Abstract
Purpose of Review
A critical component of any rehabilitation program following injury is a graduated exposure of pathologic or vulnerable tissue to sport-specific stressors. A foundational aspect in the return to sport process following an injury in baseball athletes is the development of an interval throwing program. A shift has occurred in recent years from generic programs to individualized progressions. The current review explores the evolution of interval throwing program construction and discusses the possibilities of the future with advancements in technology and understanding.
Recent Findings
Early interval throwing programs relied primarily on pre-determined throwing distance and volume to estimate total training load while following a fixed throwing schedule. Currently, clinicians have begun to utilize available technology in attempts to determine training prescription and obtain more accurate estimates of stresses placed upon the body. Thus, interval throwing programs have become more individualized and flexible to account for each athlete’s individual differences and biological response to training. Future development may be able to predict specific internal response to stressors and proactively adjust training load to maximize positive adaptations while minimizing any maladaptive events.
Summary
As with all concepts and principles within the realm of athlete rehabilitation, clinicians must continue to adapt how they conceptualize and develop individualized interval throwing programs for the overhead throwing athlete. We will continue to see a shift away from a responsive approach to a proactive one, where clinicians can utilize modern technologies to precisely prescribe a throwing dosage based upon expected tissue response within the athlete.
Keywords: Interval throwing programs, Overhead athlete, Baseball injuries, Throwing workload
Introduction
The baseball throwing motion has been described as one of the most violent and stressful motions in all sport [1•]. The arm has been reported to experience velocities greater than 9000 deg/s and distraction forces upwards of 1070 N at ball release [2]. Due to the violent and repetitive nature of throwing, arm injuries are common and continue to increase among youth, collegiate, and professional athletes [3, 4].
A critical component of any rehabilitation program following injury is a graduated exposure of pathologic or vulnerable tissue to sport-specific stressors. A foundational aspect in the return to sport (RTS) process following an injury in baseball athletes is the development of an interval throwing program (ITP). However, it should be noted that interval throwing programs are also completed in the absence of injury as part of healthy preparation for competition. While many of the concepts and principles discussed will also apply to healthy athletes, this review will primarily evaluate interval throwing programs in the context of the rehabilitation process.
A shift has occurred in recent years in the development of interval throwing programs from generic programs to individualized progressions. As with all concepts and principles within the realm of athlete rehabilitation, clinicians must continue to adapt how they conceptualize and develop individualized interval throwing programs. We will continue to see a shift away from a responsive approach to a proactive one, where clinicians can utilize modern technologies to precisely prescribe a throwing dosage based on an expected tissue response within the athlete.
Thus, a common conceptual framework of training load and how this relates to throwing is needed to optimize performance during the rehabilitation process [5••]. A common verbiage as outlined by Jeffries at al. that will be utilized within this review includes the differentiation between training prescription, training load, external training load, internal training load, and training response (Table 1). Since interval throwing programs are ubiquitous and critical to the RTS process in baseball athletes, it is worth considerable time and effort to optimize them. The current review explores the evolution of interval throwing program construction from the past to the present, while also discussing the possibilities of the future with advancements in technology and understanding.
Table 1.
Training prescription | Operational Definition: Short to long written plan detailing the goals and structure of a single training session or the training cycle, with the intention to improve sports performance. The training prescription would take into consideration contextual and individual factors and the athlete’s response to training (training effect). |
Practical Baseball View: A detailed written interval throwing program with consideration of volume and intensity, in addition to programmed activities such as rehabilitative exercises, resistance training, energy systems development, and recovery interventions. A Key component of future interval throwing programs should lie in developing training prescription based on internal load and training responses. Example: Force plate data, RPE, Acute and Short Recovery and Stress Scales, HRV data and osmolarity testing can be utilized to determine an athletes subsequent throwing parameters. | |
Training load | Operational Definition: The amount of training that is verifiably completed and experienced by the athlete, which can differ from what was planned (i.e., training prescription). Training load is the theoretical measure encompassing both external and internal load. |
Practical Baseball View: Objective and subjective measures that a clinician or coach would be able to document to monitor the work done and resulting stress in a session. A multidisciplinary team can develop monitoring systems (short and long term) that analyze an athlete’s psychological and physiological responses, and utilize these monitoring systems to guide the decision-making process while the athlete is going through an interval throwing program. | |
External training load | Operational Definition: Work performed by the athlete during training. This work does not specifically define physical quantities, rather it can encompass mechanical, psychological, physiological stress placed upon or experienced by the athlete. |
Practical Baseball View: External load can be measured by utilizing IMUs (intensity), Radar Guns, Distance, Number of Throws (volume), etc. when it comes to throwing. Clinicians can leverage current and future advances in technology to monitor and manipulate external load parameters during the RTS process. Example: Clinicians may decide to utilize microsensors (IMU) to determine an athlete’s elbow torque (intensity) as well as to count the number of throws (volume) performed during a session. Furthermore, Radar guns can be utilized to determine or guide intensity during ITPs, rather than relying on arbitrary percentages of intensity. | |
