Relevant bibliographies by topics / Baseball pitcher

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Baseball pitcher'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "Baseball pitcher"

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Chalmers, Peter, Rocco Bassora, Chris Inzerillo, Andrew Beharrie, Anthony Romeo, and Brandon Erickson. "Training with Lighter Baseballs Increases Velocity Without Increasing Injury Risk." Orthopaedic Journal of Sports Medicine 8, no. 7_suppl6 (2020): 2325967120S0034. http://dx.doi.org/10.1177/2325967120s00341.

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Objectives: Pitch velocity has become an increasingly popular metric by which pitchers are graded and compared. Training programs that utilize weighted balls have been effective in increasing velocity but at the cost of increased injury risk. The purpose of this study was to determine if a baseball pitcher-training program utilizing lighter baseballs could increase fastball velocity without increasing injury risk. The author’s hypothesized that the training program with lighter baseballs would increase fastball velocity without causing injuries during the training program to the participants Methods: All baseball pitchers who participated in a 15-week pitching mechanic and velocity training program were included. Training program was broken down into three phases, and each participant went through the same program. Lighter balls (4oz and 3oz) and standard baseballs (5oz) were utilized as part of the training program. Weighted (heavier) balls were not used. Velocity was measured at four time points throughout the program. Injury rates for all players were recorded throughout the entire program. Results: 48 male pitchers aged 10-17 (average age: 14.7 +/- 1.8) years started the program and 44 had complete data and were included in the analysis. No pitcher sustained a baseball-related injury while participating in the training program (one player broke his ankle playing basketball, one player moved, one did not have baseline velocity data, and one experienced biceps soreness after participating in back to back showcases against recommendations). Fastball velocity increased by an average of 4.8mph (95% confidence intervals 4.1 - 5.5mph). Overall 43/44 players (98%) had an increase in fastball velocity over the course of the program. Conclusions: A 15-week baseball pitcher-training program with lighter baseballs significantly improved pitching velocity without significantly increasing injuries. Lighter baseballs should be considered instead of weighted baseballs when attempting to increase a pitcher’s velocity.
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Erickson, Brandon J., Peter N. Chalmers, Michael J. Axe, and Anthony A. Romeo. "Exceeding Pitch Count Recommendations in Little League Baseball Increases the Chance of Requiring Tommy John Surgery as a Professional Baseball Pitcher." Orthopaedic Journal of Sports Medicine 5, no. 3 (2017): 232596711769508. http://dx.doi.org/10.1177/2325967117695085.

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Background: Empirical evidence has suggested a connection between youth pitch counts and subsequent elbow injury. For players within the Little League World Series (LLWS), detailed historical player data are available. Some of these players progress to both professional play and require an ulnar collateral ligament reconstruction (UCLR). Purpose: To determine the percentage of LLWS pitchers who proceed to play professional (major or minor league) baseball, the rate of UCLR in former LLWS pitchers who played professional baseball, and the risk to those who exceeded current pitch count recommendations while playing in the LLWS. Study Design: Cohort study; Level of evidence, 3. Methods: All LLWS pitchers from 2001 through 2009 from all teams and countries were identified, and all performance data were extracted. A professional (major and minor league) baseball database was then searched to determine whether each former LLWS pitcher played professional baseball. These professional players were then searched for using publicly available databases to determine whether they underwent UCLR. Results: Overall, 638 adolescents pitched in the LLWS between 2001 and 2009; 62 (10%) progressed to professional play. Of the 56 minor league players, 25 (45%) pitched. Of the 6 Major League Baseball players, 3 (50%) pitched. Three former LLWS pitchers (5%) who played professionally underwent UCLR. In former LLWS pitchers who exceeded pitch counts and played professionally, 50% (2/4) required UCLR, while only 1.7% (1/58) of those who did not exceed pitch count recommendations required UCLR ( P = .009). Similarly, among former LLWS pitchers who subsequently played professionally, 23.1% of those who played as a pitcher required UCLR while 0% of those who also played other positions required UCLR ( P = .008). Conclusion: Progression from LLWS pitching to professional baseball is uncommon. Among youth players, both diversification (playing other positions besides pitcher) as well as following current pitch limit regulations may protect against UCLR.
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Greiner, Justin J., Geoffrey S. Baer, and Timothy A. McGuine. "PITCH COUNTS IN YOUTH BASEBALL PLAYERS: A COMPARISON TO PITCH SMART GUIDELINES." Orthopaedic Journal of Sports Medicine 8, no. 4_suppl3 (2020): 2325967120S0023. http://dx.doi.org/10.1177/2325967120s00234.

