 7.8, meaning he was roughly eight wins better than a replacement-level player. Stated another way, if you swapped out Trout for, say, an emergency fringe talent, then the Angels would have been almost eight games worse in the standings. Suffice it to say, that's a huge difference, particularly in a sport like baseball in which any individual player's contributions are structurally limited. (Aside: Per FanGraphs, the highest single-season WAR of all-time is Babe Ruth's 15.0 in 1923.)

FanGraphs and Baseball-Reference are the two primary purveyors of WAR data, and there are some differences between the two calculations, especially when it comes to pitching. FanGraphs' version of WAR (usually abbreviated as "fWAR') uses as its primary inputs the elements of the game over which the pitcher (and catcher, to an extent) exerts the most control. To wit, fWAR pays the most heed to strikeouts, walks, home runs allowed, groundball-flyball tendencies and popup rates. In contrast, bWAR is, generally speaking, driven by a pitcher's runs allowed. In other words, bWAR, relative to fWAR, makes less of an attempt to isolate pitching from fielding. As a consequence, you see the two methods diverge pretty substantially when it comes to some pitchers.

For example, Nathan Eovaldi in 2014 pitched to a bWAR of 0.2 but an fWAR of 3.0. In the former instance, he's a replacement-level pitcher; in the latter, he's a well above-average major-league starter. Why the wide gap? Well, Eovaldi gave up 107 runs in 199 2/3 innings and did so while pitching his home games in a run-suppressing park and in a down year for offense. (WAR, like the best metrics, corrects for league and ballpark influences.) That leads to his paltry bWAR. On the other hand, Eovaldi struck out more than three times as many as he walked, and he also did a good job of keeping the ball in park. His success in those regards helps yield his strong fWAR.

In a way, though, this seeming disconnect is a feature rather than a bug. Determining pitcher value is a tricky thing, and together these two distinct measures do a good job of capturing and rendering the many-splendored thing that is pitching. Want a "bottom line" measure of value that bakes in defense and blind luck into the mix? Then bWAR is the right choice. Want something that isolates a pitcher's core skills? Then fWAR is here to help. Some analysts even use a blend of the two measures to arrive at a WAR figure that provides a bit of both approaches. Those who complain, somewhat simplistically, that WAR is to be ignored because not even its advocates can agree on how to calculate it are really wishing that pitching itself weren't quite so complicated and nuanced.

To be sure, though, WAR does have weaknesses. Specifically, the defensive component of WAR -- Ultimate Zone Rating (UZR) for fWAR (more on UZR below) and Defensive Runs Saved (DRS) for bWAR -- aren't as definitive as we would like. Each is among the very best methods we have for assessing defensive value, but they're far from perfect. First, single-season defensive data is especially prone to random variation, and second, the publicly available defensive data may not fully correct for things like extreme defensive shifts (which are very much a part of the game these days).

If a player's WAR seems to be heavily uplifted or dragged down by an outlying single season of defensive data, then skepticism toward our ability to peg his value is warranted. Also, WAR isn't precise in the extreme. A player with a 3.3 WAR isn't irrefutably better than a player with, say, a 2.9 WAR. The error bars are there, but as blunt instruments go, it's our best implement when it comes to gauging a player's overall value. In large part, that's because WAR does a tremendous job at reflecting offensive value.

WAR adds to our understanding of the game. Those who cite it as inerrant gospel are misguided -- almost as misguided as those who indulge in wholesale dismissals of WAR.

Further reading on WAR: FanGraphs, Baseball-Reference, Wikipedia

My promise to you: Succeeding entries are going to be much shorter!

Win Probability Added (WPA): How much a did a player or hitter alter a given game with his performance? This, broadly speaking, is the question that WPA attempts to answer. Basically, WPA tracks a team's percentage of winning a given game -- known as "win expectancy" -- and measures how a given player affects that percentage. RBI double in the early innings of an eventual 12-3 win? The hitter's WPA will go up at game's end, but not by all that much. Down 3-2 in the ninth, bases loaded with two outs and the batter strikes out? His WPA for the game is going to take a pretty substantial hit, since that was the quintessence of a clutch situation.

For season-long totals, a player's or pitcher's WPA tallies from each game are added up -- the positive and the negative -- to arrive at a final figure. You'll find that these generally track with our notions of who the best producers are. After all, good players tend to be good in all situations, and "clutch" best describes performances rather than the performers themselves.

Last season, Trout led all players with a WPA of 6.88, which means that through the timing and sequencing of his efforts he added almost seven wins over and above the average MLBer.

OFFENSIVE STATISTICS

Isolated Power (ISO): ISO -- also sometimes referred to as "Isolated Slugging" -- is an indicator of a hitter's raw power. It's simply batting average subtracted from slugging percentage. Basically, it's how many extra bases a hitter averages per at-bat. An ISO of less than .100 indicates a hitter with very little power, while an ISO of .250 or more marks the province of a true slugger.

OPS+: By now, we're pretty much all familiar with OPS, which is on-base percentage added to slugging percentage. OPS+ takes this a step or two further by adjusting a hitter's OPS to reflect park and league conditions, as all good statistics do. That is, putting up a .900 OPS in Coors Field in 2000 in quite different from putting up an OPS of .900 in Dodger Stadium in 1968.

OPS+ is scaled so that 100 is the league average. Last season, Andrew McCutchen led the NL with an OPS+ of 168, which means that his park-adjusted OPS was 68 percent better than the league-average mark. McCutchen's teammate Gregory Polanco in 2014 registered an OPS+ of 84, which means his park-adjusted OPS was 16 percent worse than the league-average mark.

