Low Launch Angle, High Exit Velocity: A Sleeper MLB Hitter?
- Pittsburgh Pirates outfielder Oneil Cruz possesses a rare combination of power and speed, but his performance has been inconsistent.
- However, a recent analysis utilizing a Statcast-based player comparison tool suggests Cruz may be poised for a breakout season.
- The key to Cruz’s potential lies in his exceptional exit velocity.
Potential Breakout Player: Oneil Cruz’s Unique Statcast Profile
Pittsburgh Pirates outfielder Oneil Cruz possesses a rare combination of power and speed, but his performance has been inconsistent. Despite showcasing flashes of brilliance with 20 home runs and 38 stolen bases, Cruz struggled through a difficult season in 2025, hitting just .200 with a .326 on-base percentage and a wRC+ of 86 in 544 plate appearances. His second half was particularly challenging, as he batted only .177 with a wRC+ of 56.
However, a recent analysis utilizing a Statcast-based player comparison tool suggests Cruz may be poised for a breakout season. The tool, which focuses on batted ball distribution, barrel rate, strikeout and walk rates, identifies players with similar profiles, potentially uncovering overlooked talent. According to the analysis, Cruz’s underlying data remains highly promising, even if not fully reflected in his traditional statistics.
The key to Cruz’s potential lies in his exceptional exit velocity. While his overall numbers haven’t consistently matched his raw power, the Statcast data indicates a significant upside. The analysis highlights that despite his struggles, the algorithm continues to favor Cruz, even without directly weighting his impressive exit velocity.
A critical factor in unlocking Cruz’s potential may be improving his bat path. Sources indicate that a very low launch angle is a characteristic of his swing. If he can adjust his approach to optimize his launch angle, his already impressive exit velocity could become truly devastating.
The Statcast Similarity tool identifies players with comparable profiles to Cruz, including James Wood, Riley Greene, Nick Kurtz, and Bryan Reynolds. This comparative approach aims to identify players who might follow a similar trajectory to Cruz, offering insights into his potential development.
The importance of launch angle and exit velocity in evaluating hitters is increasingly recognized in modern baseball analysis. According to research, exit velocity tends to peak between -10 and 10 degrees of vertical launch angle for most hitters. Understanding these relationships is crucial for identifying players who can consistently generate impactful contact.
Beyond Cruz, the Statcast-based approach has previously identified other potential breakout players, including Tyler Soderstrom and Ben Rice. While not every prediction is accurate, the method has demonstrated a track record of uncovering hidden gems.
The analysis also emphasizes the importance of considering factors beyond the Statcast data, such as playing time, speed, injury risk, and platoon splits. These contextual elements are crucial for refining player evaluations and making informed predictions.
In the American League, other players are also demonstrating promising underlying data. Edgar Montero, a shortstop in the Athletics organization, has shown a strong combination of contact rates, chase rates, exit velocity, and launch angle. Montero, an 18-year-old Dominican native, slashed .313/.484/.580 with nine home runs in 55 games, boasting a 90th percentile exit velocity of 104.7 mph and a hard-hit launch angle of 17.5 degrees. Aron Estrada, a 20-year-old second baseman in the Orioles system, also impressed after reaching Double-A, hitting .300/.355/.500 with a 15.5% strikeout rate.
These players, along with Cruz, represent potential breakout candidates for , showcasing the value of analyzing underlying data to identify talent that may be overlooked by traditional scouting methods. The combination of exit velocity, launch angle, contact rates, and chase rates provides a valuable baseline for understanding a hitter’s strengths and weaknesses and predicting future performance.