Internal training load | Operational Definition: Internal stress and strain experienced during exercise and training. The stresses on specific tissues by an applied force can also be considered an internal load. |
Practical Baseball View: Internal load can be measured through heart rate, EMG, Oxygen Saturation, Creatine Kinase, RPE, or measures that can be utilized to monitor the body’s response during an activity. Structural tissue issue adaptation during throwing. As a multidisciplinary team, stakeholders involved in the athlete’s care can utilize available tech to determine mechanical and psycho-physiological loading. For example: Trained health professionals can perform ultrasonography to determine tissues’ response to throwing and establish acute and chronic effects to throwing. This information can then be utilized to drive external load parameters (i.e., distance and number of throws), while considering individual and contextual factors related to the athlete. | |
Training effect | Operational Definition: The body’s response to a single training session or series of training sessions. This response can be acute, occurring after a single or a few training sessions, or the response can be chronic, resulting in cumulative effects over a longer period. These effects can be positive which improve sport performance, or negative which hinders sport performance. |
Practical Baseball View: From a musculoskeletal point of view, an acute training effect following a high intensity throwing session would encompass a decrease in glenohumeral ROM and strength. A chronic effect or adaptation to prolonged high-intensity throwing would be a glenohumeral torsion or an increase in ligament stiffness post throwing. Furthermore, the multidisciplinary team can leverage their expertise to determine an athlete’s response to throwing in a holistic manner. Example: Reduction in average HRV (Heart rate variability) with an increase in HR at rest can potentially indicate fatigue or maladaptation to training. Thus, modifications can be made to external load parameters for a period of time so that risk for injury or re-injury can potentially be mitigated. | |
Table Adapted from Jefferies et al. 2021 [5••] |
Past
Early interval throwing programs primarily focused on externally guided training prescription and post hoc training modifications while lacking attentiveness to differences between athletes. To initiate the return to throwing process following injury, two primary criteria were required: perceived biological healing and physician clearance [6, 7]. At that time, the athlete would begin an interval throwing program with progressive overload in volume and intensity to gradually expose the pathological tissue to mechanical stress, resulting in tissue adaptation and readiness for game-specific demands [6].
These training prescriptions were previously developed by progressively increasing the athlete’s external training load. The two categories of parameters that were most manipulated were 1) the number of throws or volume and 2) throwing distance and effort level as surrogate markers of intensity. These variables of volume and intensity were progressed in a similar manner from program to program with minimal customization [6]. In this past framework, throwing prescription was reactionary and static as opposed to anticipatory and individually prescriptive.
Typically, athletes were allowed to throw daily barring new or persistent adverse exacerbations which required 1 day of complete rest, followed by repeating the previous phase of throwing [6]. In this way, clinicians acknowledged potential adverse effects of progressive tissue exposure, such as pain, discomfort, mechanical damage or swelling. While this way of post hoc monitoring has been successful at returning many overhead athletes to sport, it may have neglected the complexity of physical training and performance enhancement in the return to sport process.
A primary disadvantage of this approach was that it ignored individual characteristics such as throwing kinetics/kinematics, training history, training response, and contextual factors. Athletes followed a semi-rigid throwing schedule, though the pace of the progression may not have aligned with their specific needs. Recent literature has analyzed the differences in arm kinematics and kinetics during long toss and mound pitching in baseball players at different competitive levels (high school, college, professional) [8, 9••, 10]. Aguinaldo et al. reported that high school baseball players experience similar elbow torques at lower throwing velocities when compared to professional baseball players [11•], thus illustrating the importance of individualization in training prescription and modification strategies with consideration of training age and experience [12].
In retrospect, early interval throwing programs excelled in recognizing the importance of biological tissue healing and adapting to the adverse effects if throwing was progressed too rapidly within the rehabilitation process. Despite early successes, interval throwing programs relied on semi-arbitrary throwing prescriptions based on estimated external load metrics, post hoc training modifications based on adverse effects, and lacked individualization.
Present
While early interval throwing program guidelines relied primarily on biological healing as a time-based approach for determining readiness to throw after injury, recently, there has been an emphasis on utilizing a criteria-based approach: evaluating biological and performance measures to determine overall athlete readiness [12]. These functional benchmarks may include restoration of adequate range of motion and strength measurements, non-compensatory motor patterns, and completion of an appropriate upper extremity plyometric program [13]. Previous studies suggest that lower extremity and core testing should be performed, and movement patterns normalized prior to throwing due to the importance of the kinetic chain in throwing efficiency [13].
As discussed, previous interval throwing programs utilized volume and intensity as the fundamental components for training prescription. Program modifications in this context were contingent upon adverse events from throwing, which would then trigger adjustments. Current practice has shifted to the use of available monitoring strategies of training response to guide prescriptions and modifications in attempts to mitigate potential risks for rehabilitation setbacks or re-injury [14]. Common monitoring strategies include subjective reporting, changes in physiological adaptations, and evaluating performance measures such as joint kinematics, kinetics, biomechanics, and throwing velocity [14, 15].