OPS+ is what you call a "rate-based" statistic like batting average or ERA, which means it's not tied to playing time as WAR and other cumulative measures are.

OPS+ thinks a lot of Andrew McCutchen. As it should! (USATSI)
OPS+ thinks a lot of Andrew McCutchen. As it should! (USATSI)

Weighted On-Base Average (wOBA): wOBA takes every possible offensive event -- including a player's work on the bases -- and weights it properly with regard to each event's influence on run-scoring. For instance, doubles tend to lead to more runs than walks do, just as GIDPs tend to be more damaging than strikeouts. The final result is tweaked so that, visually, it looks like on-base percentage (i.e., a wOBA of .290 is pretty bad while a wOBA of .400 is MVP caliber). As quick-look offensive measures go, it's an excellent one.

Weighted Runs Created+ (wRC+): This one measures all phases of production at the plate and adjusts them for ballpark and league environments. The higher the wRC+, the better the hitter was. wRC+ is scaled so that a mark of 100 reflects a league-average hitter. wRC+ is like OPS+ in that regard, but it's an improvement over OPS+ because it takes into account base-running, double plays and so forth.

PITCHING STATISTICS

ERA+: This is a pitcher's ERA adjusted to reflect home ballpark and league environment. It's scaled so that a mark of 100 is league average, and the higher the mark the better from the pitcher's standpoint. An ERA+ of 110 means that the pitcher's park- and league-adjusted ERA was 10 percent better than the league mean. Likewise, an ERA+ of 90 means that the pitcher's park- and league-adjusted ERA was 10 percent worse than the league mean. In 2014, Clayton Kershaw paced the majors with a stellar ERA+ of 197.

Fielding-Independent Pitching (FIP): In general terms, FIP is what a pitcher's ERA should have been if you emphasize what's most under the pitcher's control (i.e., strikeouts and walks) and correct for things like luck, defense and sequencing. It's a good indicator of a pitcher's underlying basic skills on the mound and is better at projecting a pitcher's future ERAs than ERA itself.

K% and BB%: A pitcher's (or a hitter's) strikeouts and walks expressed as a percentage of total batters faced/total plate appearances. K% and BB% constitute an improvement over the more familiar K/9 and BB/9 in that the former aren't tied to innings and thus account for how many batters a pitcher faces (i.e., a pitcher who strikes out all three batter he faces in an inning is doing better than one who "strikes out the side" while allowing three runs in a frame, and K/9 doesn't account for such things). Last season, the average pitcher struck out 20.4 percent of opposing hitters while walking 7.6 percent of same.

Batting Average On Balls In Play (BABIP): Balls in play are fair-hit balls that don't leave the park. Typically, a pitcher's BABIP will settle in at around .290 or so. While some pitchers have some ability to control BABIP to an extent, generally at the MLB level when you see a pitcher's BABIP widely diverge from that .290-.300 range, luck -- good or bad -- is likely playing a role (in addition to the quality of the defense behind him). It's one of the first things we look at when we're trying to determine whether a pitcher's performance is sustainable.

DEFENSIVE STATISTICS

Defensive Runs Saved (DRS): Again, DRS is the defensive component of bWAR. It measures the number of runs saved above the MLB average at a given player's position and includes a "degree of difficulty" element. For instance, the less likely a play is to be made by the average fielder, the more credit a player gets for pulling it off. It's built off the Fielding Bible's plus-minus system, which you can read more about here. Per Fielding Bible, here's what goes into calculating DRS, which measures all phases of defense:

  • Plus/Minus Runs Saved (All Non-Catchers)
  • Catcher Adjusted Earned Runs Saved (Catchers)
  • Catcher Stolen Base Runs Saved (Catchers)
  • Pitcher Stolen Base Runs Saved (Pitchers)
  • Outfielder Arm Runs Saved (Outfielders)
  • Bunt Runs Saved (Corner Infielders, Catchers, Pitchers)
  • Double Play Runs Saved (Middle Infielders and Corner Infielders)
  • Good Plays/Misplays Runs Saved (All Fielders)

Defensive Efficiency Rating (DER): As team-wide defensive measures go, this one's my favorite. DER is the percentage of balls in play (i.e., fair batted balls that don't go over the fence) that a team defense converts into outs. That, after all, is the whole point of defense at the team level. Unlike the deeply flawed fielding percentage, DER accounts for range and the team-wide ability to make the routine play.

Ultimate Zone Rating (UZR): This, as noted above, is the defensive statistic used in fWAR calculations. UZR divides the field up into defensive zones and also corrects for the speed of a batted ball. It's denominated in runs and compares fielders to the MLB average at their respective positions. A full discussion of UZR is beyond the scope of this exercise, so I'll point you to this lengthy explanation by UZR's creator, Mitchel Lichtman.

Last season, Alex Gordon of the Royals led all fielders with a UZR of 25.0 -- meaning that, in the field, Gordon was worth 25 runs over and above the average left fielder. See the WAR entry above for a quick discussion of the shortcomings of defensive metrics. Those shortcomings probably aren't going away, at least until more publicly available StatCast data head our way ...

Along these lines, the Inside Edge scouting data available at FanGraphs are a tremendous addition to the sub-genre of defensive metrics.  

When it comes to these advanced baseball stats, there are others, of course. I would encourage you to poke around the FanGraphs and Baseball-Reference glossaries for more information. However, the stats detailed above are the ones you most frequently encounter in analytic circles. That's for good reason, as these measures are good at what they aim to do.

Again, stick to the concepts and benchmarks, and you won't lose your way. Most of all, think of Sabermetrics as a means to advance the conversation rather than end arguments.