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Background: Overthrowing injuries in youth baseball players have been linked with pitching behaviors such as as high pitch counts, inadequate rest, and participating in throwing activities throughout the year. Pitch Smart guidelines were developed as an initiative between Major League Baseball and USA Baseball to provide recommendations for youth baseball athletes to help decrease the risk of injuries from overthrowing. Purpose: The purpose of this study was to perform a quantitative analysis of pitch counts in youth baseball players and evaluate compliance with Pitch Smart guidelines. Methods: Local youth baseball teams competing in nine and under (9U) to fourteen and under (14U) age brackets were recruited to track pitches during the summer baseball season. A tablet with a pitch counting application was used to record pitches for each pitcher of the study team and their opponents. Days of rest between games was calculated for the study teams only and not opponents. Pitch counts and days of rest for each pitcher were compared to the recommended Pitch Smart guidelines. Continued prospective collection of data is ongoing through the 2019 summer. Results: Interim review of 23 youth baseball teams using a tablet allowed analysis of 181 pitchers of the 23 study teams using tablets and 285 pitchers of 98 opponent teams. Violation of Pitch Smart guidelines occurred in 14 (60.9%) study teams and 29 (16.0%) pitchers. Of these violations, 27 (93%) pitchers had insufficient rest between games while 2 (7%) pitchers exceeded daily maximum pitches. Further, 8 (35%) teams had more than one player violate guidelines. Pitch smart daily maximum pitch counts were violated in 2 of 98 (2.0%) opponent teams and 2 of 285 (0.7%) of opponent pitchers Conclusion: A total of 61% of youth baseball teams and 16% of pitchers in this study violated Pitch Smart guidelines at interim analysis. The vast majority of guideline violations were due to inadequate rest between games. The high rate of Pitch Smart violations suggests that further education of coaches, parents, and athletes regarding these guidelines, with emphasis on rest recommendations, is necessary to prevent overthrowing injuries in youth baseball players. [Table: see text]
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Trotter, Cameron A., Justin J. Greiner, Tim McGuine, and Geoffrey S. Baer. "PITCHING IN YOUTH SOFTBALL: HOW MUCH ARE PITCHERS THROWING?" Orthopaedic Journal of Sports Medicine 9, no. 7_suppl3 (2021): 2325967121S0004. http://dx.doi.org/10.1177/2325967121s00049.

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Background: Softball is a popular sport among youth female athletes. While multiple youth baseball studies have evaluated the relationship of injury to pitch counts, there is a paucity of literature for youth softball. In contrast to the numerous youth baseball leagues adhering to pitching guidelines, pitch counts are frequently not enforced in youth softball which results in pitchers with exceedingly high volumes. Purpose: The purpose of this study was to perform a quantitative analysis of pitching volume in youth softball players. We hypothesized that the majority of pitches would be thrown by a small proportion of pitchers on each team. Methods: Seventy youth softball teams including 538 pitchers competing in age brackets eight and under (8U) to fourteen and under (14U) between Spring 2017 and Fall 2019. Game dates and pitch counts were collected for each player using an electronic application. Games played on two or more consecutive days were defined as a tournament. The three highest-volume pitchers from each team defined by total season pitches were analyzed for comparison to the average pitcher. Results: 538 pitchers on 70 teams were included. The average pitcher threw 813 pitches per year and appeared in 20.0% of games and the average high-volume pitcher threw 2500 pitches per year and appeared in 54.5% of games. The highest-volume pitcher from each team threw 40% of all recorded pitches, the second highest 27.2%, and the third highest 15.2%, totaling 82.4% of all team pitches. Single day pitch counts of >100 and >200 occurred in 17.7%, and 1.1% of same day games with the average pitcher and in 31.2%, and 2.4% of same day games with the average highest-volume pitcher. Tournament pitch counts of >100 and >200 occurred in 51.0% and 13.8% of tournaments with the average pitcher and in 81.4% and 30.8% of tournaments with the average highest-volume pitcher. The average and highest-volume pitcher threw pitches in two or more games on the same day in 37.5% and 48.6% of possible games while pitching two or more consecutive days in 64.0% and 79.6% of possible games, respectively. Conclusion: Softball pitchers throw high volumes of pitches while also pitching multiple days consecutively. A disparity among pitchers on softball teams exists as 82.4% of team pitches are thrown by three pitchers. These high-volume pitchers may be engaging in unsustainable pitching practices that could predispose to injury. Tables: [Table: see text]
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Okoroha, Kelechi R., Jason E. Meldau, Vincent A. Lizzio, et al. "Effect of Fatigue on Medial Elbow Torque in Baseball Pitchers: A Simulated Game Analysis." American Journal of Sports Medicine 46, no. 10 (2018): 2509–13. http://dx.doi.org/10.1177/0363546518782451.