Subjective Athlete Self-reported Measures
Subjective athlete self-reported measures (ASRM) have been utilized to encompass various physical, psychological, and overall well-being domains of the athlete [16]. Administration can be completed at regular intervals throughout the rehabilitation process or may be used daily depending on the measure of choice. Custom ASRM that have not been validated but are specific to a rehabilitation or training facility may be more practical in the applied setting due to ease of application. However, empirical ASRM (Table 2) with established psychometric properties have demonstrated the ability to consistently provide a dose-response relationship between stress and training load, with an inverse relationship between recovery and training load [17]. Though the efficacy of subjective measures has been well established, optimal implementation has yet to be determined [17]. In the applied setting, utilization may differ between users, but a common application is the use of ASRM to promote dialogue with athletes regarding the relationship between training stress and recovery.
Table 2.
Characteristics | Practical view | |
---|---|---|
Profile of mood states (POMS) | Primary Dimensions explored: Mood | Can be challenging to complete on a regular basis. May be difficult to have athletes complete a 65-question form on a weekly basis. |
Performed Weekly | May be an option for athletes in later stages of an ITP, where they may only require a weekly check-up at an outpatient rehabilitation facility. | |
Has been consistently shown to respond well to dose-response and training load, in addition to identifying overtrained athletes. | ||
Shorter derivatives of the POMS have been utilized to monitor athletes. | ||
65 items allow for a deeper understanding of athlete’s current state. | ||
Recovery-Stress Questionnaire for Athletes (RESTQ-Sports) | Primary Dimensions explored: Stress, Recovery | May be an option for clinicians in the outpatient setting if seeing patient 2-3 times a week. |
A dose response relationship between stress and training load, and an inverse relationship between recovery and training load has been observed in athletes. | ||
75/52/36 item questionnaires available for clinician use. | ||
Performed every 3 days/nights | ||
Acute Recovery and Stress Scale (ARSS) | Primary Dimensions: Stress, Recovery | May be an option for professional teams attempting to gather information about an athlete’s daily response to throwing. |
32 item questionnaires | ||
Helps Identify current fatigue state of the athlete. | ||
Short Recovery and Stress Scale (SRSS) | Primary Dimensions: Stress, Recovery | May be an option for professional teams attempting to gather information about an athlete’s daily response to throwing. |
8 Item questionnaire | ||
Helps identify the current fatigue state of the athlete. | ||
Table Adapted from Saw et al. [16] |
Physiological Adaptations
Physiological adaptations in overhead athletes are well documented and are most often associated with the musculoskeletal system’s response to repetitive throwing [18, 19, 20, 21••, 22]. These adaptations commonly include structural, mobility, strength, and kinematic changes at the glenohumeral joint [23•, 24, 25]. These changes can be either acute or chronic in nature. Acute effects may be caused by one or more throwing sessions and require a relatively brief time to return to homeostasis [5••, 26••]. These effects are seen as alterations in range of motion, strength, and muscle architectural changes at the glenohumeral joint that typically resolve within 72 h (about 3 days) of high-effort throwing [13, 21••, 23•, 27, 28, 29•]. However, chronic effects, such as structural changes to the throwing shoulder and elbow, accumulate over months or years of throwing and require longer periods to return to baseline once training has stopped or decreased [5••, 22]. Understanding acute versus chronic adaptive effects allows clinicians to differentiate between normal alterations and adverse responses. Knowledge of the effects of throwing is valuable in the decision-making process surrounding the advancement or regression within the interval throwing program. For example: a clinician should expect a higher-level baseball pitcher to demonstrate increased glenohumeral external rotation and decreased internal rotation in their dominant arm at baseline and should not be alarmed if the amount of internal rotation were to decrease shortly after a bout of throwing. Familiarization with a particular athlete’s range of motion will allow the clinician to accurately flag an abnormal response and make the correct training modifications necessary to allow for restoration of baseline function before proceeding with ITP advancement.
In addition to acute and chronic physiological changes within the athlete, another area of recent focus has been the relationship between acute and chronic workload. One training prescription method that has received mixed reviews in the literature is the use of the acute: chronic workload ratio (ACWR) [30]. This ratio is calculated by dividing the acute load (previous week’s training load) by the chronic training load (average workload of the previous four weeks). This ratio is meant to quantify the relative rate of workload increase over a given period [30]. While some have suggested it is a useful tool for optimizing performance while mitigating injury risk potential [30, 31], others have raised concerns for the conceptual basis of ACWR’s along with collection and statistical faults in the calculations [32, 33]. In the applied setting, absolute measures of training load and sound progressive principles without a specific target ratio have been suggested to be more informative and provide guidance to overall training prescription [34]. When progressing an ITP, it is important for prescribers to acknowledge all components of an athletes training regimen (i.e., lifting, conditioning, skill work, and rehabilitative exercises) and account for those stressors. Failure to do so may result in a sharp increase in overall workload, hindering an athlete’s ability to recover and adapt, and may even result in eventual adverse event.
