Baseball Sabermetrics Trivia Quiz

Answer: Batting Average on Balls in Play

There are three main variables that influence BABIP, the defense, luck, and talent level. If a player hits a ball towards third base, the difference between the fielding capabilities of the third baseman, where they are playing on the field, and the speed and bounces of the ball can all affect the hitters batting average by a great deal. An average BABIP is between .290 and .310. If a player has a higher or lower BABIP, it means that the player will regress back to their career BABIP rate eventually.

A hitter can slightly control his BABIP based on speed. A more speedy player can beat out groundballs for hits, where another might not.

Answer: Walks + Hits / Innings Pitched

A more common sabermetric, this stat shows exactly how many baserunners a pitcher allows. It is known by many baseball statisticians as a poor judge on how well a pitcher is, because the defense usually determines what a hit is. Pitchers do determine a walk, based on how and where they throw. An excellent pitcher will have a WHIP just above 1, where a bad WHIP is usually around 1.8.

Answer: On Base Percentage

A more easier stat for average baseball fans, OPS stands for On-Base Plus Slugging, and combines a player's On Base Percentage and his Slugging Percentage. Traditionally, the best hitters in Major League Baseball will have an OPS of around 1, where an average ball player's OPS will be around 0.7.

Answer: runs

Weighted Runs Created, and the more in depth Weighted Runs Created+ try to determine how many runs a player was worth to his team, other than saying his complete statline to get an idea. The stat is based off of Weighted On Base Average. wRC+ sets the league average at 100 runs created, and adjusts player's stats based to that. If Player X's wRC+ is 120, that means he is 20% better than the league average. If Player Y's wRC+ is 75, he is 25% worse than a league average.

Answer: ERA

Most pitcher's FIP's are close, sometimes even the same as their ERA's. The formula for FIP is [(13HR)+(3BB)-(2K)] divided by Innings Pitched and then plus 3.1, to come close to an ERA. FIP is one of the mainstays among statisticans in sabermetrics. xFIP is similar to FIP, just Home Runs is substituted with expected home runs, using a home run per fly ball ratio of 10.6%.

The stat is used as a predictor of how a pitcher is going to fare in the future.

Answer: WAR

WAR, or Wins Above Replacement determines how many wins a player was worth to his team, compared to a replacement level player, or a minor leaguer. Ways to calculate someone's WAR varies, but stats from fielding, hitting, and baserunning all play a factor. Over his career, Babe Ruth's WAR was a combined 177.7 wins above replacement, including 15.4 wins in the 1923 season alone.

Answer: Coors Field (Colorado)

Based on the elevation that Coors Field is at in Denver, the ball travels much farther off the bat then anywhere else. Estimates show that the ball travels 9% farther than anywhere else, and that a 400-foot shot at sea level, could go upwards of 440 feet in the Mile High City. Based on this, sabermetric stats are usually adjusted so that players, regardless of team, and stadium, are on a level playing field for evaluation.

There is no real exact formula to remove park factors, because there is no specific way to measure it.

Answer: False

The stat stands for Home Runs per Fly Ball, and is used as a sabermetric to determine a player's luck in terms of power. An average HR/FB rate is around 10-15%, so a players percentage can tell you if he is getting lucky based on park dimensions, or on a hot streak. Along with BABIP, it is the two main factors in determining if a play is lucky or unlucky.

Answer: Pythagorean Expectation

This stat is used to show how lucky a team is, as a group. The use of squared (therefore the Pythagorean Expectation) is questioned, as many statisticans are trying to find the perfect exponent, 1.83 is used by some websites to determine it. This stat has also been adapted to football and basketball to determine wins, compared to points scored.

Answer: Billy Beane

"Moneyball: The Art of Winning an Unfair Game", a 2003 book written by Michael Lewis, looked into how Beane built his organization, based on sabermetric stats, which led to the 2011 movie. The movie starred Pitt as Beane, and Jonah Hill, a young Yale graduate who introduces Beane to these advanced statistics. Former shortstop Royce Clayton played Miguel Tejada, and players like Johnny Damon and Matt Stairs played themselves.