For Major League Baseball pitchers, high pitch velocity has become one of the most coveted skills. But a recent study co-authored by Brown researchers found that higher pitch speed on its own is not significantly associated with reducing the chance of a hit — challenging one of the sport’s most prominent paradigms.
Instead, the study determined pitching accuracy to be the most significant variable for pitcher success. Accurately thrown pitches are around three times more likely to result in a favorable pitching outcome, reducing hitters’ batting average and slugging percentage by 50%, according to Anthony Napoli, one of the lead authors of the study and professor of health services, policy and practice and emergency medicine.
The inspiration for the study came from Anthony Napoli’s son, Benjamin Napoli, a student at Villanova University and lead author of the study.
When Benjamin Napoli was a pitcher on his high school baseball team, he noticed that he often outperformed other pitchers who threw faster than him. But he found that pitching speed was viewed with more importance by his peers and coaches.
“I’ve heard from some of the people I played with and college coaches to (focus on) speed, because you can’t teach speed but you can teach accuracy,” he said. He believes that “it’s the other way around, where accuracy is more important than speed and you can gain speed.”
In the study, researchers analyzed 1,000 randomly selected at-bats over 17 games during the 2022 MLB season. The study tested pitching success against other variables including pitch type, location and speed. To determine whether a pitch was accurate, they manually examined whether the pitch was within six inches of where the catcher set their glove, Anthony Napoli said.
The study also found that higher velocity pitching was associated with lower pitch accuracy. The researchers said they hope their findings encourage pitchers, MLB organizations and youth pitching programs to prioritize accuracy over speed.
Over the past decade, data analytics have taken on a more prominent role in the recruiting philosophy of MLB teams. After Statcast, an automated analytical tool, debuted in the MLB in 2014, baseball became a more number-driven sport.
“It’s just a very analytical game in the day and age that we are now,” Benjamin Napoli said. He noted that even during games where managers make “human decisions,” these decisions are largely based on analytics.
Benjamin Napoli added that looking at additional variables like spin rate — how much the ball rotates once a pitch is thrown — could improve understanding of successful pitcher outcomes.
Looking forward, Anthony Napoli said machine learning algorithms could evaluate a larger sample size of at-bats, which would more strongly validate study results.
While the researchers did not examine the joint effect of the accuracy and speed of pitches, both Anthony and Benjamin Napoli believe accuracy coupled with high speeds could yield the most optimal pitch.
“There (are) so many different ways you can add on to the study to see specifically what makes the optimal pitcher,” he said.
Jonathan Kim is a senior staff writer covering Science and Research. He is a second-year student from Culver City, California planning to study Public Health or Health and Human Biology. In his free time, you can find him going for a run, working on the NYT crossword or following the Dodgers.
