Advanced baseball statistics can be hard to understand and often contain more acronyms than the New Deal. Here is a list of 12 terms that are widely used with an explanation of what they measure.

WAR (or WARP, wins above replacement player)

WAR attempts to encapsulate the value of all players across all positions for a season: How much better or worse is a player than a theoretical call-up a team has waiting in the wings? And how many wins did he add to his team’s total that season compared to if he wasn’t in the lineup? It takes into account a player’s offense, defense and base running. Pitchers’ WARs have their own metrics. Three websites, Fangraphs, Baseball Reference and Baseball Prospectus, have different variations of this statistic. They differ the greatest in what metrics (some of which are on this list) they use to calculate a player’s defense and how they evaluate pitchers. So a player’s WAR on one website can be different than the others.

Good, bad and average: These are the general ranges across each version of WAR -- below 0 is replacement level; 0-2 is a bench player; 2-5 is a starter; 5-8 is an All-Star and above 8 is MVP-worthy.

Examples: Mike Trout of the Angels leads the majors with a 6.3 WAR, according to Fangraphs, and Eddie Rosario leads the Twins with a 3.6 WAR (13th in MLB). Joe Mauer’s WAR this season is .5; during his 2009 MVP season it was 7.6.

OPS (on-base percentage plus slugging percentage) and OPS+ (OPS plus)

– it simply adds a player’s on-base and slugging percentages together to show how often he reaches base and hits for power. OPS+ makes small adjustments to OPS and scales it to a more easily digestible number with 100 being the league average and each point up or down being 1 percent better or worse than league average.

Good, bad and average: That changes by year, but according to Fangraphs, an OPS of .570 and below is awful, .600 is poor, .670 is below average, .710 is average, .800 is above average, .900 is great, 1.000 excellent. For OPS+, 150 and up is excellent. 125-150 is very good. Below 75 is poor.

– and just misses the top 10 – with his .924 number.

wOBA (weighted on-base average)

This is a more refined statistic that attempts to improve on OPS. Instead of counting the value of a double as twice that of a single (as slugging percentage does), wOBA attempts to use that actual mathematical value of each outcome at the plate (walks and hit batters included) in how it usually contributes to scoring a run.

Good, bad and average: The average changes by season, but these are generally the accepted ranges, according to Fangraphs: below .300 awful; .300 to .310 poor; .310 to .320 below average; .320 to .340 average; .340 to .370 above average; .370 to .400 very good; .400 and up is excellent.

Example: Betts leads MLB at .458 with Trout at .450. Boston’s JD Martinez is third at .428, giving the Red Sox two of the top three players in that statistic. Rosario again leads the Twins at .385, 15th overall in MLB.

wRC (weighted runs created) and wRC+ (weighted runs created plus)

Updates a statistic Bill James devised called runs created. It uses a player’s weighted on-base average to determine a player’s offensive value and measure it in runs. wRC+ takes every outcome a hitter had and adjusts for the park he was playing in and how the rest of the league was scoring that season. Similar to OPS+, wRC+ uses a scale with 100 as the league average.

Good, bad and average: For wRC+, 60 is awful; 75 is poor, 80 is below average, 100 is average, 115 above average, 140 great, 160 is excellent.

Example: Trout leads here at 196. Betts isn’t far behind at 195. Rosario leads the Twins at 146, good for 16th.

Exit velocity

How hard the ball is hit off the bat, in miles per hour. This was introduced in 2015 with the launch of MLB’s Statcast, the technology that provides a lot of advanced data.

Good, bad and average: Anything 95 miles per hour and above is hard hit. Most home runs are around the 100 miles per hour mark or greater. The hardest hit ball this season was 121.1 MPH by Gary Sanchez of the Yankees. Anything from the mid 80s to 90 is moderately hit and the low 80s and below is not that hard and unlikely to result in a hit.

Example: The hardest hit home run for the Twins this season was a two-run blast from Miguel Sano on April 25 at Yankee Stadium. Sano hit the ball 440 feet at 114.6 MPH off the bat.

Launch angle

The angle at which the ball comes off the hitter’s bat, with the point of contact serving as the vertex of the angle. MLB also introduced it with Statcast technology in 2015. Players in recent seasons have tried to raise their average launch angle in an attempt to hit more home runs.

– a line drive with a little bit of lift. Anything in that area, provided it has a hard-hit exit velocity, is likely to result in an extra-base hit or a home run. When the launch angle and exit velocity are in such a positive correlation, it’s referred to as a “barrel.”