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Background: The incidence of overuse injury to the elbow among baseball pitchers continues to rise, despite extensive efforts at pitch count regulations and emphasis on proper throwing mechanics. Purpose: To determine if the medial elbow experiences increased torque levels as a baseball pitcher fatigues through the course of a simulated game. Study Design: Descriptive laboratory study. Methods: High school and collegiate baseball pitchers were recruited for this simulated game study. Each pitcher completed a simulated game consisting of 6 innings and a standardized pitching scheme of fastballs, curveballs, and changeups. In total, each pitcher threw 90 pitches. Fatigue was reported per inning with a visual analog scale, and pitch velocity was captured per pitch with a radar gun. Outcome measures were assessed with a validated mobile sensor and included medial elbow torque, arm speed, arm rotation, and arm slot. Linear and quadratic regression modeling was used to evaluate the relationship between pitcher fatigue and pitching kinematics. Results: A total of 11 pitchers (mean age, 17.6 years; range, 15-20 years) completed the study. Visual analog scale fatigue scores increased 0.72 points per inning pitched ( P < .01, effect size = 0.64). Medial elbow torque also increased beyond inning 3, with an increase of 0.84 N·m each inning ( P < .01, effect size = 0.08), while pitch velocity decreased (0.28 mph per inning, P < .01, effect size = 0.27). Fastballs generated the greatest amount of medial elbow torque (49.3 ± 1.4 N·m, P < .01, effect size = 0.24). There were no differences in arm rotation ( P = .42) or arm speed ( P = .80) as the game progressed. However, arm slot decreased with each successive inning (0.73° on average per inning, P = .03, effect size = 0.12). No adverse outcomes were noted with use of the mobile sensor. Conclusion: In this simulated game analysis, pitchers experienced increased fatigue after each successive inning. While the average pitch velocity declined with each successive inning, the torque on the medial elbow increased after inning 3. These findings signify a possible relationship between fatigue and injury risk.
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Whiteside, David, Douglas N. Martini, Ronald F. Zernicke, and Grant C. Goulet. "Changes in a Starting Pitcher’s Performance Characteristics Across the Duration of a Major League Baseball Game." International Journal of Sports Physiology and Performance 11, no. 2 (2016): 247–54. http://dx.doi.org/10.1123/ijspp.2015-0121.

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Purpose:With a view to informing in-game decision making as it relates to strategy and pitcher health, this study examined changes in pitching-performance characteristics across 9 innings of Major League Baseball (MLB) games.Methods:129 starting MLB pitchers met the inclusion criteria for this study. Pitch type, speed, ball movement, release location, and strike-zone data—collected using the MLB’s ball-tracking system, PITCHf/x—were obtained for 1,514,304 pitches thrown from 2008 to 2014.Results:Compared with the 1st inning, the proportion of hard pitches thrown decreased significantly until the 7th inning, while the proportions of breaking and off-speed pitches increased. Significant decreases in pitch speed, increases in vertical movement, and decreases in release height emerged no later than the 5th inning, and the largest differences in all variables were generally recorded between the 1st inning and the late innings (7–9). Pitchers were most effective during the 2nd inning and significantly worse in innings 4 and 6.Conclusion:These data revealed that several aspects of a starting pitcher’s pitching characteristics exhibited changes from baseline as early as the 2nd or 3rd inning of an MLB game, but this pattern did not reflect the changes in his effectiveness. Therefore, these alterations do not appear to provide reasonable justification for relieving a starting pitcher, although future work must address their relevance to injury. From an offensive standpoint, batters in the MLB should anticipate significantly more hard pitches during the early innings but more breaking and off-speed pitches, with decreasing speed, as the game progresses.
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Irawan, Fajar Awang, and Chuang Long-Ren. "Baseball and biomechanics: Injury prevention for baseball pitcher." Jurnal Keolahragaan 7, no. 1 (2019): 57–64. http://dx.doi.org/10.21831/jk.v7i1.24636.

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Pitching was the fastest motion in baseball. Upper extremity has important roles especially in shoulder, elbow, wrist, and fingers. The purpose of this study was to integrate the information in a resume of biomechanical pitching and baseball pitcher’s injuries. The data base used refers to PubMed, SAGE, and Elsevier and several relevance journals related to baseball and injuries. Source refers to the data since December 2017 to the oldest 2000 to get data source in baseball pitcher injuries. Upper arm has the prominent role when pitching to get maximum motion and joints stabilize. Rotator cuff muscle generate rotation in the shoulder while pitching and control shoulder joints in the lower arm’s muscles and joints. Baseball pitcher has a special skill in the strength, speed, and endurance. They had to keep their performance to avoid from injury especially shoulder and elbow injuries. Biomechanical analysis can help to evaluated performance in monitoring dan give recommendation to elevate skills and prevent injury. Knowledge and understanding about basic of pitching have to mastering before elevate to the next level. Further study can focus on the time for the pitcher to improve the skills and maximizing the pitch type to avoid from injuries.
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Makhni, Eric C., Jason E. Meldau, Jeff Stephens, et al. "Relationship Between Pitcher Fatigue and Medial Elbow Torque in Baseball Pitchers: A Simulated Game Analysis." Orthopaedic Journal of Sports Medicine 6, no. 7_suppl4 (2018): 2325967118S0007. http://dx.doi.org/10.1177/2325967118s00073.

