Relevant bibliographies by topics / Sports performance metrics

Academic literature on the topic 'Sports performance metrics'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Sports performance metrics"

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Nindl, Bradley C., Dianna P. Jaffin, Michael N. Dretsch, Samuel N. Cheuvront, Nancy J. Wesensten, Michael L. Kent, Neil E. Grunberg, et al. "Human Performance Optimization Metrics." Journal of Strength and Conditioning Research 29 (November 2015): S221—S245. http://dx.doi.org/10.1519/jsc.0000000000001114.

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Raysmith, Benjamin, Jenny Jacobsson, Michael Drew, and Toomas Timpka. "What Is Performance? A Scoping Review of Performance Outcomes as Study Endpoints in Athletics." Sports 7, no. 3 (March 16, 2019): 66. http://dx.doi.org/10.3390/sports7030066.

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Purpose: This review set out to summarise, define, and provide future direction towards the use of performance outcome measures as endpoints in research performed at international benchmark events in athletics. Methods: Scoping review methodology was applied through a search of the PubMed and Sports Discus databases and a systematic article selection procedure. Articles that met the inclusion criteria underwent triage for further quantitative and qualitative analysis. A concept chart was generated to describe the methods by which performance had been measured and introduce descriptive labels for theoretical and practical application. Results: None of 2972 articles primarily identified from the database search met the triage standards for quantitative data extraction. Eleven articles were included in a qualitative analysis. The analysis identified the common methods by which performance has been measured, reported and analysed. The resulting concept chart collates labels from the qualitative analysis (categories, themes, and constructs) with sports practice labels (performance metrics, framework, and analysis). Conclusions: The state of knowledge concerning methods to employ performance metrics as endpoints in studies performed at major competitions in athletics has been summarised. Constructing a methodology that combines the performance metric variables (continuous and ordinal) that are currently utilised as endpoints remains a challenge.
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Petersen, Alexander M., and Orion Penner. "Renormalizing individual performance metrics for cultural heritage management of sports records." Chaos, Solitons & Fractals 136 (July 2020): 109821. http://dx.doi.org/10.1016/j.chaos.2020.109821.

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Favorov, Oleg V., Eric Francisco, Jameson Holden, Olcay Kursun, Laila Zai, and Mark Tommerdahl. "Quantification of Mild Traumatic Brain Injury via Cortical Metrics: Analytical Methods." Military Medicine 184, Supplement_1 (March 1, 2019): 228–36. http://dx.doi.org/10.1093/milmed/usy411.

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Abstract Mild traumatic brain injuries are difficult to diagnose or assess with commonly used diagnostic methods. However, the functional state of cerebral cortical networks can be rapidly and effectively probed by measuring tactile-based sensory percepts (called cortical metrics), which are designed to exercise various components of cortical machinery. In this study, such cortical metrics were obtained from 52 college students before and after they experienced sports-related concussions by delivering vibrotactile stimuli to the index and middle fingertips. Performance on four of the sensory test protocols is described: reaction time, amplitude discrimination, temporal order judgment, and duration discrimination. The collected test performance data were analyzed using methods of uni- and multivariate statistics, receiver operated characteristic (ROC) curves, and discriminant analysis. While individual cortical metrics vary extensively in their ability to discriminate between control and concussed subjects, their combined discriminative performance greatly exceeds that of any individual metric, achieving cross-validated 93.0% sensitivity, 92.3% specificity, 93.0% positive predictive value, and 92.3% negative predictive value. The cortical metrics vector can be used to track an individual’s recovery from concussion. The study thus establishes that cortical metrics can be used effectively as a quantitative indicator of central nervous system health status.
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Melcher, Carolin, Andreas Korge, Michael Cunningham, Kevin T. Foley, and Roger Härtl. "Metrics Development for Minimal Invasive Unilateral Laminotomy for Bilateral Decompression of Lumbar Spinal Stenosis With and Without Spondylolisthesis by an International Expert Panel." Global Spine Journal 10, no. 2_suppl (April 2020): 168S—175S. http://dx.doi.org/10.1177/2192568219893675.

