Search Results Heading

MBRLSearchResults

mbrl.module.common.modules.added.book.to.shelf
Title added to your shelf!
View what I already have on My Shelf.
Oops! Something went wrong.
Oops! Something went wrong.
While trying to add the title to your shelf something went wrong :( Kindly try again later!
Are you sure you want to remove the book from the shelf?
Oops! Something went wrong.
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
    Done
    Filters
    Reset
  • Discipline
      Discipline
      Clear All
      Discipline
  • Is Peer Reviewed
      Is Peer Reviewed
      Clear All
      Is Peer Reviewed
  • Reading Level
      Reading Level
      Clear All
      Reading Level
  • Content Type
      Content Type
      Clear All
      Content Type
  • Year
      Year
      Clear All
      From:
      -
      To:
  • More Filters
      More Filters
      Clear All
      More Filters
      Item Type
    • Is Full-Text Available
    • Subject
    • Publisher
    • Source
    • Donor
    • Language
    • Place of Publication
    • Contributors
    • Location
135 result(s) for "Baseball Statistical methods."
Sort by:
When Big Data Was Small
Richard D. Cramer has been doing baseball analytics for just about as long as anyone alive, even before the term \"sabermetrics\" existed. He started analyzing baseball statistics as a hobby in the mid-1960s, not long after graduating from Harvard and MIT. He was a research scientist for SmithKline and in his spare time used his work computer to test his theories about baseball statistics. One of his earliest discoveries was that clutch hitting-then one of the most sacred pieces of received wisdom in the game-didn't really exist. In When Big Data Was Small Cramer recounts his life and remarkable contributions to baseball knowledge. In 1971 Cramer learned about the Society for American Baseball Research (SABR) and began working with Pete Palmer, whose statistical work is credited with providing the foundation on which SABR is built. Cramer cofounded STATS Inc. and began working with the Houston Astros, Oakland A's, Yankees, and White Sox, with the help of his new Apple II computer. Yet for Cramer baseball was always a side interest, even if a very intense one for most of the last forty years. His main occupation, which involved other \"big data\" activities, was that of a chemist who pioneered the use of specialized analytics, often known as computer-aided drug discovery, to help guide the development of pharmaceutical drugs. After a decade-long hiatus, Cramer returned to baseball analytics in 2004 and has done important work with Retrosheet since then. When Big Data Was Small is the story of the earliest days of baseball analytics and computer-aided drug discovery.      
Correlation of pitching velocity with anthropometric measurements for adult male baseball pitchers in tryout settings
Several studies have investigated factors influencing baseball pitching velocity. However, some measurements require expensive equipment, and some tests need familiarity to perform well. In this study, we adopted field tests executed using affordable equipment in a tryout event for a professional baseball team in Taiwan, 2019. We use half day to test 64 players, and the result of measurement are used to develop a model for predicting pitching velocity of amateur adult pitchers (age: 23.9 ± 2.8 years; height: 180.3 ± 5.9 cm; weight: 81.4 ± 10.9 kg). The measurements and tests in tryout settings should be easy to implement, take short time, do not need high skill levels, and correlate to the pitching velocity. The outcome measures included maximum external shoulder rotation, maximum internal shoulder rotation, countermovement jump (CMJ) height, 20-kg loaded CMJ height, 30-m sprint time, height, age, and weight tests. Multiple regression indicated a moderate correlation between these tests and pitching velocity (adjusted R 2 = 0.230, p = 0.0003). Among the measures, the ratio of loaded CMJ to CMJ, ratio of first 10-m sprint time to 30-m sprint time, and height were significant contributors to pitching velocity. Overall, these measures explained 23% of the variance in the predicted pitching velocity. These field tests can be adopted in tryout events to predict a prospect’s potential and to identify underestimated players. Coaches can obtain an expectation of a pitcher’s performance by comparing his pitching velocity with the predicted value derived from the statistical model presented herein, and the room of growth by comparing his current strength to average strength growth after being drafted and trained with professional coaches.
Detecting Novel Associations in Large Data Sets
Identifying interesting relationships between pairs of variables in large data sets is increasingly important. Here, we present a measure of dependence for two-variable relationships: the maximal information coefficient (MIC). MIC captures a wide range of associations both functional and not, and for functional relationships provides a score that roughly equals the coefficient of determination (R²) of the data relative to the regression function. MIC belongs to a larger class of maximal information-based nonparametric exploration (MINE) statistics for identifying and classifying relationships. We apply MIC and MINE to data sets in global health, gene expression, major-league baseball, and the human gut microbiota and identify known and novel relationships.