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Objectives: The incidence of overuse injury to the elbow in baseball pitchers continues to rise, despite exhaustive efforts at pitch count regulations and emphasis on proper throwing mechanics. The goal of this study was to determine if the medial elbow experiences increased torque levels as the pitcher fatigues through the course of a simulated game. Methods: Competitive baseball pitchers were recruited for this simulated game study. Medial elbow torque was assessed using a validated mobile sensor that recorded medial elbow torque during the throwing motion. A radar gun was used to capture pitch velocity for each recorded pitch. Each pitcher completed a simulated game consisting of 6 innings and a standardized pitching scheme of fastballs, curveballs, and change-ups. Visual analog scores (VAS) measuring fatigue were recorded in between each inning. In total, each pitcher threw 90 pitches. Data was recorded every pitch to include ball velocity, medial elbow torque, arm speed, arm rotation, and arm slot. Results: A total of 11 pitchers (average age 17.6 years; range 15-20 years) completed the study. No adverse outcomes were noted with use of the mobile sensor. VAS scores increased 0.716 points per inning pitched (p<0.001). Medial elbow torque also was found to increase with successive innings, with an increase of 0.836 Nm each inning (p<0.001), while average pitch velocity was found to decrease as the game progressed (0.28 mile per hour decrease per inning; p<0.001). Fastballs generated the highest amount of medial elbow torque. There were no differences found in arm rotation or arm speed as the game progressed. However, the arm slot was found to decrease with each successive inning (0.731 degree decrease per inning; p<0.001). Conclusion: In this simulated game analysis, pitchers were noted to experience increase fatigue after each successive inning. While the average fastball velocity decreased from inning-to-inning, the medial elbow torque was found to increase, signifying a possible risk factor for overuse injury to the medial elbow.
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Tajika, Tsuyoshi, Noboru Oya, Tsuyoshi Ichinose, et al. "Relation between grip and pinch strength and pitch type in high school pitchers with and without elbow symptoms." Journal of Orthopaedic Surgery 28, no. 1 (2020): 230949901989074. http://dx.doi.org/10.1177/2309499019890743.

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Objective: Gripping and pinching a ball is a fundamentally important part of the kinetic chain for throwing baseball pitches of various types. This study of high school pitchers was conducted to assess the association between grip and pinch strength, the pitch type, and the history of elbow symptoms. Methods: We examined 133 high school baseball pitchers, all of whom had completed a self-administered questionnaire including items related to pitch type throwing ratios, the age at starting each pitch type, and throwing-related elbow joint pain sustained during the prior 3 years. We measured grip strength and the bilateral side tip, key, and palmar pinch strengths. Comparisons were made between the participants with and without an elbow symptom history to assess the grip and each pinch strength, throwing ratio of pitch type, and the age at starting to throw each pitch type. Results: Pitchers with an elbow symptom history exhibited less difference between the grip strength on the throwing side than those with no elbow symptom history ( p = 0.04). No difference was found between participants with and without an elbow symptom history in terms of pinch strength, the throwing ratios of pitch types, or the age at starting to throw pitches of each type. Positive significant association was found between pinch strength on the pitching side and the forkball and screwball throwing ratio ( r = 0.27, p = 0.002). Conclusion: Grip strength might influence high school baseball pitcher elbow conditions. The frequency of certain pitch types might develop pinch strength in high school baseball pitchers.
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Pareek, Ayoosh, Chad W. Parkes, Alexey A. Leontovich, et al. "Are Baseball Statistics an Appropriate Tool for Assessing Return to Play in Injured Players: An Analysis of Statistically Variability in Healthy Players Using a Machine Learning Approach." Orthopaedic Journal of Sports Medicine 7, no. 7_suppl5 (2019): 2325967119S0039. http://dx.doi.org/10.1177/2325967119s00397.

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Objectives: Traditional pitching statistics (ERA, WHIP, etc) have been used as surrogates for pitcher performance without being validated. Even amongst healthy pitchers, the normal variability of these parameters has not yet been established. The purpose of this study was to determine the normal variability of basic and advanced pitching statistics in non-injured Major League Baseball (MLB) pitchers. It is our hope that this work will serve as the foundation for the identification and implementation of validated, pitcher dependent statistical measures that can be used to assess return to play performance following injury. Methods: Publicly available data from MLB Statcast and Pitch/Fx databases was used to analyze all non-injured MLB pitchers during 2015 and 2016 seasons who pitcher greater than 100 innings each season without injury. Traditional and advanced baseball pitching statistics were analyzed. The variability of each parameter was assessed by computing coefficient of variation (CV) between individual pitchers and across all pitchers. A CV below 10 is typically indicative of a relatively constant parameter, and parameters with a CV > 10 are generally considered inconsistent and unreliable. Results: A total of 118 pitchers met all inclusion criteria. For each of these healthy pitchers, 38 basic/traditional parameters and 17 advanced parameters were analyzed. Of the traditional pitcher statistics, only 1 (3%) demonstrated a CV value < 10 (average fastball velocity [FBv]; CV 1.5) (Figure 1). In advanced statistics, 9 of 17 (53%) variables demonstrated acceptable consistency as evidenced by a CV value < 10 (Figure 2). Release position from plate (release_pos_y) along with velocity from the plate (vy0) where the two most constant advanced parameters. When separated by pitch type, these two parameters were the most constant (lowest CV) in every pitch type. Conclusion: The validity and variability of baseball statistics as surrogate markers for performance after injury/surgery have not yet been evaluated. It is critical that baseball statistics undergo proper vetting prior to being used to assess recovery. This study reveals average fastball velocity and release position from the plate to be the least variable basic and advanced baseball statistics in MLB pitchers. In total, only 10 of the 55 statistics analyzed demonstrated acceptable consistency and reliability. This study can be further used to determine the minimum time that each of these variables needs to be followed to ensure an appropriate sample size is obtained to detect significant differences in pre- and post- injury performance. [Figure: see text][Figure: see text]
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Dissertations / Theses on the topic "Baseball pitcher"

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Nicholson, Michael Eugene. "The effect of overload and traditional pitcher conditioning on the velocity of pitched baseballs." Master's thesis, This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-01262010-020057/.

