I’m not going to force numbers on you. I’m not going to take the effort, the love, the tenacity that baseball players pour into each and every game and throw it out the window. That being said, I’m also not going to let you tell me the only thing that matters is a guy playing really hard, getting his pants dirty, feeling like he “left it all on the field”, resulting in a genuine desire to win a baseball game; A desire more sincere than his counterpart. That’s foolish. Travis Wood doesn’t look Starling Marte up and down thinking, “I want this so much more than Starling. He doesn’t have a damn chance.” Both guys — ALL THE GUYS — are getting paid to play baseball. If you’re taking the field without the desire to win, it’s a character flaw and has nothing to do with the game itself. But who’s to say we can’t have a fair balance of both? Who’s to say we can’t watch Aaron Rowand circa 2001 knocking over anything and everything on his way to a measly infield single while also enjoying the intricacies and nuances behind why Mariners’ ace Hisashi Iwakuma probably deserved the AL Cy Young over the Tigers’ Max Scherzer?
No one, that’s who.
So, that’s what we’ll do. Throughout the 2014 MLB season, the Standby blog will be the only place you should go for a healthy mix of unadulterated baseball and the advanced analytics behind it. But first, you’ll need to know some of the basic sabermetrics used in today’s game:
OPS/OPS+: Odds are, you’re familiar with OPS on its own. The most simplistic of new-age advanced metrics, it takes the sum of a player’s on-base percentage (OBP) and slugging percentage (SLG%), combining it into an easy to read number. But just to show you how quickly the field of sabermetrics is advancing, many saberists already discredit OPS. Although an easy statistic for fans to understand, it treats OBP and SLG% equally, when data shows OBP to be worth roughly two times SLG% when it comes to the production of runs. That’s where the “+” comes in. It must be noted that nobody plays in the same environment all the time. The playing field is not level. So, OPS+ adjusts for these variables that might affect OPS scores, such as ball park effects and difficulty of the opposition. A 100 OPS+ is league average, and each point up or down is one percentage point above or below league average. In other words, if a player had a 90 OPS+ last season, that means their OPS was 10% below league average.
BABIP: Batting Average on Balls in Play (BABIP) is just what it sounds like. When a hitter puts the ball in play, he will either reach base safely or return to his respective dugout. It’s safe to assume that around 30% of balls hit in fair territory will go for a hit. The variables that contribute to that 30% and the remaining 70% are as follows:
Defense: The one thing players don’t have control over is the defenses they’re facing. A line drive is shot down the third base line, but Orioles phenom Manny Machado’s heels are dug in. The likelihood he fields that ball is high, but not determined at all by the hitter. The same could be said for the opposite.
Luck: This is the main variable fans think of when discussing BABIP. Regardless of the defense’s skill, bloopers happen. And on the contrary, lesser defensive players make plays that maybe they shouldn’t.
Phases and Adjustments: Over the course of a season, players find themselves making many changes. Whether said changes are to their physical approach, their mindset in the batter’s box, or the mechanics behind their swing, players adjust. And with positive changes, you’re most likely hitting the ball harder and making contact more often. Both of those things would point to a player having a BABIP higher than normal, as harder hit balls have a much greater chance of falling for a hit.
The average BABIP for hitters is around .290 to .310. If you see any player that deviates from this average to an extreme, they’re likely due for regression.
ISO: Isolated Power (ISO) quite simply measures a hitter’s raw power. Or, taking a look from a different angle, measures a player’s ability to hit for extra bases. The simplest way to calculate ISO is to subtract a player’s Batting Average (BA) from their SLG%, leaving us with that player’s extra bases per at bat. Or if you want to get fancy, go ahead and calculate ISO this way:
ISO = ((2B) + (2*3B) + (3*HR)) /AB ISO = Extra Bases / At-Bats
ISO requires a larger sample size than most advanced metrics. For example, if Albert Pujols has a .550 ISO (Like that would ever happen, amirite?) two weeks into the season, it’s way too early to expect that to continue.
Lots of numbers, I know. And I did say up top that I’m not going to force them on you. This is a friendly place for all baseball fans to hang out. Whether you like a player who grinds out at bats or you like the guy who is relatively unknown but whose numbers jump off the charts, I’m going to address it. Sit back, relax, and strap it down; We’re going for a ride.Shane is a co-host and producer for both “Nothin’ But Net” and “The Baseball Show” on WCRXFM and WCRXFM.com. Listen on Tuesday nights from 7-9pm and to the Baseball Show on Saturday mornings at 9am . Follow Shane on Twitter: @Shane_Riordan