Information-Coupling in Baseball Batters

Information-Coupling in Baseball Batters

Garrett Boyum

Missouri State University 

November 23, 2019

Abstract

Baseball batting is one of the most difficult skills to acquire in all of sports. Hitting a baseball under a dynamic and variable spatial time constraint poses a significant coordination challenge. As a result, the use of ball projection machines has become ubiquitous in training in many fastball interceptive sports including baseball batting.  Recent research in other sports has brought into question the efficacy of their use and no subsequent study has been conducted in baseball. The following is a research proposal for the examination of the use of ball projection machines effects on baseball batting with regards to facing a live pitcher.   

Introduction

The extreme temporal and spatial task constraints of dynamic interceptive actions present in baseball batting require an athlete to display extraordinary skill and dexterity. Batters strive to hit barrels a metric that was created in the Statcast Era to quantify ideal batted ball contact which is defined as a ball hit with a minimum of 98mph exit velocity with the probability to produce .500 batting average and 1.500 slugging percentage since the implementation of Statcast in MLB 2015  (Major League Baseball, 2019). Batters face pitches traveling up to 105mph, the fastest recorded in Major League Baseball, giving the hitter approximately 337 milliseconds to coordinate a barreled bat-ball contact (BaseballSavant.com, 2019). In addition to this the pitches batters face pitches that vary in speed, vertical, and horizontal movement measured in inches as it travels to and through the hitting zone. Not only that but they will be thrown by pitchers that have their own unique styles and accompanying arm slots and release points. This presents a tremendous challenge to the batter’s perceptual-motor systems leading Hall of Fame hitter Ted Williams to deem it “the single most difficult thing to do in sport” (Williams & Underwood, 1986, p.7).  As a result, baseball coaches have increasingly turned to the use of pitching machines to aid hitters in their preparation to face the modern pitcher who’s pitching velocities have risen over the past decade all the while commanding an arsenal of pitches with deceptive movement (Claire, 2018).

Advances in pitching machine and pitch tracking technology have made pitching machines an attractive tool for training baseball batters. Pitch tracking technology now allows coaches to not only know how fast a pitch is thrown but also its spin rate and spin axis which they can then use with newer pitching machines to replicate a pitches velocity and movement. These benefits along with others are all valid reasons for the use of pitching machines yet in reviewing the current literature there appears to be no research into pitching machines effect on a batter’s perception and subsequent mechanics in relation to facing a live pitcher. Pinder al et. in 2011 similarly noted that no studies had examined the visual gaze behaviors of batters facing ball projection machines compared to facing a live bowler in cricket (Pinder, Renshaw, Davids, & Kerherve, 2011). This exemplifies the importance of conducting a study which seeks to investigate how batting against pitching machines may affect baseball batters gaze and movement behavior when compared to a live pitcher. Studies like this can provided coaches with insights into how different batting practice conditions may affect a batter’s gaze and swing kinematics transferability to a competitive setting.  

How is it that elite hitters are able to barrel the balls at the professional level given the difficulty of the task? Ecological psychology and dynamic systems theory have been utilized in an attempt to describe the relationships that are involved in the control and regulation of movement to achieve specific task goals like interceptive actions (Pinder, Renshaw, & Davids, 2009). Ecological Dynamics seeks to take a systems approach to motor control that emphasis the reciprocal relationship between the performer and the environment culminating in the coupling of perception and action (Renshaw & Davids, 2014). This reciprocal perception-action  relationship is shaped and described by Newell’s 1986 Constraints model of motor control. Within Newell’s Constraints Model performers actions emerge out of culmination of constraints placed upon the human movement system (Newell, 1986). The constraints that shape an actor’s behaviors are broken down into three general categories: organismic (individual), environmental, and task constraints (Newell, 1986). The interaction of these constraints influence and shape the performer’s perceptions and actions of and within the environment (Newell, 1986). These constraints provide continuous information that is directly perceivable to be utilized by the performer to coordinate movement (Gibson, 1979). This information in the surrounding environment has been shown to be exploitable by performers to regulate the action of interceptive tasks like cricket (Pinder, Renshaw, & Davids, 2009; Regan, 1997; Williams, Davids, & Williams, 2000). A major source of information is provided by the task constraints which are defined by the factors that are related directly to the activity being performed (Renshaw & Davids, 2014).  Examples of task constraints would be considered: rules or instructions, equipment used, boundaries, field markers, other players, as well as other information sources that emerge from specific performance contexts  (Renshaw & Davids, 2014).  In the case of baseball task constraints would include things such as: bat type, baselines, field of play dimensions, pitching machines, pitcher type, distance of the mound or bases.