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Glasser, Jacob. "Pitch it to Me: The Determinants of a Professional Baseball Pitcher’s Salary." Scholarship @ Claremont, 2017. http://scholarship.claremont.edu/cmc_theses/1658.

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The professional sports industry is one of the most engaging and entertaining markets in the United States. Specifically, Major League Baseball is unique in the sense that it is America’s pastime and oldest American sport. Professional baseball teams are businesses that trade commodities in the form of baseball players. Unlike publicly traded stocks, baseball players are not traded on an exchange. So, what determines the “price” of professional baseball players? More specifically, what determines the price of professional pitchers in the MLB? My study reveals that pitching is an extremely subjective aspect of baseball and there is no one statistic that can be used to forecast a pitcher’s salary. Based on my research and analysis, I investigate which performance metrics are the most important in determining a professional pitcher’s salary and if these metrics can ultimately be used to forecast future pitchers’ salaries in order for baseball franchises to acquire undervalued pitchers.
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Ström, Martin. "What happens in the shadows? : A quantitative analysis on the effect of shadows in baseball." Thesis, Linnéuniversitetet, Institutionen för idrottsvetenskap (ID), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-104253.

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Baseball is one of the most statistically documented sports in the world. Every statistical outcome in baseball starts with the pitcher and the plate appearance. In baseball, it is believed that when shadows are present between the pitcher’s mound and the batter’s box, the pitcher is at an advantage. Therefore, the aim of the study was to identify if there is an advantage for pitchers pitching with shadows separating the pitcher’s mound from the batter’s box. Only games from Major League Baseball in which the shadows were present between the pitcher’s mound and batter’s box were analyzed. Analyzed variables were comprised of traditional statistical outcomes categorized as good or bad outcomes. Furthermore, good and bad outcomes were analyzed using their ordinal subcategories rated from 1 to 4. Differences between good and bad outcomes of plate appearances, when shadows were and were not present, was analyzed using a Mann-Whitney U Test.  The results of the study indicate that shadows do not have a significant effect on the outcome of plate appearances. Moreover, pitchers do not have an advantage pitching while shadows are present between them and the batter’s box. Frequencies of outcomes with shadows present was much the same to outcomes without the shadows present. In conclusion, it does not appear that shadows influence the outcome of plate appearances. However, further research on statistical metrics and their effect on plate appearances is necessary.
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Erkel, Jeremy J. "The changes in pitching mechanics and pitch velocity during a seven-inning simulated game in high school baseball pitchers a prospective descriptive study /." Morgantown, W. Va. : [West Virginia University Libraries], 2007. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=5354.

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Thesis (M.S.)--West Virginia University, 2007.<br>Title from document title page. Document formatted into pages; contains viii, 138 p. : ill. (some col.). Includes abstract. Includes bibliographical references.
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Facciolo, Philip Joseph III. "Salary determination of arbitration and free agent Major League Baseball pitchers 1984--2003 /." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file 0.73Mb., 139 p, 2005. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:1428205.

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Monteleone, Brian R. "Social facilitative effects of dominant motor skills in NCAA Division I baseball pitchers." Virtual Press, 1993. http://liblink.bsu.edu/uhtbin/catkey/864940.

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This study used archival data retrieved from the 1992-1993 baseball season from Ball State University. Pitching data were used from thirteen pitchers, ages ranging 18-22, from all practices (fall and winter) and games (home and away conference and non-conference). The dependent variable was the strikes per balls ratio, multiplied by number of batters faced. Two hypotheses were generated: (1) pitchers would perform better, as defined by the strikes per balls ratio, in game situations than in practice; (2) pitchers would perform better, as defined by the strikes per balls ratio, in home games than away games. Practice conditions duplicated game conditions except for the presence of an audience. Results were analyzed by a multivariate repeated measures analysis of variance (MANOVA) and followed up by a univariate analysis of variance (ANOVA). Sufficient data were available for windup fastballs and windup curveballs. Data wereanalyzed for (1) practice versus home and away games, (2) home versus away, conference and non-conference games, and (3) practice versus nonconference games. Data were positively skewed and were modified by a logarithmic transformation. The transformed data for practice versus nonconference games showed a significant multivariate effect, E(2, 98) = 6.90, A = .002. A univariate analysis test showed significant effects for a windup curveball, F(1, 99) = 13.33, . < .000. The univariate test for the windup fastball was not significant. These results support the hypothesis that pitchers will perform better in game conditions than in practice. The transformed data for practice versus home and away games showed a significant multivariate effect, E(4, 194) = 3.52, l . = .008. A univariate analysis showed significant effects for a windup curveball, E(2, 98) = 6.90, P_= .002. These results supported the first hypothesis which stated pitchers would perform better in game conditions than in practice. Results were not significant for the windup fastball. A moderate association between performance conditions and both dependent variables, eta2 = .13, was obtained. The association for the windup curveball was almost the same, eta2 = .12.<br>Department of Psychological Science
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Ishii, Brian. "Using Pitch Tipping For Baseball Pitch Prediction." DigitalCommons@CalPoly, 2021. https://digitalcommons.calpoly.edu/theses/2311.