Performance Measures
Performance measures are typically the ultimate driver of training progression and indicator of athlete readiness. Kinematics and kinetics of the pitching cycle have been shown to have a profound impact on upper extremity stress and performance. Technological advancement has allowed for improved analysis of throwing performance and precision of training prescription (Table 3) [48]. Two current technologies that are being used to analyze biomechanics and monitor mechanical stress upon the upper extremity are motion capture systems and inertial sensor monitoring units (IMUs). Motion capture systems typically consist of a series of cameras surrounding an athlete which track the motion of strategically placed reflective markers on the athlete’s body. More advanced systems may not require markers, instead tracking specified joints or anatomical structures. These systems are utilized to assess throwing kinematics, grade biomechanical efficiency, and estimate relative stress upon the body. This information is then utilized to guide throwing prescription when developing ITPs. For instance, an athlete with an inefficient throwing pattern may require a more gradual progression than an athlete who throws with high efficiency, as those two athletes will not experience the tissue stress at the same throwing distance and intensity [11•]. Motion capture systems are highly accurate and offer valuable insight, but they tend to be expensive and require specialized knowledge and training to operate.
Table 3.
Pros | Cons | Feasibility | |
---|---|---|---|
Inertial Sensor Measuring Units | Easily available, small portable equipment | Low inter-thrower reliability. | Can easily be implemented in the clinical setting. |
Can be utilized while throwing in game/practice | Microsensors are often housed in arm sleeves made of nylon fabric, which can potentially stretch and drift during the throwing motion, thus potentially being a source of error in data. | ||
Affordable and easy to use/implement | |||
May be more accurate at capturing body segment motion during pitching since it does not rely on visual artifact and lighting. | |||
Camera-Based Monitoring Systems (Motion Analysis) | High precision; most accurate | Costly; Not easily accessible. | Motion capture systems are highly accurate and offer valuable insight, but they tend to be expensive and require specialized knowledge and training to operate. However, currently, companies are attempting to bring marker less biomechanical data to smart phone devices via apps (I.e., Pro Play AI) |
Marker-less video-based systems can be utilized in-game to gather real-time performance data during games. | Space required to set up camera system | ||
Marker-based systems require upwards of 40 reflective markers that attach to key anatomical areas, generate silhouette of the body, and gather kinematic data of the throwing motion. Furthermore, a marker can be tracked only if it is captured by two or more cameras. Thus, camera set-up is vital for accurate data. | |||
Data quality can be affected by visual artifacts or changes in background lighting. | |||
Radar Gun | Easily available, Small; easily portable equipment. | Output measures do not tell you how the athlete is achieving velocity number; does not consider throwing efficiency. | Can easily be implemented in the clinical setting. |
Can be utilized while throwing in game/practice to determine a player’s output velocity. | Players may manipulate effort levels to hit a specific number. | Presently, there are small and easily portable radar guns on the market that can be utilized in most if not all clinical and field settings. (I.e., pocket radar) | |
Can be used to guide intensity of a session. | |||
Vellios et al. 2020 [35•] |
In comparison to large-scale motion capture systems, IMUs are small, wearable devices that are suggested to provide objective data regarding joint and limb angles, velocities, and overall mechanical stress [35•, 36•, 37]. They can also serve to count the number of throws an athlete performs over a specific timeframe, providing a more precise quantification of throwing volume. Previous studies tracking the number of throws on game day in high school and collegiate athletes have identified that most throws performed during game day are often unaccounted for [38, 39, 40•]. Wearable micro-sensors (IMUs) allow clinicians to develop ITPs that theoretically account for all external training measures and ensure athletes are not accumulating too much workload during the return to sport process. Additionally, IMUs can give clinicians in-game/practice measures of relative stress on the upper extremity. Previous studies have reported that throwing to 120 feet over flat ground induces similar elbow stress to pitching from a mound at the standard 60.5 feet, suggesting that an athlete who can throw to 120 feet with minimal ball arc may be ready to handle the stress from throwing down the mound [1, 8]. Presently, private baseball and performance facilities across the nation utilize wearable and motion capture systems as part of their development programs. Therefore, the opportunity of developing individualized programs currently exists and clinicians should leverage such services to bridge the gap between rehabilitation and performance in the development of ITPs.
Another device that has had practical importance regarding throwing intensity, or effort, is the radar gun. Ball velocity has been demonstrated to have a stronger correlation to stress exerted on the shoulder and elbow than perceived effort of throwing [41••]. Slenker et al. found that an athlete throwing at a self-reported 60% of their maximal perceived effort produces 84% of their maximum ball velocity [42], illustrating the discrepancy between athlete perception and true throwing intensity. Considering this relationship, the utilization of radar guns during a throwing session have shown to be beneficial to monitor ball velocity and relative throwing intensity in real-time. Utilizing a radar while simultaneously collecting subjective reports from the athlete regarding perceived effort may offer valuable, albeit indirect, insight into relative arm stress.