Given that task constraints are a key information source for the regulation of coordination and control of a performer’s actions, this necessitates becoming highly attuned, or highly sensitive to specifying information in the environment for action that are present across performance contexts (Pinder, Renshaw, & Davids, 2009).  Although athletes can become attuned to specifying information, they also can attune to non-specifying information that as the level of competition increase will impede their ability to compete with their peers that have learned to pick up the specifying information in the environment functional for guiding their actions (Pinder, Renshaw, & Davids, 2009). By attuning to specifying information relating to the task goal the performer may then be able to more quickly and accurately anticipate the future ball flight and location (Cassidy, 2000; Müller et al., 2006, 2017; Müller & Abernethy, 2012; Prigent et al., 2015). Cassidy, 2000 doctoral thesis found that batters were able to distinguish more quickly what pitch was thrown from a live arm than from a machine demonstrating that the specifying information present is different between the two conditions. Takeuchi & Inomata, 2009 also found that expert batters were more quickly able to distinguish pitches from novices when standing in against a live pitcher.

Gaze Behavior   

Given that the attunement to the specifying variables is integral to fastball interceptive sports like baseball batting the question becomes what specific information are batters attuning to? Several studies have sought to examine the gaze behavior of baseball batting. The earliest studies on gaze behavior focused largely on the batter’s ability to track the ball throughout its entire flight path which found that batter’s eyes were unable to track the ball all the way to contact (Bahill, 1984; Hubbard & Seng, 1954). This is thought to be due to the limitation for how fast the eyes can move in smooth pursuit of an object leading to the observation that elite batters use a combination of head and eye movement to track the ball as compared to novice batters that tended to move one or the other (Bahill & LaRitz, 1984; Gray, 2017). They also found that some batters would also employ a different eye movement strategy where they would follow the ball for approximately the first 25 feet before quickly jumping their eyes via a saccade to the spot they anticipated the ball to be to repick up the ball with smooth pursuit to contact (Bahill & LaRitz, 1984; Gray, 2017). This possibly provides the batter with more feedback on the accuracy of their judgement of the pitch trajectory (Gray, 2017). The draw back to using this strategy is that the pick-up information during the saccade is so minimal that we are almost blind in the process (Gray, 2017). The smooth eye movement strategy was dubbed by Bahill and LaRitz the optimal hitting strategy as it provides the batter with more continuous information upon which to base their movements while the saccade strategy was optimal learning strategy as it could be utilized to calibrate their perception and action (Gray, 2017).  

More recently studies have sought to examine what information are batters looking at during the pitching delivery (Kato & Fukuda, 2002; Takeuchi & Inomata, 2009). Two studies have compared the visual fixation points of varsity college batters to novice batters when viewing a pitching delivery. The pitching delivery was broken down into 4 phases; phase 1 was the start of the pitching motion to leg lift, phase 2 is the downward move out of leg lift by the lead leg, in phase 3 is arm movement thru front foot strike with the throwing arm is cocked back going into ball release , while phase 4 is the movement from max external rotation into ball release (Kato & Fukuda, 2002; Takeuchi & Inomata, 2009). Both studies found that expert batters used a visual pivot strategy to shift their gaze from the head and trunk region to the elbow and hand at ball release (Kato & Fukuda, 2002; Takeuchi & Inomata, 2009). A visual pivot is defined by a visual fixation where the attention of the individual is distributed to pick up specifying information in the periphery of the visual field (Vater, Williams, & Hossner, 2019).  Takeuchi & Inomata, 2009 found that some expert batters looked at release point which differed slightly from Kato & Fukuda, 2002 findings which suggested that experts used a visual pivot by looking at elbow and forearm. Which would seem to run somewhat contrary to the visual pivot strategy use of periphery vision to pick up ball release information. It was also found that expert batters tended to have longer fixations than novices which seems to align with some of Joan Vickers “Quiet Eye” research where experts athletes tend to hold their gaze longer on their fixation point before acting (Gray, 2017; Kato & Fukuda, 2002). It has also been found that expert baseball batters have more fixations during the pitching delivery than novices(Takeuchi & Inomata, 2009). On the other hand the visual gaze behavior of cricket batters facing ball projection machines tend to fix or “park” their gaze on where the ball comes out of the machine (Croft, Button, & Dicks, 2010). This would suggest that when batters hit off machines they use the visual gaze behavior is similar to that of a novice. Thus, it appears that batters visual gaze behavior differs between these two task conditions.   

