Advanced Stats from 30,000 Feet

Here at the General Store we try to stay on the #cutting #edge with our baseball analysis, using the best available metrics to describe the performance of players and teams. Some of these new statistics are quickly becoming common in the baseball lexicon, while others may still be less familiar. I want this to be an easy and accessible resource, so I’m keeping it extremely simple and will not be backing up any of my bold claims. But for those who may need more convincing before abandoning their current tools for these shiny new ones, I will be linking to other resources that provide additional depth in their explanations. It’s not that we think conventional stats are evil or “wrong”, it’s that the stats presented here tell a more complete story of a player’s performance while still being simple and accessible. If there are any other stats that you see us use often but aren’t found here, please comment on this post or send us a tweet and we’ll add it.


Wins Above Replacement (WAR) is an estimate of a player’s value in terms of wins. It incorporates all aspects of a player’s performance, evaluates his performance relative to his position, and compares it to a baseline (or “replacement level” player). You can think of a replacement level player as a good AAA guy who’s not quite good enough to be an everyday guy in the majors. Thus, a player’s WAR is how many more games a team can expect to win by playing him rather than one of these replacement guys.

Because it evaluates everyone on the same scale (wins), it allows us to compare players at different positions, including pitchers to position players. No other metric combines defense, baserunning, and hitting,  nor does any other metric allow you to compare pitchers to hitters. There are currently three different versions of WAR available to the public, which may sound confusing at first. The one used by FanGraphs is denoted fWAR, Baseball Reference’s is bWAR, and Baseball Prospectus’ is WARP. All are doing the same thing but use slightly different adjustments for some of their estimates. They generally agree, but for consistency’s sake when we refer to WAR we are referring to fWAR unless specifically noted otherwise. This is mainly because FanGraphs has the most easily navigable website of the three.



Weighted On Base Average (wOBA) is simply a measure of a hitter’s performance at the plate. It should be used in lieu of batting average (AVG), on base percentage (OBP), and slugging (SLG). As a rule of thumb, a wOBA of around .320 represents an average hitter. Around .360 represents a solid all-star level hitter, and .400 and higher represents an elite level hitter.


Weighted Runs Created Plus (wRC+) is based on wOBA but makes contextual adjustments for the park and league that a hitter played in. For example, balls travel farther off the bat in Colorado than in Atlanta due to the altitude difference, so you would have to make appropriate adjustments if comparing Rockies hitters to Braves hitters. The great thing about wRC+ is it is scaled to league average (hence the +), so a 100 wRC+ always represents an average hitter. A player with a 110 wRC+ has been 10 percent better than average, a player with an 80 wRC+ has been 20 percent worse than average, and so on and so forth. Because of the adjustments and the scaling making it easy to understand and compare across leagues and eras, this is my go-to hitting statistic.


Batting Average on Balls In Play (BABIP) is simply the percentage of balls put into play that fall for a hit. Note than home runs do not count as balls in play. While batters do have some control over their BABIP based on how they hit the ball and their speed, there’s also a fair amount of randomness and luck involved, thus expect us to discuss a player’s BABIP in reference to how much of his hitting performance has been due to luck.


Isolated Slugging (ISO) is a player’s batting average subtracted from his slugging percentage. It’s a quick and easy way of measuring how well a player hits for power. As of this writing, Giancarlo Stanton leads the majors in ISO since 2014, and Ben Revere has the lowest ISO over the same time frame.



Fielding Independent Pitching (FIP) measures a pitcher’s performance on the same scale as ERA. It gives pitchers credit for their ability to generate strikeouts and limit walks and homeruns, and it operates under the assumption that pitcher’s don’t have much control over the sequencing of events and that the only control they have on batted balls is whether it’s a ground ball or a fly ball. While this isn’t completely true for everyone (ever heard of Greg Maddux?), it is closer to the truth than saying pitchers have complete control over the outcomes of batted balls, which is what ERA assumes.


Expected FIP (xFIP) is the same as FIP, but instead of giving a pitcher credit or blame for the number of home runs he allows, it assumes whether or not a fly ball becomes a home run is outside of his control. Like FIP, it’s not perfect, but it’s good to use when you only have a small sample of innings to make an assessment on a pitcher.


Stats with a “-” are similar to stats with a “+”, which we discussed above with wRC+. Whereas with a “plus” stat, values greater than 100 represent above average performance, values less than 100 represent above average production for “minus” stats. For example, an FIP- of 80 represents a performance 20 percent better than league average, while an FIP- of 115 represents a performance 15 percent worse than league average.


Wait a second, we already talked about BABIP? Well, here we are again, as BABIP is good to use for pitcher’s, too. Just as a hitter with an extremely high BABIP may be getting lucky, a pitcher with an extremely high BABIP against him may be getting unlucky. It’s a great diagnostic tool to see if a pitcher’s ERA is a cause for concern or not.


Left On Base Percentage (LOB%) is another diagnostic tool for determining if a pitcher has been good or lucky. It measures the percentage of batters who reach base against a pitcher but never score. While better pitchers will obviously leave more guys stranded, extremely high or low LOB% could indicate a pitcher was getting unlucky in the sequencing of events. For example, two pitchers who both allowed 10 baserunners and 6 strikeouts in a game probably performed equally well. But if for one pitcher all 10 of those baserunners reached in the same inning, his runs allowed would make it look like he performed significantly worse than the other guy, when in reality he probably just had one unlucky inning.

K/9, BB/9, HR/9

Strikeouts, walks, and home runs per nine innings pitched. Doesn’t get more straightforward than that.



Both Defensive Runs Saved (DRS) and Ultimate Zone Ratings (UZR) estimate how many runs a player saved with his defense based on the difficulty of the plays he did or did not make. These are better than Errors or Fielding Percentage as neither of those take into account a player’s range, which is one of the most important factors in defense.

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