Sabermetrics provide more efficient way to analyze player performance

The way sports teams scout athletes is always changing, but baseball is changing more than any other sport from a statistical standpoint.

It could be argued that Michael Lewis’ book “Moneyball: The Art of Winning an Unfair Game” paved the way for a new way to analyze and scout players.

Based on Major League Baseball’s Oakland Athletics early 2000s teams, the book focuses on how the team found success despite having one of the lower budgets in the game.

It tells the story of how the team stopped stealing bases, tried to get on base more and found different ways to create runs.

Because of the team’s success, a plethora of new statistics soon rolled in, providing teams across the MLB new ways to build rosters.

These new stats are called sabermetrics, coined by Bill James, Boston Red Sox senior adviser on baseball operations.

Sabermetrics provide a more scientific way to look at players’ value, as opposed to the old stats, such as batting average, earned run average (ERA) and win/loss records.

Batting average and ERA are OK stats to evaluate players, but they are not as good as the sabermetric stats, whereas judging a pitcher’s win/loss record is a horrible way to evaluate a pitcher because a game’s outcome doesn’t fully rely on his performance.

Judging a pitcher by his win/loss record shows a pitcher can have a 20-11 record. Twenty wins in baseball is a “good stat,” but what if the pitcher has a 4.12 ERA?

This shows the offense scored a lot of runs on days the pitcher started, but he also gave up a lot of runs, which is not good.

I would rather have a guy with a 2.93 ERA and a 13-12 record, because that means he pitched well enough to get a win, but his team didn’t score enough runs or the bullpen blew the game.

I’m not saying losing 12 games is great, but a pitcher is not likely to get the same amount of run support every game.

This is where fielding independent pitching (FIP) comes in.

Fielding independent pitching does not rely on the defense’s fielding ability.

The formula for FIP is ((13 times the number of home runs) plus (three times (walks plus hit by pitch)) minus (two times strikeouts)) divided by innings pitched plus constant.

I’ll use a constant of 3.10 and use UCA junior pitcher Connor Gilmore to calculate his FIP as an example.

Last season, Gilmore finished with a 2.98 ERA and 102.2 innings pitched. He gave up four home runs, walked 40 batters, hit eight and struck out 53.

Using the FIP formula, Gilmore gave up about 3.98 earned runs per game, but defense and good luck helped his ERA.

That’s not to say Gilmore wasn’t a solid player last season, but he didn’t have as good a season as his ERA shows.

However, he is due for progression this season.

Batting average of balls batted in play (BABIP), wins above replacement (WAR) and weighted runs created (wRC) are better stats to judge a player.

At the collegiate level, WAR isn’t as important as it is at the major league level because it’s hard to justify who is an average player because of lineup changes.

According to, BABIP measures how often a ball in play goes for a hit in fair territory.

One of the more important stats to measure offensively is wRC because it calculates a player’s offensive value and measures it by runs.

Watching the UCA baseball team over the past few seasons, I have noticed the team uses some sabermetric strategies, which has helped.

The team has reached back-to-back Southland Championship games.

It helps the team get on base, which helps tremendously because it puts players in position to score more easily.

The team’s strength is wearing out the opposing pitcher by taking so many walks.

Traditional baseball purists may stick with old stats, which is fine, but the way the game is changing, those stats might not be around forever.

Classical theatrical drama gives historical understanding

Previous article

Stellar season from Eli Manning makes him elite NFL quarterback

Next article

You may also like