The modern baseball fan ventures to the world wide web, routes their machine to www.baseballsavant.mlb.com and pulls up an advanced scouting report along with advanced statistics on any player desired. This tool for the common man epitomizes the age of baseball we are in. Every movement, play, and outcome are scrutinized like never before. The game is entrenched in an analytic revolution. It essentially can be played on a computer. What if I told you that this was still not enough? Despite the focus on numbers, outcomes, and scrutiny on every movement, there is still hidden value being missed by the numbers. The next stage of the baseball statistical revolution is in relational analytics. Studying this, will lead organizations to become more economically efficient. They should not only be focused on capturing the “what” but also on the journey, or the “how.” Using this process enhances cost-savings and evens the playing field when your organization may have less resources to work with. In comparison analytics, the goal is cost-effectiveness while finding the same production on the field.
In my previous article (found here: https://wisedudesports.com/the-ops-debate/), I discussed the importance of on base plus slugging percentage in evaluating a productive offensive player. This is a perfect example of putting relational analytics to use. There are many different ways a player can achieve a high OPS. For example, the high power, high walk, high strikeout type of player can often find their way towards the top of OPS leaderboards. In most cases, this comes at a cost. The three-pronged player mentioned above has success despite their swing-and-miss tendencies. These types of hitters were often over-looked in previous generations due to this. If you are able to find cheaper ways to obtain the same OPS number, why would you not use that to your advantage when constructing a roster? Different types of players with different skill sets can garner a high OPS. Certain skills sets are more expensive or harder to find so the market forces teams to fork out substantial dollars. This is where small-market teams can get caught up in a proverbial wasteland while trying to compete with far more resourceful teams. Overspending in this manner is not ideal for success. Another example is wins above replacement or WAR. In fact, WAR = (Batting Runs + Base Running Runs +Fielding Runs + Positional Adjustment + League Adjustment +Replacement Runs) / (Runs Per Win)
This analytic shows how many wins a player truly contributes to his team over the course of a season. The number is telling but, how a player becomes strong in this category should be of equal or greater importance. In exploring this new idea, organizations will run into more so-called gems or diamonds in the rough in player development. This is a recipe filled with bargain opportunity.
Studying and scouting a player is more intricate than ever before. Sabermetrics and advanced analytics are being used heavily to ensure decision-makers are putting their team in favorable position to win night in and night out. There is no doubt the game is more data-driven than ever before. In order to win without being the Yankees, Red Sox or Dodgers you must use this data in creative, dynamic ways. As a baseball community, we have only scratched the surface. Player development staffs must dig deeper into what the data is showing. To put this into perspective, Marcus Semien and Trevor Story are vastly different in what they bring to the table yet have very similar WARs.
WAR = (Batting Runs + Base Running Runs +Fielding Runs + Positional Adjustment + League Adjustment +Replacement Runs) / (Runs Per Win)
An extreme power hitter who obtains a high WAR through his proficiency at the plate is different than a player like Marcus Semien. In the case of Semien, he is a low-cost yet dynamic ball player that impacts the game without the glitz or glamour. On the other hand, Trevor Story, is potentially a costly power bat who plays a smooth middle infield with a plus arm. Both are incredible to have on your team. One is less costly, and harder to find. At the end of the day, any advanced statistic should be studied further. Observers are well aware of all the information data can bring to light and there is always opportunity for more. It becomes not only about what the stat represents but also how a player is able to use his abilities to get there. Data represents conclusions. Because the data is accurate and stable it is not in our nature to inquire more about what is already known. There is more to be known in the game of sabermetrics and advanced analytics. The possibilities are endless.