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Data Analytics and technology have changed baseball as we know it. From the increase in defensive shifts to teams using cameras in the outfield to steal signs, teams will try anything to win. One way to gain an edge in baseball is to figure out what pitches a pitcher will pitch. Pitch prediction is a popular task to try to accomplish with all the data that baseball provides. Most methods involve using situational data like the ball and strike count. In this paper, we try a different method of predicting pitch type by only looking at the pitcher's pose in the set position. We do this to find a pitcher's tell or "tip". In baseball, if a pitcher is tipping their pitches, they are doing something that gives away what they will pitch. This could be because the pitcher changes the grip on the ball only for some pitches or something as small as a different flex in their wrist. Professional baseball players will study pitchers before they pitch the ball to try to pick up on these tips. If a tip is found, the batters have a significant advantage over the pitcher. Our paper uses pose estimation and object detection to predict the pitch type based on the pitcher's set position before throwing the ball. Given a successful model, we can extract the important features or the potential tip from the data. Then, we can try to predict the pitches ourselves like a batter. We tested this method on three pitchers: Tyler Glasnow, Yu Darvish, and Stephen Strasburg. Our results demonstrate that when we predict pitch type at a 70\% accuracy, we can reasonably extract useful features. However, finding a useful tip from these features still requires manual observation.
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Gillis, Isabelle Leslie. "LONGITUDINAL DESCRIPTIVE PROFILE OF COLLEGIATE PITCHERS PARTICIPATING IN A SUMMER BASEBALL LEAGUE." UKnowledge, 2019. https://uknowledge.uky.edu/khp_etds/67.

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The purpose of this study was to provide a longitudinal profile of pitching performance in a cohort of pitchers over two collegiate seasons and a summer league. Thus, this study utilized a longitudinal design to evaluate the impact of summer league participation on subsequent collegiate regular season pitching performance. Specifically, the performance of a cohort of Division 1 collegiate baseball pitchers during the 2018 Spring collegiate season, 2018 Summer League season, and the 2019 Spring collegiate season was evaluated and stratified by pitcher designation, arm dominance, and academic status. Analyses of variance were used to identify main and interaction effects on pitching outcomes. The level of statistical significance was set at p < .05 for all analyses. Data were publicly accessed from thirty-seven Division I collegiate baseball pitchers who participated in a summer baseball league. Collectively, all pitchers significantly improved earned run average (p = .024), number of strikeouts (p = .011), and strikeout efficiency (p = .034) from 2018 to 2019 collegiate seasons. Whereas, starting pitchers (n = 15) yielded fewer earned runs (p = .039) and enhanced hit efficiency (p = .012) from 2018 to 2019 collegiate seasons. Relief pitchers (n = 16) produced significantly more strikeouts from 2018 to 2019 collegiate seasons (p = .012). Finally, there were no differences in pitching outcomes for closers (n = 6) over time (p > .05). Regarding arm dominance, right-handed pitchers (n = 23) improved win average (p = .001), strikeouts (p = .008) and strikeout efficiency (p = .031) from 2018 to 2019 collegiate seasons. Left-handed pitchers (n = 14) significantly improved earned run average (p = .015), earned runs (p = .048), and hit efficiency (p = .014). Regarding academic stratification, the freshman to sophomore cohort (n = 15) significantly improved number of pitches (p = .018), innings pitched (p = .019), hits (p = .029), and strikeouts (p = .003). Whereas, the sophomore to junior cohort (n = 21) significantly improved losses (p = .042) and hit efficiency (p =.028). The findings from this study indicate that participation in a summer baseball league may have improved several critical pitching metrics with implications to enhance team performance.
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Smrzley, Erica L. "The development of a screening tool for the prevention of shoulder injuries in baseball pitchers." Morgantown, W. Va. : [West Virginia University Libraries], 2007. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=5058.

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Nelson, Jamie Lynn. "The effects of video and cognitive imagery on throwing performance of baseball pitchers a single subject design /." Click here to access thesis, 2007. http://www.georgiasouthern.edu/etd/archive/spring2007/jamie_l_nelson/nelson_jamie_l_200701_ms.pdf.

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Thesis (M.S.)--Georgia Southern University, 2007.<br>"A thesis submitted to the Graduate Faculty of Georgia Southern University in partial fulfillment of the requirements for the degree Master of Science." Under the direction of Daniel R. Czech. ETD. Electronic version approved: May 2007. Includes bibliographical references (p. 49-54) and appendices.
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Books on the topic "Baseball pitcher"

1

George, Sullivan. Pitcher. Crowell, 1986.

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Glaser, Jason. Pitcher. Gareth Stevens, 2011.

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Christopher, Matt. Power pitcher. Norwood House Press, 2010.

