Explaining Sabermetrics: 10 Stats You Need to Know

More than any other sport, baseball is defined by statistics. Off the top of your head, you may not know how many touchdowns your favorite quarterback threw this season, or how many three-pointers Steph Curry made this year. However, I can almost guarantee that most baseballs fans can tell you how many home runs their team's 1st baseman has this year. Despite the historical emphasis on statistics in the game, baseball has been famously stubborn in welcoming new statistics onto its portfolio. Players have always been judged the same way, and baseball seems reluctant to change the way things have always been. However, over the last 15 years or so, there has been a revolution in terms of statistics in baseball, where new ways of measuring player's performance are becoming as popular as the traditional statistics. These new player evaluation tools are called sabermetrics.

Before I discuss the intricacies of sabermetrics, I should explain why they are needed in the first place. For decades, two stats have dominated player evaluation. For batters, that stat is Batting Average. Batting Average is extremely simple: you just divide the number of hits a player has by the number of at-bats that he has. So, for example, if a player has 150 hits in 500 at-bats his Batting Average would be .300. While Batting Average (BA) was its uses, it is a very narrow-minded way of looking at a player's contributions. For example, a player might have a very high BA of .350, but that does not tell us anything about the quality of that player's hits. If all of the player's hits are singles, then he is not a very effective player, despite his high BA.

For pitchers, they have always been judged by their Earned Run Average (ERA). ERA is not as weak of a stat as Batting Average, but it too does not tell the whole story about a pitcher's contributions. ERA only calculates how many earned runs a pitchers allows per every 9 innings that he pitches. Now, a pitcher's job is to allow as few runs as possible, so in many ways ERA can tell you a lot about a pitcher. However, ERA also leaves a lot to be desired. It is more than possible for a pitcher to be ineffective, yet still have a good ERA, if he is fortunate enough to have good luck. Good luck for a pitcher could entail batters hitting the ball hard right at fielders. A low ERA could also be the product of pitcher having a great defense behind him, while a more effective pitcher with less luck might have a higher ERA if he plays for a bad defensive team. Again, ERA can be very useful to judge a pitcher's performance, but their are other statistics that give you a better idea of how he is actually performing.

It is a common misconception by older baseball fans that sabermetric stats are here to replace traditional stats like BA and ERA. As a result, they refuse to accept these stats as legitimate barometers for player performance. This is a shame, because they are completely missing the point of what sabermetrics are for. Sabermetrics are used to support traditional baseball stats, not replace them. They are designed to fill in the hole that are left open by stats like BA, ERA, and fielding errors. I strongly encourage anyone who is interested in baseball to take the time to learn the basic sabermetrics stats. So, without further ado, here are the 10 sabermetric stats that every baseball fan should be familiar with:

1. Wins Above Replacement (WAR) is a stat designed to combine all of player's contributions into one stat. The resulting number is how many wins a player will add to their team compared to a replacement player (a replacement player is typically understood to be a below-average player). So for example, a player with a 3.2 WAR is worth 3.2 more wins to his team as opposed to a replacement-level player. In regards to WAR, 2.0 and above is considered to be a starting-caliber player, while 5.0 ad above is considered to be all-star worthy
2. On Base plus Slugging Percentage (OPS) is unique in that it combines two traditional stats (on base percentage and slugging percentage) into one new stat. The stat is very simple as it just adds the two percentages together. So an player with a .350 OBP and a .450 SLG will have an .800 OPS. OPS is a great barometer for a player's offensive contributions, it counts how often the player gets on base and how many bases he gets on his hits (a double, for example, is more valuable than a single).
3. OPS+ is very similar to OPS, except that it is ballpark-adjusted. This means that the stat is adjusted to incorporate the effect that ballparks have on the player. For example, Yankee Stadium is widely considered to be beneficial to hitters, while Petco Park in San Diego is considered to be a pitcher's park. So if a player on the Yankees and a player on the Padres each had an OPS of .800, the player on the Padres' OPS+ would be higher because he plays in a more difficult ballpark. The league-average number for OPS+ is always 100, so anything above that is above-average, and vice-versa.
4. Weighted Runs Created Plus (wRC+) measures how many runs a player creates for his team in comparison to other players. Similar to OPS, it combines a player's ability to get on base with his ability to hit for extra bases. However, unlike OPS and OPS+, wRC+ places more value on simply getting on base, whereas OPS values the quality of those bases (with singles and doubles being less valuable than triples and home runs). Similar to OPS+, the league average for wRC+ is always 100, and it is weighted in regards to ballpark factors. So, a player with a 150 wRC+ will produce 50% more runs than a player with a 100 wRC+.
5. Batting Average on Balls in Play (BABIP) is a simple, yet very useful stat. Simply put, it shows the batting average that a player has on balls that he makes contact with. So for example, strikeouts are not included in this statistic. BABIP is useful because it shows how lucky a player has been, which standard BA will not show. So, if a players BABIP is significantly higher than his standard BA, it probably means that he has been extremely lucky and is due for a regression.
6. Earned Run Average Plus (ERA+) is a stat that puts a pitcher's ERA in the context of the ballpark that he pitches in. Obviously, a pitcher who pitches in a bigger ballpark will benefit from that ballpark. So, ERA+ helps judge how good a pitcher has been while including the factor of the stadium that he pitches in. The league-average for ERA+ is always 100.
7. Fielding Independent Pitching (FIP) is a stat that helps fill in the holes left by ERA. As stated before, a pitcher can benefit or suffer from the defense around him, so FIP completely eliminates fielding from the equation. FIP measures a pitchers ability to strike out batters, while preventing home runs, walks, hit-by-pitches, and strikeouts. Pitchers generally do not have control over balls that need to be fielded, so FIP tells us how good a pitcher is at controlling the outcomes that only he can affect.
8. Walks and Hits divided by Innings Pitched (WHIP) tells us how good a pitcher is at preventing baserunners. As a general rule, a pitcher will be more successful if he allows less baserunners. In a similar way to FIP, WHIP offers an alternative to ERA to see how effective a pitcher has been, and if he is due for a regression. So, for example, if a pitcher has a low ERA and a high WHIP, he is almost certainly due to regress. 
9. Ultimate Zone Rating (UZR) is a stat designed to measure how good of a fielder a player is. Historically, a player has always been judged on his fielding by his fielding percentage. However, fielding percentage is probably the worst stat in sports, as it only factors plays in which a fielder reaches the ball. Fielding percentage does not count balls that player should have gotten to, so it is essentially useless. UZR attempts to combat this problem. UZR divides the baseball field into zones, and assigns each player on the field as being responsible for every ball hit in that area. So, UZR is calculated by determining how many plays a player successfully makes in his zone on the field. The average for UZR is always 0, so anything above that is considered to be above-average. 
10. Defensive Runs Saved (DRS) is very similar to UZR in that attempts to calculate how good of a fielder a player is. However, DRS calculates how many runs a player saved or cost their team on defense relative to an average player. The calculation of DRS revolves around the difficulty of plays that a player makes. So for example, if he makes an incredibly difficult catch, his DRS will go up. If he makes a routine play, his DRS will be unaffected.  If he misses an easy play, his DRS goes down significantly. However, if he misses a very difficult play, his DRS will go down only slightly. Like UZR, the average DRS is 0.