Sabermetrics 201: Digging Deeper

In our first edition of sabermetrics education we covered most of the popular statistics. Here is a quick recap:

• OPS+, a ballpark and era adjusted stat that shows both how hard a player hit the ball and how often they reached base compared to league average.
• BABIP, an average that reflects how often a player reached base on batted balls that a fielder actually interacted with (i.e. no strikeouts or home runs are counted).
• RC and wRC+, the latter of which shows how well a player contributed runs to their team compared to league average.
• wOBA, a modified version of OBP that gives different value to different methods of reaching base (e.g. a single is better than a walk)
• ERA+, a ballpark and era adjusted stat that shows how well a player pitched compared to league average.
• Game Score, a rough indicator of a pitcher’s overall performance rather than just earned runs allowed.
• K/BB, an indicator of a pitcher’s control.
• WAR, a simple number that says how many wins a player contributed to a team compared to a replacement (i.e. AAA) player.

In this second edition we are going to discuss a couple more player-focused metrics as well as one team related statistic.

ISO

ISO stands for Isolated Power, and it shows how often a player hits for extra bases. The formula is quite simple: ISO = SLG – AVG. I think providing an example helps explain why this is a useful statistic. In 2019, Mets rookie Pete Alonso hit 53 home runs. His batting average was .260 and his slugging percentage was .583, giving him an ISO of .323, 76% higher than the MLB average ISO of .183. Nolan Arenado, the Rockies All-Star third baseman, also had a slugging percentage of .583, but his batting average was .315, giving him an ISO of .269. He clearly hit for average more than for power compared to Alonso (although he still had 41 home runs, tied for 6th best in baseball). Ultimately, ISO won’t show you dramatically different results than SLG, but it’s important to consider when making the batting order for a team.

WHIP

Walks plus Hits per Innings Pitched is exactly what it sounds like, and it’s an indicator of how many base runners a pitcher allows per inning. It’s useful for evaluating pitchers because of the short term nature. A walk or a hit constitutes a single play; while the rest of the fielders obviously affect this statistic, their influence is less prominent compared to ERA, as a run takes more time and more plays to happen.

FIP

FIP is short for Fielding Independent Pitching. It tries to provide a more accurate ERA by removing plate appearances affected by the rest of the defense. FIP only considers the “four true outcomes”, meaning home runs, walks, hit by pitch, and strikeouts. These are the four events that are solely controlled by the pitcher. A pitcher with a higher FIP than their ERA means they were aided by the defense.

In 2019, Cardinals starting pitcher Dakota Hudson had an ERA of 3.35, a full run under the league average of 4.49. His FIP however was 4.93 (MLB average 4.50), a difference of -1.58. This means the St. Louis defense greatly aided Hudson’s performance. This can also be seen in his K/BB rate of 1.58, the worst of all qualified pitchers last season. Don’t feel too bad though, with an ERA+ of 126 he was still considered an above average hurler!

Pythagorean Win-Loss

Baseball is a notoriously unfair sport. Even with a 162 game schedule the best teams don’t always win the most. Luck can have a huge influence on teams, sending truly inferior teams to the playoffs. How can we evaluate which teams are the best, or how do we predict their future performance? The answer is the Pythagorean Win-Loss formula. It simply converts runs allowed and runs scored into a winning percentage. The formulas is (runs scored)^2 / (runs scored)^2 + (runs allowed)^2 = win %.

In 2016, the Texas Rangers earned the AL West division title with a record of 95-67. With 765 runs scored and 757 runs allowed, their pythagorean win-loss record was 82-80, an insane 13 wins fewer than their real record! If the Rangers had gone 82-80, their division rival Seattle Mariners (86-76, one win worse than their pythagorean record) would have won the division and gone to the playoffs for the first time since 2001. (While many believe the M’s to be a perpetually unlucky team, this is not true. From 2002-2019, they won 1388 games compared to an expected 1380 games. The M’s aren’t always unlucky, they’re just bad.)

Thanks for reading this second edition of sabermetric stats explained! In the next and final entry I will discuss defensive fielding metrics that are fairly difficult for the average fan to process. Thank you to baseball-reference.com for their statistics. If you liked this article, please follow me on Twitter @LTS_tweets!