For most sports, the game tends to follow a gameplan that is directed to more in-the-moment strategies. For example, in basketball, if you want to score, you have to find a way around the opponents blocking you from the net. Most of this relies on instinct and pure agility to get around your opponents. The same applies for football, where a quarterback will throw to the receiver farthest from the defense, not the receiver that specifically has the most catches or the most yards. In baseball, it’s a bit different.

In recent years, sabermetrics,  which by definition is the statistical analysis of baseball data, has transformed baseball as we know it. No longer is it a game of just trying to score the most runs and hoping to be the team with the most luck in regards to the seemingly random outcomes in baseball (ex: trying to hit a 95mph fastball with a round bat doesn’t offer the best odds for success). Coaches and front offices have long given up on that belief. Instead of relying on the favor of the baseball gods, many, if not almost all, organizations have turned to a heavy use of sabermetrics use to determine practically everything from how far off the bag a baserunner will stand to how many pitches (almost to the exact number) a pitcher will throw.

For example, there currently is a statistic that can accurately measure the value of a starting player compared to their replacement. It’s called Wins Above Replacement (WAR, for short). It’s represented in a pretty simple manner, with a positive WAR representing a positive net amount of wins, a 0 WAR representing, obviously, no positive/negative value to a team’s wins, and a negative WAR representing that that player has cost the team wins, as opposed to if they had that players’ replacement in the field. While some may already be overwhelmed by the extensively analytical attributes of WAR, you’ll be interested to know that WAR can actually be broken down into sub-groups dedicated to analyzing specific players. Those sub-groups include (but are not limited to, due to the significant amount of them) waaWL% (the win-loss record set to the standard of an average team in the games that only that player plays in), 162WL% (waaWL% but extended for an entire season), oWAR (WAR, but with fielding/defense not accounted for), and dWAR (WAR, but with offense/hitting not accounted for). That’s just the tip of the iceberg.

If you’re interested in seeing the full statistical spread for a player, check out Giancarlo Stanton, right fielder for the Miami Marlins and primarily known for his power hitting, on ( They have every possible breakdown to analyze Stanton, from his WAR (and several sub-groups) to how many runs he was worth over a 1200 inning span (roughly 135 games). After looking over that page for any player, one might feel like they’re best friends with the player, simply with how much analysis has been done on his performance.

One may assume that these statistics are for the armchair GM, who obsesses and perfects his fantasy roster. That would be absolutely wrong. The use of the statistics are widespread, from the actual GM’s office to the dugout on the field, these statistics are in use in some manner or form. From setting up a shift (aligning your the players on the field in practically any location, regardless of position, in order to prevent a hit) to determining what pitch to throw on a 2 ball-2 strike count, sabermetrics finds prominence in baseball.

As one would expect, many baseball traditionalists are voicing concern over these seemingly obsessive and minute analytics of the game, believing that they block the actual game and instead set up a Stats 101 class on the field. While there certainly is validity to that argument, baseball needs sabermetrics and, obviously inferred by the definition, sabermetrics needs baseball. The game being played in 2015 is not the game that was being played even 20-30 years ago. In such a society we live in today, with the concentration that many hold on perfecting their ability or abilities, the baseball players of today are truly the best baseball players in the world. This isn’t just applicable to the top major league level players, which would have been the case 20-30 years ago. Not at all. If you are ever on a cross country road trip and happen to stop in a small town like Kingsport, Tennessee or even a big city like Charlotte, North Carolina (both the respective homes of the Rookie League (lowest level in MLB) New York Mets and the AAA-level Chicago White Sox), sit in for a few innings. The baseball you will watch will still be of almost the highest caliber on the planet. The difference between the players in the minors and the players in the majors are incredibly minute. It’s the fraction of a second difference between when the batter decides to swing or the one or two pitches a pitcher throws that he should not have. Fractional. Seemingly irrelevant. But they are. Because in this day, as opposed to the past, baseball is a game of perfection. As opposed to football or basketball, where you can drop the pass or bounce it off the rim, there isn’t room for that in baseball. For every mistake you make, there is a player a level down from you who made it and is willing to take your spot in a heartbeat.

That level of perfection and of heavy analysis to determine the minute details and distinctions between the best baseball players the world has to offer is why baseball needs sabermetrics. As previously noted, the level at which baseball is being played today does not have room for subjectivity or opinionated choices. It needs a uniform level of objectivity. The sport needs to be able to determine how many wins a player is worth and the statistical chance of a pitcher giving up a homerun. Regardless of what caused it to be such an incredibly competitive environment , that is how baseball must operate.

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