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Study Design: Prospective study. Objectives: To develop, operationally define, and seek consensus from procedure experts on the metrics that best characterize a reference approach to the performance of a minimally invasive unilateral laminotomy for bilateral decompression (ULBD) for lumbar spinal stenosis. Methods: A Metrics Group consisting of 3 experienced spine surgeons (2 neurosurgeons, 1 orthopedic surgeon), each with over 25 years of clinical practice, and an educational expert formed the Metrics Group that characterized a lumbar decompression surgery for spinal stenosis as a “reference” procedure. In a modified Delphi panel, 26 spine surgeons from 14 countries critiqued these metrics and their operational definitions before reaching consensus. Results: Performance metrics consisting of 6 phases with 42 steps, 21 errors, and 17 sentinel errors were identified that characterize the procedure. During the peer review, these were evaluated, modified, and agreed. Conclusions: Surgical procedures can be broken down into elemental tasks necessary for the safe and effective completion of a reference approach to a specified surgical procedure. Spinal experts from 16 countries reached consensus on performance metrics for the procedure. This metric-based characterization can be used in a training curriculum and also for assessment of training and performance in clinical practice.
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Green, Gary, Keshia M. Pollack Porter, Anton Kvit, Stan Conte, John D’Angelo, Alex Valadka, and Frank C. Curriero. "Examining Batting Performance After a Sports-Related Concussion Among Major League Baseball Position Players." American Journal of Sports Medicine 49, no. 3 (January 29, 2021): 790–97. http://dx.doi.org/10.1177/0363546520987232.

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Background: An ongoing challenge in sports-related concussion (SRC) is determining full recovery. This study examines performance metrics in baseball after an SRC and provides a template for assessment of return-to-performance parameters. Purpose: To determine whether batting performance returns to baseline after an SRC. Study Design: Descriptive epidemiological study. Methods: Participants were all Major League Baseball (MLB) position players with confirmed SRCs that occurred during the 2011-2015 seasons. A retrospective review and assessment of performance metrics before and after injury were conducted as defined relative to the number of plate appearances (PAs) to yield reliable performance statistics. Seven batting metrics were considered as outcomes in longitudinal regressions: batting average, on-base percentage, slugging percentage, on-base plus slugging, bases on balls, strikeouts, and home runs. Metrics were calculated for each player 60, 30, and 14 days before their SRCs, as well as for the 14, 30, and 60 days after returning to play. Other variables controlled for included defensive position, player age at the time of SRC, number of days missed, mechanism of injury, whether the player completed a rehabilitation stint, and year in which the mild traumatic brain injury (MTBI) occurred (2011-2015). Results: A total of 77 MTBI case events occurred in MLB position players over 5 seasons. These injuries resulted in a mean 11.4 days lost to injury. For all performance metrics using 60 or 30 days before MTBI as baseline, no statistically significant differences were found in batting performance. In total, 63 events met PA criteria before injury. Varying the PA cutoff thresholds to be more inclusive or more restrictive yielded similar regression results. For the 48 events that met PA criteria before and after injury, most performance metrics showed no significant performance change after MTBI and, in some events, a slight though mostly nonsignificant performance improvement after MTBI. Conclusions: MLB position players who are medically cleared to return to play after an SRC perform at the same offensive performance levels as their preinjury statistics when an adequate number of PAs is used to compare performance before and after injury.
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Rahutomo, Faisal, Trisna Ari Roshinta, Erfan Rohadi, Indrazno Siradjuddin, Rudy Ariyanto, Awan Setiawan, and Supriatna Adhisuwignjo. "Open Problems in Indonesian Automatic Essay Scoring System." International Journal of Engineering & Technology 7, no. 4.44 (December 1, 2018): 156. http://dx.doi.org/10.14419/ijet.v7i4.44.26974.

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This paper presents open problems in Indonesian Scoring System. The previous study exposes the comparison of several similarity metrics on automated essay scoring in Indonesian. The metrics are Cosine Similarity, Euclidean Distance, and Jaccard. The data being used in the research are about 2,000 texts. This data are obtained from 50 students who answered 40 questions on politics, sports, lifestyle, and technology. The study also evaluates the stemming approach for the system performance. The difference between all methods between using stemming or not is around 4-9%. The results show Jaccard is the best metric both for the system with stemming or not. Jaccard method with stemming has the percentage error lowest than the others. The politic category has the highest average similarity score than lifestyle, sport, and technology. The percentage error of Jaccard with stemming is 52.31%, Cosine Similarity is 59.49%, and Euclidean Distance is 332.90%. In addition, Jaccard without stemming is also the best than the others. The percentage error without stemming of Jaccard is 56.05%, Cosine Similarity is 57.99%, and Euclidean Distance is 339.41%. However, this percentage error is high enough to be used for a functional essay grading system. The percentage errors are relatively high, more than 50%. Therefore this paper explores several ideas of open problems in this issue. The openly available dataset can be used to develop better approaches than the standard similarity metrics. The approaches expose are ranging from feature extraction, similarity metrics, learning algorithm, environment implementation, and performance evaluation.
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McKay, Alannah K. A., Trent Stellingwerff, Ella S. Smith, David T. Martin, Iñigo Mujika, Vicky L. Goosey-Tolfrey, Jeremy Sheppard, and Louise M. Burke. "Defining Training and Performance Caliber: A Participant Classification Framework." International Journal of Sports Physiology and Performance 17, no. 2 (February 1, 2022): 317–31. http://dx.doi.org/10.1123/ijspp.2021-0451.

