Once majorly governed and influenced by traditional scouting and player management, the sport of baseball has undergone an analytical revolution. By overcoming intuition and letting data drive decision-making, baseball has seen analytics reshape its team strategies, tactical execution and the ability to adjust to various challenges. Over the years, the data and analytics revolution has completely transformed one of America’s favourite sports.
What was once an American pastime, baseball truly entered its highly professional and advanced analytics era from the 1970s and 1980s, when pioneers such as Bill James developed sabermetrics that could objectively measure in-game activity. Historically, batting average and RBIs were prioritised in baseball’s analysis and selection strategies. But the introduction of advanced data and technology helped teams dig deeper into a player’s statistics and assess their future capabilities.
Key Analytical Tools
While sabermetrics helped make the empirical analysis of baseball through statistics, the Moneyball era that followed saw Billy Beane’s Oakland Athletics deploy advanced analytics to try and bridge the gap with stronger and higher-budget teams and compete on a more even footing.
As of today, every side in Major League Baseball has a designated data analyst, who brings machine learning and predictive analytics to the fore and aids clearer decision-making and greater performance. Tools such as WAR (wins above replacement), wOBA (weighted on-base average) and FIP (fielding independent pitching) are the byproducts of the advanced analytics and are commonly used by teams to decide their strategy.
Advanced data helps teams map out where exactly a hitter is most likely to place the ball, allowing teams to pre-determine infield and outfield alignments that then raise their defensive efficiency. Predictive analytics boosts a team’s pitch sequencing and execution of different pitches at the right time based on the information provided by the data. Statistics also aid teams’ choice for a particular batting order against a specific opposition. It challenges the traditional norms where teams often preferred having the fastest player bat leadoff. The pitch counts, match-ups and rest days may also be assessed by optimising the data resources.
OPS
The term ‘OPS’ is short for ‘On-Base Percentage and Slugging’. It is one of the advanced analytics tools that are integral to baseball today. The OPS concerns the baseball hitter and determines his on-base percentage and slugging percentage together. The number which we have at the end of the OPS assessment gives an idea of how often a player reaches the base while also quantifying the quality of the hits he produces. The OPS significantly overcomes the limited influence and analysis possible with the traditional batting average.
Depending on the per plate appearance, the on-base percentage measures how often a hitter reaches base. This percentage is inclusive of a hitter’s hits, hit-by-pitches and walks but excludes reaching base on an error, dropped third strike or fielder’s choice. For example, for a baseball hitter that reaches base either by hit, walk or hit-by-pitch 34 times in his 100 appearances, his on-base percentage will be .340. To get the ultimate OPS rating, we just have to add the slugging percentage to the on-base percentage.
Slugging percentage assesses a hitter’s power and the quality of the hits he produces. Unlike the on-base percentage determined by walks and hit-by-pitch, the slugging rate accounts for only the hits. While calculating this critical percentage, singles count as one, doubles are multiplied by two, triples are multiplied by three, and home runs are multiplied by four. The result value is then added together and divided by the number of at-bats.
Spin Rate
Spin rate concerns the pitcher, quantifying how fast a baseball rotates as it travels toward the plate. The value is counted in revolutions per minute. The higher the value, the greater the spin imparted on the ball. The increased spin majorly impacts the success of the pitch against a baseball hitter. The aerodynamics play a major part in ultimately dictating the spin or the movement of the ball in potentially deceiving the hitter. There are effectively two types of variations that can cause such deception: the fastballs and curveballs.
The fastballs are pitches with effective backspin that stay on the higher plane and avoid the drop to continue sliding quicker towards the hitter. The aim is to rob the hitter time to properly place the hit in the intended direction. The curveballs are also pitched with the intention to disrupt a hitter but in a slower and more deceptive way. Curvalls delivered with the efficient topspin would invariably drop on the hitter, causing an optical illusion where the hitter is more often than not too early into his swing and end up missing or miscueing the pitch. The curveballs rely quite a lot on the orientation of the ball and also the seam, which determines the air flow and release.