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John, Thorn. The pitcher. Prentice Hall, 1987.

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Chris, Kreie, and Tiffany Sean ill, eds. Pressure pitcher. Stone Arch Books, 2010.

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Thorn, John. The pitcher. Prentice Hall Press, 1988.

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Christopher, Matt. Power pitcher. Norwood House Press, 2010.

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Christopher, Matt. Prime-time pitcher. Little, Brown, 1998.

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Prime-time pitcher. Little, Brown, 1998.

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Grey, Zane. The young pitcher. Beech Tree Books, 1992.

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Book chapters on the topic "Baseball pitcher"

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Gregory, Andrew. "A 12 Year Old Baseball Pitcher." In Mechanics, Pathomechanics and Injury in the Overhead Athlete. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12775-6_12.

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Bakshi, Neil K., and Michael T. Freehill. "A 16-Year-Old Baseball Pitcher with a Sore Elbow." In Mechanics, Pathomechanics and Injury in the Overhead Athlete. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12775-6_15.

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Nagami, Tomoyuki, Takatoshi Higuchi, and Kazuyuki Kanosue. "The Spin on a Baseball for Eight Different Pitches Thrown by an Elite Professional Pitcher." In Sports Performance. Springer Japan, 2015. http://dx.doi.org/10.1007/978-4-431-55315-1_26.

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Hirotsu, Nobuyoshi, and Mike Wright. "Modeling a Baseball Game to Optimize Pitcher Substitution Strategies Using Dynamic Programming." In Economics, Management and Optimization in Sports. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24734-0_9.

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Mahure, Siddharth A., Mina M. Abdelshahed, and Andrew S. Rokito. "Type II SLAP Tear in an 19-Year-Old Baseball Pitcher Treated with SLAP Repair." In The Biceps and Superior Labrum Complex. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54934-7_10.

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Chen, Chih-Cheng, Meng-Lung Lin, Yung-Tan Lee, Tien-Tze Chen, and Chih-Lun Huang. "Selection Best Starting Pitcher of the Chinese Professional Baseball League in 2010 Using AHP and TOPSIS Methods." In Frontiers in Computer Education. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27552-4_86.

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Ruggiero, John. "Evaluating Pitchers." In Frontiers in Major League Baseball. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-0831-5_6.

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Ruggiero, John. "Steroids in MLB: An Analysis of Pitchers." In Frontiers in Major League Baseball. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-0831-5_10.

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Chen, Reed, Dylan Siegler, Michael Fasko, Shunkun Yang, Xiong Luo, and Wenbing Zhao. "Baseball Pitch Type Recognition Based on Broadcast Videos." In Communications in Computer and Information Science. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1925-3_24.

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Siegler, Dylan, Reed Chen, Michael Fasko, Shunkun Yang, Xiong Luo, and Wenbing Zhao. "Semi-automated Development of a Dataset for Baseball Pitch Type Recognition." In Communications in Computer and Information Science. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1925-3_25.

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Conference papers on the topic "Baseball pitcher"

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Sumitani, Haruka, Kenta Oku, and Kyoji Kawagoe. "Predicting a Starting Pitcher in Baseball by Heuristic Rules." In the Ninth International C* Conference. ACM Press, 2016. http://dx.doi.org/10.1145/2948992.2949026.

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Darmawan, Rusdiana, Pitirani Agus, and Pipit. "Fatigue Impact to Mechanical Movement and Ball Velocity Pitcher Baseball." In Proceedings of the 5th International Conference on Physical Education, Sport, and Health (ACPES 2019). Atlantis Press, 2019. http://dx.doi.org/10.2991/acpes-19.2019.19.

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Gushiken, Shokei, Junpei Ikezaki, and Ryota Miyata. "Principal component analysis of starting pitcher indexes in Nippon professional baseball." In 2015 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS). IEEE, 2015. http://dx.doi.org/10.1109/iciibms.2015.7439490.

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Higuchi, Hiroshi, and Toshiro Kiura. "Flow-Structure Interaction Problem of a Pitched Baseball Without Spin (Knuckleball)." In ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting collocated with 8th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-30397.

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The “knuckleball” effect is believed to be caused by asymmetric flow separation over the baseball, but little is known about its flow physics. The baseball is gripped with the knuckles in a certain position and is pitched in a way that introduces nearly no rotation, resulting in erratic flight paths which confuse batters. In the experiment described in this paper, the flow near the seams of the baseball is visualized thoroughly and the velocity vector fields near the surface and in the wake are obtained with Digital Particle Image Velocimetry. Depending on its position, the seam is found to trigger the boundary layer transition thus delaying the separation, or to cause separation itself. Three-dimensional wake patterns associated with specific ball orientations are identified and related to the force variations on the ball.
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Chou, Ting-Hsuan, and Wei-Ta Chu. "Automatic Baseball Pitch Overlay." In ICMR '21: International Conference on Multimedia Retrieval. ACM, 2021. http://dx.doi.org/10.1145/3460426.3463576.

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Yang, Nicholas H., Kathleen Allen Rodowicz, and David Dainty. "Baseball Head Impacts to the Non-Helmeted and Helmeted Hydrid III ATD." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-38648.