Pitching Machines

As a result of altering task constraints such as the use of a pitching machine it appears that batters visual gaze behavior differs from facing live pitcher. Does this change in gaze behavior and specific perceptual information, or lack thereof, lead to a significant alteration in a batter’s kinematics and ability to detect relevant information to hit the ball when facing a pitcher? Pitching machines are considered to be useful training equipment to provide batters with consistent accurate pitches that can exhibit game like velocity and or movement (Pinder, Renshaw, & Davids, 2009). Additionally, pitching machines can alleviate the logistical and workload challenges with regards to having enough skilled batting practice pitchers to use while mitigating the corresponding risk of overuse throwing injuries in the course of providing batters with the necessary practice repetitions (Dennis, Finch, & Farhart, 2005; Pinder, Renshaw, & Davids, 2009; Pinder, Renshaw, Davids, & Kerherve, 2011). Studies on the effects of the use of ball projection machines for fast dynamic interception sports have predominately been done on cricket and tennis players (Carboch, Süss, & Kocib, 2014; Gibson & Adams, 1989; Krause, Farrow, Buszard, Pinder, & Reid, 2019; Pinder, Renshaw, & Davids, 2009; Renshaw, Oldham, Davids, & Golds, 2007). Such studies have consistently established that ball projection machines alter the kinematics and timing of performers movements as compared to when facing a real opponent (Carboch, et al., 2014; Gibson & Adams, 1989; Krause, et al., 2019; Pinder, et al., 2009; Renshaw, et al., 2007). This brings into question the efficacy of the use of pitching machines in other interceptive sports such as baseball where no similar comparative studies have been done.

The majority of baseball studies tend to focus on isolating specific aspects of baseball batting for analysis and in the process potentially altering how the batter naturally operates there by severing the performer-environment relationship and or decoupled the perception-action link from the actual action of swing a bat at a moving ball (Cassidy, 2000; Gray, 2002; McCue, 2019; Pinder, Renshaw, & Davids, 2009). Many baseball batting studies have examined batter’s decision-making choice to either swing, determine pitch type, location, and or ball or strike. The main limitation with these study designs is that batters may not be consciously aware of these things when they swing. Additionally, some batters will make batted ball contact with pitches outside the strike zone. Hitters have even reported not knowing what pitch they have hit. This questions the efficacy of this type of research.  Occlusion studies also have similar limitations even (Higuchi et al., 2016) study that kept the perception-action coupled, did so using a pitching machine which poses some ecological validity concerns mentioned previously. Another limitation with the current body of literature is common use of virtual reality (VR) in baseball research. Many VR studies may lack ecological validity due to disassociated tactile and visual feedback in addition to inadequately being able to optically recreate a 3-D space and movement that could possibly omit vital elements of specifying information that the performer would otherwise use for action (McCue, 2019).  Moreover, there have been no studies examining the visual strategies employed while batting against a ball projection machine compared to live – pitcher and its subsequent effects on the batter’s timing and movements (Pinder, Renshaw, Davids, & Kerherve, 2011). Therefore, the purpose of this study is to examine baseball batter’s gaze and movement behavior between batting off a machine compared to facing a live pitcher.

Hypothesis

We hypothesize that the gaze behavior and movement kinematics will vary based upon the practice condition. We predict that the gaze behavior for the machine batting condition will be “parked” on the ball outlet of the ball projection machine whereas in the live condition batters will employ a pivot gaze or saccade strategy. This is in line with previous research (Croft, Button, & Dicks, 2010; Gibson & Adams, 1989; Kato & Fukuda, 2002; Pinder, Renshaw, & Davids, 2009; Renshaw, Oldham, Davids, & Golds, 2007; Takeuchi & Inomata, 2009).

Methods

Participants were selected from the Missouri State University baseball team. Consent and medical clearance from the training staff was obtained for all participants. The age range for participants was 18-24-year-old. Ethical clearance was given through Missouri State University’s ethics committee.

Procedure

The study took place in the indoor practice facility in the Bill Rowe Training Center at Hammons Field. Each batter will complete a standardize full-body warm-up accompanied by a hitting warm-up. The full-body warm-up will consist of neck rotations, trunk twists, bent over trunk twists, arm swings across the chest, arm circles forwards and backwards, forward lunge with hip lift to thoracic rotation, single leg RDLs with quad stretch, and 3-way lateral lunge. The hitting warm-up will consist of dry swings, 8 swings off a tee, and 8 swings off of underhand front toss. This is done to minimize any confounding effects that hitting off a tee or underhand front toss may present. Batters will be allowed to take as many dry swings as they feel necessary as this would be permissible in a competition setting if they were on warming up on deck or before competition.