Example: Eddie Rosario’s 18 home runs have an average launch angle of 33 degrees. His highest was 42.4 degrees, his lowest was 24.7.

BABIP (batting average on balls in play)

This statistic only focuses on balls a batter puts in play. It does not take into account home runs. It shows how often a batter gets a hit when he puts the ball in the field of play. It can also be used to evaluate pitchers to see what their batting average of balls in play is against them. You can use BABIP to determine how lucky or unlucky a hitter is. If a hitter has a high BABIP, it usually means he’s getting lucky. If it’s low, he might be unlucky. This works in reverse for pitchers.

Good, bad and average: The league average tends to be around .300, but you have to take into account each individual when using BABIP. For example, if a hitter has had a career .280 average BABIP but in a given season it’s .330, that might mean he is getting a bit lucky. Or maybe he’s hitting the ball harder. You can then use his average exit velocity to see if that’s the case. For pitchers, a lower BABIP than their career averages may mean they are benefiting from luck or good defense or maybe they’re inducing softer contact.

Example: Eduardo Escobar hit just .279 on balls in play last season but that number improved to .327 this season. Escobar has also raised his hard contact rate by eight percent. It’s one reason Escobar has been so successful through the first three months.

Catch probability

According to, it’s “likelihood that a batted ball to the outfield will be caught, based on four important pieces of information. 1. How far did the fielder have to go? 2. How much time did he have to get there. 3. What direction did he need to go in? 4. Was proximity to the wall a factor?”

Good, bad and average: Every fly ball gets assigned a catch probability percentage. MLB has a star-rating system for each catch. Catches with a 0-25 percent catch probability is a five-star play; 26 to 50 is four star; 51 to 75 percent is three star; 76 to 90 is two star; 91-95 percent one star.

Example: Byron Buxton led baseball in 2017 with 16 four-star catches and was tied for second with five five-star catches.

UZR (ultimate zone rating)

This attempts to quantify how many runs a fielder saved because of his range, their arm strength (for outfielders) and double plays turned (for infielders). It attempts to quantify every batted ball event in terms of the amount of effort it would take an average fielder to make the play. Its calculations vary by position. Another related statistic is defensive runs saved (DRS).

Good, bad, average: Per Fangraphs, the scale for both UZR and DRS is: -15 awful; -10 poor; -5 below average; 0 average; +5 above average; +10 great; +15 Gold Glove caliber.

Example: This is a statistic that accumulates throughout the season. Kansas City outfielder Alex Gordon leads MLB at 9.7. Rosario leads the Twins at 3.5. Buxton was seventh in baseball last season at 10.0.

FIP (fielding independent pitching)

A metric similar to ERA, but FIP uses all the batted ball events within a pitcher’s control (the amount of strikeouts, walks, hit by pitches and home runs allowed) and puts them into a complicated formula to show how a pitcher would perform regardless of the defense behind him.

Good, bad and average: The numbers compare to ERA. FIP can be helpful if there’s a significant gap between a pitcher’s ERA and his FIP. If his ERA is lower than his FIP, it could suggest he has been a bit lucky and had good defense behind him. If his FIP is lower than his ERA, he might be getting unlucky.

Example: Lance Lynn had an ERA of 3.43 and FIP of 4.82 with the Cardinals last season. Even though his ERA is worse this season (5.49), his FIP is actually better (4.38). However, his hard contact rate has risen from 29.2 percent to 35.9 percent.

WHIP (walks plus hits per innings pitched)

It adds together the walks and hits a pitcher allows to give you an indication of how often a pitcher allows base runners in an inning. Whether it was a walk or a home run, each time a batter reaches base is treated the same.

Good, bad and average: WHIP varies by season, but according to Fangraphs a general guide is this: 1.6 awful; 1.5 poor; 1.4 below average; 1.3 average; 1.2 above average; 1.1 great; 1.0 excellent.

Example: Justin Verlander leads MLB with a 0.86 WHIP. Jose Berrios is tops on the Twins at 1.00.

Spin rate

How much a ball spins out of the pitcher’s hand to home plate. It is measured in revolutions per minute. Data has suggested that fastballs and breaking balls are harder to hit when they have a high spin rate, which can create more movement on the pitch.

Good, bad, average: It varies by pitch. For a four-seamer, the average in 2016 was around 2,226 rpm; two-seamer was 2,123; splitter 1,524; changeup 1,746; slider 2,090; curveball 2,308.

Example: Cubs reliever Carl Edwards Jr. has the highest spin rate in baseball among all fastballs at 2,663 RPM. Ryan Pressly is tops on the Twins at 2,561 RPM.