Future
It is the authors’ hopes of a threefold future for interval throwing programs: 1) conceptualizing measures of internal load as primary drivers of training prescription, 2) understanding the complexities of the rehabilitation and performance process, 3) establishing an individualized, athlete-centered integrated support team. A principal component of the future should lie in developing training systems that actualize internal load metrics to drive throwing prescriptions. Kalkhoven et al. defined mechanical load-response as forces experienced by specific biological tissue that can be either externally or internally sourced [43•]. Chalmers et al. examined the ulnar collateral ligament’s response to stress in 185 professional baseball pitchers and observed over the course of a baseball season, baseline UCL thickness and valgus laxity (30°) increased while ligament stiffness decreased, followed by a subsequent decrease in thickness and valgus laxity (30°), and an increase in ligament stiffness during the off-season [44••], thus, highlighting the importance of determining specific tissue adaptations in response to mechanical load in overhead athletes. In future programs, special attention should be placed on loading responses of biological tissues and how these equate to external parameters, thus allowing for better individualization based on the athlete’s tissue response.
In many cases, an athlete’s response to throwing can be affected by individual or contextual factors exclusive to the athlete. Individual factors that influence sports performance are those that are unique to the individual (i.e., genetics, current psychological state, training age/history), while contextual factors are not typically considered as a part of training (i.e., environmental considerations, social or cultural background) [40•], but can still have an impact on the athlete’s performance capabilities in each session [43•].
In addition to conceptualizing internal training load, future challenges in developing interval throwing programs will lie in the dichotomy between rehabilitation and performance [45]. Currently, in traditional rehabilitation approaches, the concept of tissue health is often separate from that of sport performance [46]. In the future, interval throwing programs should be viewed through a dual rehabilitation and performance lens, establishing new throwing parameters, recovery strategies, and adjunct training with the aim of optimizing health and performance. While general time and criteria-based approaches will continue to be emphasized, conceptualizing the complexity of the return to sport process should be a key component of individualization [47]. In the applied setting, clinicians should attempt to address individual and contextual factors in the RTS process by collaborating and integrating other disciplines into a shared decision-making process [12].
An integrated support team may include sports medicine physicians, physical therapists, athletic trainers, sports scientists, sports psychologists, nutritionists, skill staff, and performance coaches with their own distinct skillsets to create a team environment where the whole is truly greater than the sum of its parts [48]. This is especially true within the return to sport process during an interval throwing program [12, 49]. Rehabilitation and performance are both dynamic processes changing daily with fluctuations in training load, recovery, and overall athlete well-being [48]. Having a unified purpose to drive each athlete to their highest level of performance is a starting point for this level of true integration.
Conclusion
Previously, interval throwing programs following injury in the overhead throwing athlete were reactionary and static as opposed to anticipatory and individually prescriptive. Volume and intensity were progressed in the same manner from program to program with minimal customization. Presently, there has been a shift to a criterion-based approach to initiation and progression of interval throwing programs, evaluating biological and performance measures to determine overall athlete readiness. Modern technologies such as motion capture, IMUs, and others are being used to track physiological adaptations and evaluate athlete performance, while validated subjective reporting strategies have allowed athletes to express their perception of the rehabilitative process. The evolving knowledge of how an individual athlete typically responds to throwing is critical in the decision-making process surrounding the advancement or regression of an interval throwing program.
While criterion-based approaches based on biological factors will continue to be an emphasis in interval throwing programs, conceptualizing the complexity of the return to sport process should be a key component of the individualization process [50]. Individual and contextual factors surrounding the RTS process must be considered in the collaboration and integration among multiple disciplines, including clinicians, coaches, skill development staff, and more. Future interval throwing programs should emphasize establishing holistic criteria for successful return to performance and utilize real-time internal load measures to drive external load throwing prescription. It is the authors’ hopes that future interval throwing programs will attempt to conceptualize measures of internal load and accurately predict the athlete’s response to the act of throwing to further optimize prescription and modification.
Declarations
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
Conflict of Interest
Christian Hintz DPT, Dennis Colón DPT, Danielle Honnette DPT, Nathan Denning DPT, Edwin Porras DPT, Justin Willard MBA, and Adam Diamond DPT, AT declare they have no conflict of interest.