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Throughout the sport-science and sports-medicine literature, the term “elite” subjects might be one of the most overused and ill-defined terms. Currently, there is no common perspective or terminology to characterize the caliber and training status of an individual or cohort. This paper presents a 6-tiered Participant Classification Framework whereby all individuals across a spectrum of exercise backgrounds and athletic abilities can be classified. The Participant Classification Framework uses training volume and performance metrics to classify a participant to one of the following: Tier 0: Sedentary; Tier 1: Recreationally Active; Tier 2: Trained/Developmental; Tier 3: Highly Trained/National Level; Tier 4: Elite/International Level; or Tier 5: World Class. We suggest the Participant Classification Framework can be used to classify participants both prospectively (as part of study participant recruitment) and retrospectively (during systematic reviews and/or meta-analyses). Discussion around how the Participant Classification Framework can be tailored toward different sports, athletes, and/or events has occurred, and sport-specific examples provided. Additional nuances such as depth of sport participation, nationality differences, and gender parity within a sport are all discussed. Finally, chronological age with reference to the junior and masters athlete, as well as the Paralympic athlete, and their inclusion within the Participant Classification Framework has also been considered. It is our intention that this framework be widely implemented to systematically classify participants in research featuring exercise, sport, performance, health, and/or fitness outcomes going forward, providing the much-needed uniformity to classification practices.
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Oved, Nadav, Amir Feder, and Roi Reichart. "Predicting In-Game Actions from Interviews of NBA Players." Computational Linguistics 46, no. 3 (November 2020): 667–712. http://dx.doi.org/10.1162/coli_a_00383.

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Sports competitions are widely researched in computer and social science, with the goal of understanding how players act under uncertainty. Although there is an abundance of computational work on player metrics prediction based on past performance, very few attempts to incorporate out-of-game signals have been made. Specifically, it was previously unclear whether linguistic signals gathered from players’ interviews can add information that does not appear in performance metrics. To bridge that gap, we define text classification tasks of predicting deviations from mean in NBA players’ in-game actions, which are associated with strategic choices, player behavior, and risk, using their choice of language prior to the game. We collected a data set of transcripts from key NBA players’ pre-game interviews and their in-game performance metrics, totalling 5,226 interview-metric pairs. We design neural models for players’ action prediction based on increasingly more complex aspects of the language signals in their open-ended interviews. Our models can make their predictions based on the textual signal alone, or on a combination of that signal with signals from past-performance metrics. Our text-based models outperform strong baselines trained on performance metrics only, demonstrating the importance of language usage for action prediction. Moreover, the models that utilize both textual input and past-performance metrics produced the best results. Finally, as neural networks are notoriously difficult to interpret, we propose a method for gaining further insight into what our models have learned. Particularly, we present a latent Dirichlet allocation–based analysis, where we interpret model predictions in terms of correlated topics. We find that our best performing textual model is most associated with topics that are intuitively related to each prediction task and that better models yield higher correlation with more informative topics. 1
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McCullough, Brian P., Jamee Pelcher, and Sylvia Trendafilova. "An Exploratory Analysis of the Environmental Sustainability Performance Signaling Communications among North American Sport Organizations." Sustainability 12, no. 5 (March 4, 2020): 1950. http://dx.doi.org/10.3390/su12051950.