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Traumatic brain injury may occur in baseball due to a head impact with a thrown, pitched, or batted ball. It has been shown that the average pitching speed of youth pitchers and high school pitchers is approximately 63 mph (28 m/s) and 74 mph (33 m/s), respectively. At pitching speeds of approximately 52 mph (23 m/s), the bat exit velocity (BEV) for metal bats has been shown to be approximately 100 mph (45 m/s). Head kinematics, such as linear and angular head accelerations, are often used to establish head injury risk for head impacts. With a possible ball impact velocity reaching speeds in excess of those typically tested for baseball headgear, it is necessary to understand how the head will respond to high velocity impacts in both helmeted and non-helmeted situations. In this study, head impacts were delivered to the front and side of a Hybrid III 50th percentile male anthropomorphic test device (ATD) by a baseball traveling at speeds of 60 mph (27 m/s), 75 mph (34 m/s), and 100 mph (45 m/s). Head impacts were performed on the non-helmeted ATD head and with the ATD wearing a standard batting helmet certified in accordance with the NOCSAE standard. The Hybrid III headform was instrumented with a nine accelerometer array to measure linear accelerations of the head and determine angular accelerations. Peak resultant linear head accelerations for the non-helmeted ATD were approximately 200–400 g for frontal impacts and approximately 220–480 g for lateral impacts. Peak resultant angular head accelerations for the non-helmeted condition were approximately 17,000–32,000 rad/s2 for frontal impacts and approximately 30,000–60,000 rad/s2 for lateral impacts. For the helmeted ATD, peak resultant linear accelerations of the head were approximately 70–300 g for frontal impacts and approximately 80–360 g for lateral impacts. Peak resultant angular head accelerations for the helmeted ATD were approximately 5,000–14,000 rad/s2 for frontal impacts and approximately 7,500–30,000 rad/s2 for lateral impacts. HIC values for the non-helmeted ATD were approximately 193–1,025 for frontal impacts and approximately 241–1,588 for lateral impacts. SI values for the non-helmeted ATD were approximately 235–1,267 for frontal impacts and approximately 285–1,844 for lateral impacts. HIC values for the helmeted ATD were approximately 16–415 for frontal impacts and approximately 23–585 for lateral impacts. SI values for the helmeted ATD were approximately 25–521 for frontal impacts and approximately 32–708 for lateral impacts. In comparison to the non-helmeted condition, the results demonstrate the effectiveness of a batting helmet in mitigating head accelerations for the frontal and lateral impact conditions tested.
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Cook, Harold A., Sam Akhavan, Patrick J. DeMeo, and Mark Carl Miller. "Finite Element Analysis of the Ulnar Tunnel in Ulnar Collateral Ligament Reconstruction." In ASME 2010 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2010. http://dx.doi.org/10.1115/sbc2010-19040.

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The ulnar collateral ligament (UCL) of the elbow originates on the medial epicondyle of the humerus and inserts on the sublime tubercle of the proximal ulna. This ligament is classically composed of three distinct structures: the anterior bundle, the posterior bundle, and the transverse bundle. Of these three, the anterior bundle has been shown to be the primary stabilizer to valgus load between 20° and 120° of flexion [1]. Injuries to the anterior bundle of the UCL are commonly seen in baseball pitchers, where the valgus load on the elbow during the throwing motion approaches the failure load of the ligament [2].
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Chen, Hsuan-Sheng, Hua-Tsung Chen, Wen-Jiin Tsai, Suh-Yin Lee, and Jen-Yu Yu. "Pitch-by-Pitch Extraction from Single View Baseball Video Sequences." In Multimedia and Expo, 2007 IEEE International Conference on. IEEE, 2007. http://dx.doi.org/10.1109/icme.2007.4284927.

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Wang, Hongsheng, Koco Eaton, and Nigel Zheng. "Shoulder Rotation Laxity is Related to Pitching Mechanics." In ASME 2011 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2011. http://dx.doi.org/10.1115/sbc2011-53307.

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According to the 2002 Major League Baseball Disability Analysis, almost 70% of players on the disabled list are pitchers and throwing arm related injuries account for 53% of all disabled list placements. To reach a high ball speed, pitchers cock, or excessively externally rotate their pitching arm to or near an extreme ROM of 180° [1]. The shoulder is then immediately internally rotated to an astonishing 7000°/s after the leading foot contact. The excessive external rotation ROM and astonishing internal rotation velocity are thought to contribute to injury [2]. Repeated exposure to the excessive ROM and large shoulder loads may cause excessive laxity to the anterior shoulder and/or damage the soft tissue [2]. This can lead to shoulder instability and excessive humeral head translation that may cause impingement [3]. Therefore, the mobility and stability of the thrower’s shoulder are extremely relevant to performance and injury prevention.
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Takahashi, Masaki, Mahito Fujii, and Nobuyuki Yagi. "Automatic Pitch Type Recognition from Baseball Broadcast Videos." In 2008 Tenth IEEE International Symposium on Multimedia (ISM) (Formerly MSE). IEEE, 2008. http://dx.doi.org/10.1109/ism.2008.47.

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