Fastball Velocity and Elbow-Varus Torque in Professional Baseball Pitchers
High loads in the elbow during baseball pitching can lead to serious injuries, including injuries to the ulnar collateral ligament. These injuries have substantial implications for individual pitchers and their teams, especially at the professional level of competition. With a trend toward increased ball velocity in professional baseball, controversy still exists regarding the strength of the relationship between ball velocity and elbow-varus torque. To examine the relationship between fastball velocity and elbow-varus torque in professional pitchers using between- and within-subjects statistical analyses. Cross-sectional study. Motion-analysis laboratory. Using the previously collected biomechanical data of 452 professional baseball pitchers, we performed a retrospective analysis of the 64 pitchers (52 right-hand dominant, 12 left-hand dominant; age = 21.8 ± 2.0 years, height = 1.90 ± 0.05 m, mass = 94.6 ± 7.8 kg) with fastball velocity distributions that enabled between- and within-subjects statistical analyses. We measured ball velocity using a radar gun and 3-dimensional motion data using a 12-camera automated motion-capture system sampling at 240 Hz. We calculated elbow-varus torque using inverse-dynamics techniques and then analyzed the relationship between ball velocity and elbow torque using both a simple linear regression model and a mixed linear model with random intercepts. The between-subjects analyses displayed a weak positive association between ball velocity and elbow-varus torque ( = 0.076, = .03). The within-subjects analyses showed a considerably stronger positive association ( = 0.957, < .001). When comparing 2 professional baseball pitchers, higher velocity may not necessarily indicate higher elbow-varus torque due to the confounding effects of pitcher-specific differences (eg, detailed anthropometrics and pitching mechanics). However, within an individual pitcher, higher ball velocity was strongly associated with higher elbow-varus torque.
Group-Linear Empirical Bayes Estimates for a Heteroscedastic Normal Mean
The problem of estimating the mean of a normal vector with known but unequal variances introduces substantial difficulties that impair the adequacy of traditional empirical Bayes estimators. By taking a different approach that treats the known variances as part of the random observations, we restore symmetry and thus the effectiveness of such methods. We suggest a group-linear empirical Bayes estimator, which collects observations with similar variances and applies a spherically symmetric estimator to each group separately. The proposed estimator is motivated by a new oracle rule which is stronger than the best linear rule, and thus provides a more ambitious benchmark than that considered in the previous literature. Our estimator asymptotically achieves the new oracle risk (under appropriate conditions) and at the same time is minimax. The group-linear estimator is particularly advantageous in situations where the true means and observed variances are empirically dependent. To demonstrate the merits of the proposed methods in real applications, we analyze the baseball data used by Brown ( 2008 ), where the group-linear methods achieved the prediction error of the best nonparametric estimates that have been applied to the dataset, and significantly lower error than other parametric and semiparametric empirical Bayes estimators.
Exploring causal relationship between Major League Baseball games and crime: a synthetic control analysis
Using the Washington Nationals case, which moved from Montreal, Canada, to Washington, DC in 2005, as a natural experiment, I examine the impact of MLB games on crime in a host city. To address endogeneity concerns, this paper applies a synthetic control method with using 21 large cities which host an MLB team as a “donor pool” and employs a triple difference-in-difference approach to estimate the change in crime before and after the Nationals coming, between MLB season and off-season, and Washington, DC and the synthetic Washington. With using monthly crime data from the Uniform Crime Report, only assaults increased by 7–7.5% annually after the Nationals moved to DC; other crimes were unchanged. This result is supported by statistical significance and in-space placebo tests, and several alternative specifications in robustness check. These increases in assaults could be associated with additional costs, annually from $20 to $35 million. Little to no evidence of a causal relationship between MLB games and other types of crime.