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Sport organizations across North America promote and claim deep commitments to environmental issues through sustainability performance signaling. These signals are conveyed through external associations or memberships (e.g., Green Sports Alliance) or internally (e.g., environmental reports and communications). However, researchers have not explored this communication strategy as it relates to environmental initiatives in sport nor compared environmental communications of sport organizations from the major professional sport leagues in North America. We analyzed the websites of 147 North American sport organizations and their associated venue websites for environmental performance signaling communications. We found that only one sport organization featured an environmental report on its website, and 42 sport organizations highlighted environmental initiatives through dedicated webpages on the respective team or venue’s website. Predominately, these communications focused on fan engagement initiatives (i.e., awareness, participation) but lacked goal setting, measurement metrics, or performance summaries. We discuss these themes, the implications, and recommendations for how sustainability performance signaling can be better leveraged in the North American sport sector.
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Dissertations / Theses on the topic "Sports performance metrics"

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Simões, Paulo Jorge dos Santos Nunes Valente. "Imagética em natação-contributo para a construção de um plano de prova mental para os 100 metros crol." Master's thesis, Instituições portuguesas -- UTL-Universidade Técnica de Lisboa -- -Faculdade de Motricidade Humana, 2001. http://dited.bn.pt:80/29354.

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Tavares, António Jorge Oliveira. "Relação entre os resultados obtidos em testes específicos para a avaliação da força muscular e a prestação numa corrida de cem metros planos em atletismo." Master's thesis, Instituições portuguesas -- UP-Universidade do Porto -- -Faculdade de Ciências do Desporto e de Educação Física, 2000. http://dited.bn.pt:80/29224.

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Ellens, Susanne. "Can we catch the crooks: examining performance metrics of match-fixing association football players." Thesis, 2019. https://vuir.vu.edu.au/40593/.

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Match-fixing is the process where the result of a sporting contest or game situation is deliberately manipulated for the personal material gain of one or more parties involved in that activity. Match-fixing is a serious problem in football affecting the integrity of the game. While indicators such as betting patterns have been used to identify match-fixing cases, there are still many that go undetected and even those that are exposed are difficult to prosecute due to a lack of hard evidence. Electronic performance and tracking systems can potentially assist in both identification and evidence- development actions by detecting unusual changes in a players’ movement behaviour on the pitch. The purpose of this research was to examine whether performance metrics derived from players' positional x and y coordinates can detect match-fixing behaviour in football. Six different performance metrics have been examined and were used to create player performance profiles. The player performance profiles have been compared with standardized mean differences and were analysed with Approximate entropy (ApEn) analysis and different recursive partitioning techniques. Results show that match-fixing behaviour influenced defensive fixing players’ performance metrics during a football game. Positional performance metrics were most associated with fixing behaviour and showed substantial differences compared to normal behaviour. Fixing players moved forward on the pitch and kept more distance towards the position-specific centroid. The altered movement pattern resulted in more spread of play in the lateral direction suggesting fixing players are stretching the defence to create space. Further studies should investigate the use of a wider range of fixing scenarios of numerous games to further develop the match-fixing detection framework. The findings of this thesis can be beneficial, not only for integrity purposes of the football related society, but also for a wider spectrum of team sports using electronic performance and tracking systems to measure player performance. These findings provide insights to player performance metrics underpinning match-fixing behaviour for defence players which can possibly assist in providing supporting evidence to prosecute match-fixing players. Further, it provides scientific knowledge to create a match-fixing detection approach which covers both betting and non-betting related match-fixing.
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Alexander, Jeremy P. "A framework for quantifying tactical team behaviour in Australian Rules Football." Thesis, 2020. https://vuir.vu.edu.au/40991/.