Footnotes
This article is part of the Topical Collection on Injuries in Overhead Athletes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
- 1.Dowling B, McElheny KD, Camp CL, Ling DI, Dines JS. Effects of mound versus flat-ground pitching and distance on arm mechanics and elbow torque in high school pitchers. Orthop J Sports Med. 2020;8(12):2325967120969245. doi: 10.1177/2325967120969245. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Fleisig GS, Andrews JR, Dillman CJ, Escamilla RF. Kinetics of baseball pitching with implications about injury mechanisms. Am J Sports Med. 1995;23(2):233–239. doi: 10.1177/036354659502300218. [DOI] [PubMed] [Google Scholar]
- 3.Conte S, Camp CL, Dines JS. Injury trends in major league baseball over 18 seasons: 1998-2015. Am J Orthop (Belle Mead NJ). 2016;45(3):116–123. [PubMed] [Google Scholar]
- 4.Olsen SJ, Fleisig GS, Dun S, Loftice J, Andrews JR. Risk factors for shoulder and elbow injuries in adolescent baseball pitchers. Am J Sports Med. 2006;34(6):905–912. doi: 10.1177/0363546505284188. [DOI] [PubMed] [Google Scholar]
- 5.Jeffries AC, Marcora SM, Coutts AJ, Wallace L, McCall A, Impellizzeri FM. Development of a revised conceptual framework of physical training for use in research and practice. Sports Med. 2021;52(4):709–724. doi: 10.1007/s40279-021-01551-5. [DOI] [PubMed] [Google Scholar]
- 6.Axe MJ, Snyder-Mackler L, Konin JG, Strube MJ. Development of a distance-based interval throwing program for Little League-aged athletes. Am J Sports Med. 1996;24(5):594–602. doi: 10.1177/036354659602400506. [DOI] [PubMed] [Google Scholar]
- 7.Axe M, Hurd W, Snyder-Mackler L. Data-based interval throwing programs for baseball players. Sports Health. 2009;1(2):145–153. doi: 10.1177/1941738108331198. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Leafblad ND, Larson DR, Fleisig GS, Conte S, Fealy SA, Dines JS, D’Angelo J, Camp CL. Variability in baseball throwing metrics during a structured long-toss program: does one size fit all or should programs be individualized? Sports Health. 2019;11(6):535–542. doi: 10.1177/1941738119869945. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Melugin HP, Larson DR, Fleisig GS, Conte S, Fealy SA, Dines JS, et al. Baseball pitchers' perceived effort does not match actual measured effort during a structured long-toss throwing program. Am J Sports Med. 2019;47(8):1949–1954. doi: 10.1177/0363546519850560. [DOI] [PubMed] [Google Scholar]
- 10.Robb AJ, Fleisig G, Wilk K, Macrina L, Bolt B, Pajaczkowski J. Passive ranges of motion of the hips and their relationship with pitching biomechanics and ball velocity in professional baseball pitchers. Am J Sports Med. 2010;38(12):2487–2493. doi: 10.1177/0363546510375535. [DOI] [PubMed] [Google Scholar]
- 11.Aguinaldo A, Escamilla R. Segmental power analysis of sequential body motion and elbow valgus loading during baseball pitching: comparison between professional and high school baseball players. Orthop J Sports Med. 2019;7(2):2325967119827924. doi: 10.1177/2325967119827924. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Ardern CL, Glasgow P, Schneiders A, Witvrouw E, Clarsen B, Cools A, Gojanovic B, Griffin S, Khan KM, Moksnes H, Mutch SA, Phillips N, Reurink G, Sadler R, Grävare Silbernagel K, Thorborg K, Wangensteen A, Wilk KE, Bizzini M. 2016 Consensus statement on return to sport from the First World Congress in Sports Physical Therapy, Bern. Br J Sports Med. 2016;50(14):853–864. doi: 10.1136/bjsports-2016-096278. [DOI] [PubMed] [Google Scholar]
- 13.Sgroi TA, Zajac JM. Return to throwing after shoulder or elbow injury. Curr Rev Musculoskelet Med. 2018;11(1):12–18. doi: 10.1007/s12178-018-9454-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Thorpe RT, Atkinson G, Drust B, Gregson W. Monitoring fatigue status in elite team-sport athletes: implications for practice. Int J Sports Physiol Perform. 2017;12(Suppl 2):S227–SS34. doi: 10.1123/ijspp.2016-0434. [DOI] [PubMed] [Google Scholar]
- 15.Vanrenterghem J, Nedergaard NJ, Robinson MA, Drust B. Training load monitoring in team sports: a novel framework separating physiological and biomechanical load-adaptation pathways. Sports Med. 2017;47(11):2135–2142. doi: 10.1007/s40279-017-0714-2. [DOI] [PubMed] [Google Scholar]
- 16.Saw AE, Kellmann M, Main LC, Gastin PB. Athlete self-report measures in research and practice: considerations for the discerning reader and fastidious practitioner. Int J Sports Physiol Perform. 2017;12(Suppl 2):S2127–S2S35. doi: 10.1123/ijspp.2016-0395. [DOI] [PubMed] [Google Scholar]