Psychological well-being and quality of life in visually impaired baseball players: An Italian national survey
Italian baseball played by visually impaired and blind athletes is an adapted team sport which maintains the peculiar fast-moving features of this popular sport. It is also a mixed team game played together with sighted subjects. Here, we performed a national survey aimed at assessing the differences in psychological well-being (PWB) and quality of life (QoL) between visually impaired baseball players from Italian teams and non-players using a structured online questionnaire. Forty-three visually impaired baseball players and thirty-four visually impaired sedentary individuals completed a structured self-report survey including the validated 18-item Italian versions of the PWB (PWB-18) scale and the Short Form-12 (SF-12) questionnaire to assess the QoL. PWB-18 and SF-12 reference data from the Italian normally sighted population were also employed for comparison with the visually impaired baseball player group. Visually impaired baseball players reported better scores in all dimensions of the PWB-18 scale and significant higher scores in both physical and mental QoL evaluated by SF-12 than the non-player group. In addition, PWB-18 scale findings revealed significant differences between visually impaired baseball players and the reference normally sighted population consisting in lower scores for autonomy, environmental mastery, positive relations with others and purpose in life dimensions. Conversely, the mean scores for PWB-18 personal growth and self-acceptance dimensions were not significantly different between the two groups. The SF-12 questionnaire results demonstrated a significantly higher physical score in visually impaired players compared with the reference population. Instead, the SF-12 mental score of visually impaired athletes tended to be lower, though this difference was not statistically significant. Collectively, our findings suggest that the practice of Italian baseball may have a positive impact on PWB and QoL of visually impaired individuals.
A retrospective analysis of the efficacy of baseball suture method in single-port laparoscopic myomectomy
Objective: To assess the hemostatic effect of baseball suture after myomectomy under single-port laparoscopy. Methodology: Retrospective review of 91 patients admitted to Department of Gynecology, Jiaxing Maternity and Child Health Care Hospital from July 2021 to August 2023 who had myomas removed via single-port laparoscopy. We counted the suture method (traditional suture method vs baseball suture method) of each case divided into two groups (41 cases in control group; 50 cases in experimental group), and assessed the amount of intraoperative bleeding, postoperative hemoglobin decrease, and pelvic effusion. Propensity score matching (PSM) between groups was performed by the maximum diameter of the myoma, patient’s age, number of myomas, type of myoma, and location of myoma. Results: After PSM, a total of 38 pairs were matched. The mean amount of intraoperative bleeding, postoperative hemoglobin decrease, and pelvic fluid accumulation in the control group were significantly higher than those in the experimental group (115.79ml vs 94.34ml; 16.55g/l vs 12.79g/l; 146.74ml vs 119.13ml, P<0.05). There was no significant difference in operation time between the two groups (83.84min vs 87.79min, P>0.05). Conclusions: Our data suggested that using baseball suture method can significantly reduce the amount of intraoperative bleeding, postoperative hemoglobin decrease, and pelvic fluid accumulation in patients undergoing single-port laparoscopic myomectomy compared with traditional suture method. In addition, although using baseball suture method is more cumbersome, it does not significantly increase operation time.
Influence of Baseball Training Load on Clinical Reach Tests and Grip Strength in Collegiate Baseball Players
A baseball-specific training load may influence strength or glenohumeral range of motion, which are related to baseball injuries. Glenohumeral reach tests and grip strength are clinical assessments of shoulder range of motion and upper extremity strength, respectively. To examine changes in glenohumeral reach test performance and grip strength between dominant and nondominant limbs and high, moderate, and low baseball-specific training-load groups. Repeated-measures study. University laboratory and satellite clinic. Collegiate baseball athletes (n = 18, age = 20.1 ± 1.3 years, height = 185.0 ± 6.5 cm, mass = 90.9 ± 10.2 kg). Participants performed overhead reach tests (OHRTs), behind-the-back reach tests (BBRTs), and grip strength assessments using the dominant and nondominant limbs every 4 weeks for 16 weeks. Percentage change scores were calculated between testing times. After each training session, participants provided their duration of baseball activity, throw count, and body-specific and arm-specific ratings of perceived exertion. We classified them in the high, moderate, or low training-load group based on each training-load variable: body-specific acute:chronic workload ratio (ACWR), arm-specific ACWR, body-specific cumulative load, and arm-specific cumulative load. Mixed models were used to compare training-load groups and limbs. The arm-specific ACWR group demonstrated as main effect for OHRT (F = 7.70, P = .001), BBRT (F = 4.01, P = .029), and grip strength (F = 8.89, P < .001). For the OHRT, the moderate training-load group demonstrated a 10.8% greater increase than the high group (P = .004) and a 13.2% greater increase than the low group (P < .001). For the BBRT, the low training-load group had a 10.1% greater increase than the moderate group (P = .011). For grip strength, the low training-load group demonstrated a 12.1% greater increase than the high group (P = .006) and a 17.7% greater increase than the moderate group (P < .001). Arm-specific ACWR was related to changes in clinical assessments of range of motion and strength. Clinicians may use arm-specific ACWR to indicate when a baseball athlete's physical health is changing.