Hitters will bat against both the pitching machine and a live pitcher as the goal is to see what affects hitting off of a pitching machine will have on batting performance against a real pitcher. Batters will first hit off of a Rawlings Pro Line Three Wheel Pitching Machine before facing a live pitcher. Batters will take 3 rounds of 8 pitches off the pitching machine placed 55 feet away, a typical pitch release distance to simulate a practice condition. A Stalker Pro II radar gun that measures both pitch speed and spin rate was used to ensure pitch speeds of 88 mph +- 2mph with a spin rate of 2,264. Then after a 30-minute break and be allowed to reperform any element of the full body warm-up they feel necessary before they bat against the live pitcher. Batters will be allowed to observe a minimum of 5 and a maximum 8 warm-up throws by the pitcher to prepare themselves to bat. They are allowed to stand at typical distance and angel for a on deck batter’s circle away from the pitcher to observe. Each hitter will get 4 at bats against the live pitcher any walks will be disregarded, and the hitter will get a new at bat until 4 batted ball at bats have been recorded. The study was conducted this way to be a more accurate representation of the conditions a baseball batter will encounter.

Rapsodo Hitting unit will be utilized to measure the quality of batted-ball contact via the barrel metric in both batting conditions. The Blast Motion bat sensor and 2 GoPro video cameras recording at frame rate of 240Hz will measure the body and bat kinematics. One camera will be placed perpendicular to the batter and one above to examine torso rotation. Each batter will be equipped with a Blast Motion bat sensor as well as the Pupil Core eye tracking glasses by Pupil Labs. The Pupil Core glasses’ front facing camera filmed at 120Hz frame rate while the binocular eye cameras with a frame rate of 200Hz. Batters will also wear a modified batting helmet with the bill removed to allow proper lighting for the Pupil Core eye tracking glasses. Gaze behavior was assessed on location and duration starting 500 milliseconds before the pitchers first move to just after contact point.  

Data

Of the batted balls that were collected a kinematic analysis was conducted and the swing was broken down into 4 phases. The initial phase being the load which consists of the initial movement to start the coil of the swing, the landing phase being second which begins when the front heel is down, and the third being the swing phase which is the start of downswing of the bat, the fourth phase being impact. This is similar to how Katsumata, 2007 analyzed a baseball batter’s swing. A paired T-Test was used to assess the kinematic data.  The gaze behavior was broken down and analyzed based upon (Croft, Button, & Dicks, 2010; Kato & Fukuda, 2002; Takeuchi & Inomata, 2009) 4 phase of a pitchers motions using a two-way ANOVA.

Bibliography and References

Baseballsavant.com. (2019). Statcast Search. [online] Available at: https://baseballsavant.mlb.com/statcast_search?hfPT=SI%7C&hfAB=&hfBBT=&hfPR=&hfZ=&stadium=&hfBBL=&hfNewZones=&hfGT=R%7C&hfC=&hfSea=2019%7C2018%7C&hfSit=&player_type=pitcher&hfOuts=&opponent=&pitcher_throws=&batter_stands=&hfSA=&game_date_gt=&game_date_lt=&hfInfield=&team=&position=&hfOutfield=&hfRO=&home_road=&hfFlag=&hfPull=&pitchers_lookup%5B%5D=663855&metric_1=api_p_release_speed&metric_1_gt=104&metric_1_lt=106&hfInn=&min_pitches=0&min_results=0&group_by=name&sort_col=pitches&player_event_sort=h_launch_speed&sort_order=desc&min_pas=0#results [Accessed 19 Oct. 2019]. 

Button, C., & Croft, J. L. (2017). Sports science needs more interdisciplinary, constraints-led research programmes: The case of water safety in New Zealand. Human Movement Science, 56, 157–159.

Carboch, J., Süss, V., & Kocib, T. (2014). Ball machine usage in tennis: Movement in- itiation and swing timing while returning balls from a ball machine and from a real server. Journal of Sports Science and Medicine, 13(2), 304–308.

Cassidy, P. (2000). Detecting Anticipatory Information by Elite Collegiate Baseball Batters: An Ecological Analysis. University of Minnesota.

Croft, J. L., Button, C., & Dicks, M. (2010). Visual strategies of sub-elite cricket batsmen in response to different ball velocities. Human Movement Science, 29(5), 751–763. https://doi.org/10.1016/j.humov.2009.10.004

Clair, M. (2018, August 29). Are pitchers really throwing harder than ever. Retrieved October 16, 2019, from https://www.mlb.com/cut4/are-pitchers-really-throwing-harder-than-ever/c-292153594. 

Dennis, R. J., Finch, C. F., & Farhart, P. J. (2005). Is bowling workload a risk factor for injury to Australian junior cricket fast bowlers? British Journal of Sports Medicine, 39, 843–846.