- 17.Saw AE, Main LC, Gastin PB. Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review. Br J Sports Med. 2016;50(5):281–291. doi: 10.1136/bjsports-2015-094758. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Crockett HC, Gross LB, Wilk KE, Schwartz ML, Reed J, O'Mara J, et al. Osseous adaptation and range of motion at the glenohumeral joint in professional baseball pitchers. Am J Sports Med. 2002;30(1):20–26. doi: 10.1177/03635465020300011701. [DOI] [PubMed] [Google Scholar]
- 19.Hibberd EE, Oyama S, Myers JB. Increase in humeral retrotorsion accounts for age-related increase in glenohumeral internal rotation deficit in youth and adolescent baseball players. Am J Sports Med. 2014;42(4):851–858. doi: 10.1177/0363546513519325. [DOI] [PubMed] [Google Scholar]
- 20.Reuther KE, Sheridan S, Thomas SJ. Differentiation of bony and soft-tissue adaptations of the shoulder in professional baseball pitchers. J Shoulder Elbow Surg. 2018;27(8):1491–1496. doi: 10.1016/j.jse.2018.02.053. [DOI] [PubMed] [Google Scholar]
- 21.Thomas SJ, Cobb J, Sheridan S, Rauch J, Paul RW. Chronic adaptations of the posterior rotator cuff in professional pitchers. Am J Sports Med. 2021;49(4):892–898. doi: 10.1177/0363546520988688. [DOI] [PubMed] [Google Scholar]
- 22.Thomas SJ, Sarver JJ, Ebaugh DD, Paul RW, Osman A, Topley M, et al. Chronic adaptations of the long head of the biceps tendon and groove in professional baseball pitchers. J Shoulder Elbow Surg. 2021;31(5):1047–1054. doi: 10.1016/j.jse.2021.10.034. [DOI] [PubMed] [Google Scholar]
- 23.Pexa BS, Ryan ED, Hibberd EE, Teel E, Rucinski TJ, Myers JB. Infraspinatus cross-sectional area and shoulder range of motion change following live-game baseball pitching. J Sport Rehabil. 2019;28(3):236–242. doi: 10.1123/jsr.2017-0158. [DOI] [PubMed] [Google Scholar]
- 24.Reagan KM, Meister K, Horodyski MB, Werner DW, Carruthers C, Wilk K. Humeral retroversion and its relationship to glenohumeral rotation in the shoulder of college baseball players. Am J Sports Med. 2002;30(3):354–360. doi: 10.1177/03635465020300030901. [DOI] [PubMed] [Google Scholar]
- 25.Wilk KE, Macrina LC, Arrigo C. Passive range of motion characteristics in the overhead baseball pitcher and their implications for rehabilitation. Clin Orthop Relat Res. 2012;470(6):1586–1594. doi: 10.1007/s11999-012-2265-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Mirabito NS, Topley M, Thomas SJ. Acute effect of pitching on range of motion, strength, and muscle architecture. Am J Sports Med. 2022;50(5):1382–1388. doi: 10.1177/03635465221083325. [DOI] [PubMed] [Google Scholar]
- 27.Escamilla RF, Yamashiro K, Mikla T, Collins J, Lieppman K, Andrews JR. Effects of a short-duration stretching drill after pitching on elbow and shoulder range of motion in professional baseball pitchers. Am J Sports Med. 2017;45(3):692–700. doi: 10.1177/0363546516671943. [DOI] [PubMed] [Google Scholar]
- 28.Paul RW, Sheridan S, Reuther KE, Kelly JD, Thomas SJ. The contribution of posterior capsule hypertrophy to soft tissue glenohumeral internal rotation deficit in healthy pitchers. Am J Sports Med. 2022;50(2):341–346. doi: 10.1177/03635465211062598. [DOI] [PubMed] [Google Scholar]
- 29.Reinold MM, Wilk KE, Macrina LC, Sheheane C, Dun S, Fleisig GS, et al. Changes in shoulder and elbow passive range of motion after pitching in professional baseball players. Am J Sports Med. 2008;36(3):523–527. doi: 10.1177/0363546507308935. [DOI] [PubMed] [Google Scholar]
- 30.Gabbett TJ. The training-injury prevention paradox: should athletes be training smarter and harder? Br J Sports Med. 2016;50(5):273–280. doi: 10.1136/bjsports-2015-095788. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Andrade R, Wik EH, Rebelo-Marques A, Blanch P, Whiteley R, Espregueira-Mendes J, Gabbett TJ. Is the acute: chronic workload ratio (ACWR) associated with risk of time-loss injury in professional team sports? A systematic review of methodology, variables and injury risk in practical situations. Sports Med. 2020;50(9):1613–1635. doi: 10.1007/s40279-020-01308-6. [DOI] [PubMed] [Google Scholar]
- 32.Impellizzeri FM, Tenan MS, Kempton T, Novak A, Coutts AJ. Acute: chronic workload ratio: conceptual issues and fundamental pitfalls. Int J Sports Physiol Perform. 2020:1-7. [DOI] [PubMed]
- 33.Impellizzeri FM, Ward P, Coutts AJ, Bornn L, McCall A. Training load and injury part 2: questionable research practices hijack the truth and mislead well-intentioned clinicians. J Orthop Sports Phys Ther. 2020;50(10):577–584. doi: 10.2519/jospt.2020.9211. [DOI] [PubMed] [Google Scholar]