Gibson, A. P., & Adams, R. D. (1989). Batting stroke timing with a bowler and a bowling machine: A case study. Australian Journal of Science and Medicine in Sport, 21(2), 3-6.

Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Boston: Houghton Mifflin.

Gray, R. (2002). Behavior of college baseball players in a virtual batting task. Journal of Experimental Psychology: Human Perception and Performance, 28(5), 1131–1148.

Gray, R. (2017, August 9). “Soft Focus” or Visual Pivot Point: Which Should Baseball Batters Use? Retrieved December 2, 2019, from The Perception & Action Podcast website: http://perceptionaction.com/softfocus/

Gray, R. (2017, August 16). Eye & Head Movements in Batting: Challenging the “Truths” [Blog]. Retrieved December 2, 2019, from The Perception & Action Podcast website: http://perceptionaction.com/visualtracking/

Kato, T., & Fukuda, T. (2002). Visual Search Strategies of Baseball Batters: Eye Movements during the Preparatory Phase of Batting. 7.

Katsumata, H. (2007). A functional modulation for timing a movement: A coordinative structure in baseball hitting. Human Movement Science, 26(1), 27–47.

Krause, L., Farrow, D., Buszard, T., Pinder, R., & Reid, M. (2019). Application of representative learning design for assessment of common practice tasks in tennis. Psychology of Sport and Exercise, 41, 36–45.

Major League Baseball. (2019). What is a Barrel? | Glossary. [online] Available at: http://m.mlb.com/glossary/statcast/barrel [Accessed 19 Oct. 2019].

McCue, M. (2019). Exploring the Acute Affect of De-Coupled Batting Drills on the Gaze Behaviour and Decision-Making of Elite Baseball Players. University of Ontario Institute of Technology.

Miller, S. (2019, March 22). Will pitchers bring the most heat ever in 2019? Not so fast. Retrieved October 16, 2019, from https://www.espn.com/mlb/story/_/id/26321255/will-pitchers-bring-most-heat-ever-2019-not-fast. 

Müller, S., Abernethy, B., & Farrow, D. (2006). How do world-class cricket batsmen anticipate a bowler’s intention? The Quarterly Journal of Experimental Psychology, 59(12), 2162–2186.

Müller, S., Fadde, P. J., & Harbaugh, A. G. (2017). Adaptability of expert visual anticipation in baseball batting. Journal of Sports Sciences, 35(17), 1682–1690.

Newell, K. M. (1986). Constraints on the Development of Coordination. In M. G. Wade & H. T. A. Whiting (Eds.), Motor Development in Children: Aspects of Coordination and Control (pp. 341-360). Dordrecht, Netherlands: Martinus Nijhoff.

Pinder, R. A., Renshaw, I., & Davids, K. (2009). Information–movement coupling in developing cricketers under changing ecological practice constraints. Human Movement Science, 28(4), 468–479.

Pinder, R. A., Renshaw, I., Davids, K., & Kerherve, H. (2011). Principles for the Use of Ball Projection Machines in Elite and Developmental Sport Programmes. Sports Medicine, 41(10), 793–800.

Prigent, E., Hansen, C., Baurès, R., Darracq, C., & Amorim, M.-A. (2015). Predicting where a ball will land: From thrower’s body language to ball’s motion. Experimental Brain Research, 233(2), 567–576.

Regan, D. (1997). Visual factors in hitting and catching. Journal of Sports Sciences, 15, 533–558.

Renshaw, I., & Davids, K. (2014). Task Constraints. Eklund, Robert & Tenenbaum, Gershom (Eds.) Encyclopedia of Sport and Exercise Psychology, 10.

Renshaw, I., Oldham, A. R. H., Davids, K., & Golds, T. (2007). Changing ecological constraints of practice alters coordination of dynamic interceptive actions. European Journal of Sport Science, 7(3), 157–167. https://doi.org/10.1080/17461390701643026

Takeuchi, T., & Inomata, K. (2009). Visual Search Strategies and Decision Making in Baseball Batting. Perceptual and Motor Skills, 108(3), 971-980.

Vater, C., Williams, A. M., & Hossner, E.-J. (2019). What do we see out of the corner of our eye? The role of visual pivots and gaze anchors in sport. International Review of Sport and Exercise Psychology, 1–23. https://doi.org/10.1080/1750984X.2019.1582082

Williams, A. M., Davids, K., & Williams, J. G. P. (2000). Visual perception and action in sport (Repr). London: E & FN Spon.

Williams, T. and Underwood, J. (1986). The Science of Hitting. New York: Simon & Schuster.