- 34.Impellizzeri FM, Woodcock S, Coutts AJ, Fanchini M, McCall A, Vigotsky AD. What role do chronic workloads play in the acute to chronic workload ratio? Time to dismiss ACWR and its underlying theory. Sports Med. 2021;51(3):581–592. doi: 10.1007/s40279-020-01378-6. [DOI] [PubMed] [Google Scholar]
- 35.Vellios EE, Pinnamaneni S, Camp CL, Dines JS. Technology used in the prevention and treatment of shoulder and elbow injuries in the overhead athlete. Curr Rev Musculoskelet Med. 2020;13(4):472–478. doi: 10.1007/s12178-020-09645-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Camp CL, Loushin S, Nezlek S, Fiegen AP, Christoffer D, Kaufman K. Are wearable sensors valid and reliable for studying the baseball pitching motion? An independent comparison with marker-based motion capture. Am J Sports Med. 2021;49(11):3094–3101. doi: 10.1177/03635465211029017. [DOI] [PubMed] [Google Scholar]
- 37.Camp CL, Tubbs TG, Fleisig GS, Dines JS, Dines DM, Altchek DW, Dowling B. The relationship of throwing arm mechanics and elbow varus torque: within-subject variation for professional baseball pitchers across 82,000 throws. Am J Sports Med. 2017;45(13):3030–3035. doi: 10.1177/0363546517719047. [DOI] [PubMed] [Google Scholar]
- 38.Kibler WB, Sciascia A, Thomas SJ. Glenohumeral internal rotation deficit: pathogenesis and response to acute throwing. Sports Med Arthrosc Rev. 2012;20(1):34–38. doi: 10.1097/JSA.0b013e318244853e. [DOI] [PubMed] [Google Scholar]
- 39.Lazu AL, Love SD, Butterfield TA, English R, Uhl TL. The relationship between pitching volume and arm soreness in collegiate baseball pitchers. Int J Sports Phys Ther. 2019;14(1):97–106. doi: 10.26603/ijspt20190097. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Zaremski JL, Zeppieri G, Jones DL, Tripp BL, Bruner M, Vincent HK, et al. Unaccounted workload factor: game-day pitch counts in high school baseball pitchers-an observational study. Orthop J Sports Med. 2018;6(4):2325967118765255. doi: 10.1177/2325967118765255. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Lizzio VA, Smith DG, Jildeh TR, Gulledge CM, Swantek AJ, Stephens JP, et al. Importance of radar gun inclusion during return-to-throwing rehabilitation following ulnar collateral ligament reconstruction in baseball pitchers: a simulation study. J Shoulder Elbow Surg. 2020;29(3):587–592. doi: 10.1016/j.jse.2019.08.014. [DOI] [PubMed] [Google Scholar]
- 42.Slenker NR, Limpisvasti O, Mohr K, Aguinaldo A, Elattrache NS. Biomechanical comparison of the interval throwing program and baseball pitching: upper extremity loads in training and rehabilitation. Am J Sports Med. 2014;42(5):1226–1232. doi: 10.1177/0363546514526152. [DOI] [PubMed] [Google Scholar]
- 43.Kalkhoven JT, Watsford ML, Coutts AJ, Edwards WB, Impellizzeri FM. Training load and injury: causal pathways and future directions. Sports Med. 2021;51(6):1137–1150. doi: 10.1007/s40279-020-01413-6. [DOI] [PubMed] [Google Scholar]
- 44.Chalmers PN, English J, Cushman DM, Zhang C, Presson AP, Yoon S, et al. The ulnar collateral ligament responds to stress in professional pitchers. J Shoulder Elbow Surg. 2021;30(3):495–503. doi: 10.1016/j.jse.2020.06.027. [DOI] [PubMed] [Google Scholar]
- 45.Buckthorpe M, Frizziero A, Roi GS. Update on functional recovery process for the injured athlete: return to sport continuum redefined. Br J Sports Med. 2019;53(5):265–267. doi: 10.1136/bjsports-2018-099341. [DOI] [PubMed] [Google Scholar]
- 46.Staunton CA, Abt G, Weaving D, Wundersitz DWT. Misuse of the term 'load' in sport and exercise science. J Sci Med Sport. 2021;25(5):439–444. doi: 10.1016/j.jsams.2021.08.013. [DOI] [PubMed] [Google Scholar]
- 47.Yung KK, Ardern CL, Serpiello FR, Robertson S. Characteristics of complex systems in sports injury rehabilitation: examples and implications for practice. Sports Med Open. 2022;8(1):24. doi: 10.1186/s40798-021-00405-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Sporer BC, Windt J. Integrated performance support: facilitating effective and collaborative performance teams. Br J Sports Med. 2018;52(16):1014–1015. doi: 10.1136/bjsports-2017-097646. [DOI] [PubMed] [Google Scholar]
- 49.Dijkstra HP, Pollock N, Chakraverty R, Ardern CL. Return to play in elite sport: a shared decision-making process. Br J Sports Med. 2017;51(5):419–420. doi: 10.1136/bjsports-2016-096209. [DOI] [PubMed] [Google Scholar]
- 50.Bittencourt NFN, Meeuwisse WH, Mendonça LD, Nettel-Aguirre A, Ocarino JM, Fonseca ST. Complex systems approach for sports injuries: moving from risk factor identification to injury pattern recognition-narrative review and new concept. Br J Sports Med. 2016;50(21):1309–1314. doi: 10.1136/bjsports-2015-095850. [DOI] [PubMed] [Google Scholar]