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The inception of tracking technologies has allowed for increased access to the positioning data of team sport athletes. This information assists in understanding collective team behaviour by measuring the continuous movement patterns of players. Assessing the efficacy of collective team behaviour research requires comprehension of the contextual factors that may influence movement behaviour, such as the match phase and field location of the ball. Limited studies that have analysed collective team behaviour have accounted for such contextual variables. Research on collective team behaviour in invasion sports has typically focused on football and basketball, while investigations in Australian football (AF) remain largely absent. Furthermore, collective team behaviour investigations to date have generally inferred performance through the positioning of players without directly determining the continuous influence on match play. Therefore, this thesis presents new methodologies for measuring collective team behaviour in AF. This information was used to understand the extent to which collective team behaviour influenced match play in a continuous manner. The findings provide a framework to quantify tactical team behaviour in Australian Rules football (AFL). Global positioning systems (GPS) spatiotemporal datasets were obtained from match simulation sessions and elite-level AFL matches. This information was aligned with match event data to provide contextual information, such as match phase and ball location. Initial chapters investigated the collective behaviour of AF teams using a macroscopic approach during match simulation and a competitive match. This was undertaken using a range of spatiotemporal metrics that summarise how certain players are positioned across a field of play. These chapters identified teams that were able to obtain increased possession of the ball covered greater spatial regions. Players also repositioned deeper towards their own goal when the ball was in their defensive half and relocated higher up the field when the ball was in their forward half. Subsequent chapters used a microscopic approach to model the position of every player to understand the spatial control of each team across a playing surface. The central findings from these chapters were that the total number of players increased based on where the ball was positioned and both teams obtained greater spatial control compared to the opposition when the ball was in their defensive half. Teams were also able to arrest spatial control when forcing a turnover in possession. The general findings from this thesis are spatiotemporal metrics can be used to infer tactical behaviour. A method that continuously represents how players occupy sub-areas of play may provide coaches and sport science practitioners with a more precise account of how tactical team behaviour influences ensuing match play. Finally, quantifying the resistive exchange in spatial control between teams and detecting the value placed on controlling specific regions may contribute to providing a more representative understanding of tactical team behaviour.
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Book chapters on the topic "Sports performance metrics"

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Araújo, Duarte, Micael Couceiro, Ludovic Seifert, Hugo Sarmento, and Keith Davids. "Computational Metrics to Inspect the Athletic Performance." In Artificial Intelligence in Sport Performance Analysis, 82–112. New York : Routledge, 2020.: Routledge, 2021. http://dx.doi.org/10.4324/9781003163589-4.

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E. Teixeira, José, Pedro Forte, Ricardo Ferraz, Luís Branquinho, António J. Silva, Tiago M. Barbosa, and António M. Monteiro. "Methodological Procedures for Non-Linear Analyses of Physiological and Behavioural Data in Football." In Exercise Physiology [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.102577.

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Complex and dynamic systems are characterised by emergent behaviour, self-similarity, self-organisation and a chaotic component. In team sports as football, complexity and non-linear dynamics includes understanding the mechanisms underlying human movement and collective behaviour. Linear systems approaches in this kind of sports may limit performance understanding due to the fact that small changes in the inputs may not represent proportional and quantifiable changes in the output. Thus, non-linear approaches have been applied to assess training and match outcomes in football. The increasing access to wearable and tracking technology provides large datasets, enabling the analyses of time-series related to different performance indicators such as physiological and positional parameters. However, it is important to frame the theoretical concepts, mathematical models and procedures to determine metrics with physiological and behavioural significance. Additionally, physiological and behavioural data should be considered to determine the complexity and non-linearity of the system in football. Thus, the current chapter summarises the main methodological procedures to extract positional data using non-linear analyses such as entropy scales, relative phase transforms, non-linear indexes, cross correlation, fractals and clustering methods.
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"Using spatial metrics to characterize behaviour in small-sided games." In Performance Analysis of Sport IX, 284–92. Routledge, 2013. http://dx.doi.org/10.4324/9780203080443-51.

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Conference papers on the topic "Sports performance metrics"

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Sarwar, Umair, Kamran Cheema, and Tahira Reid. "ContaBat: Designing and Prototyping an Attachable Sports Analytics Device That Provides Ball-Bat Impact Location for Performance Enhancement." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98517.

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Abstract This paper introduces ContaBat, an attachable device for a cricket bat that provides important performance metrics like ball-bat impact location, rotation due to impact, and impact force which could be used by players, coaches and fans to gain insights about their performance. Of the metrics mentioned, obtaining the impact location is the most novel feature and is the focus of this paper. Piezo-electric sensors placed at the back of the bat are used to record pressure measurements due to impact and utilize time difference of arrival techniques (TDOA) to pinpoint the impact location. For further product realization and development, it was essential to create a prototype. The prototype was instrumental in providing testing conditions that could simulate a real-world environment, identifying the limitations of the data acquisition methods used, evaluating the usability of the product, and helping future researchers envision the final form of the product and the impact it could create before commercializing the product. The results of the algorithms showed that the accuracy of the methods used resulted in the impact location being within 0.002 m of the hit spot, with the percentage error being higher towards the edges of the bat than the middle. This paper will discuss in detail the data acquisition and data analysis methods used to measure impact location on a cricket bat, the design considerations while creating the prototype, and the insights gained from prototyping.
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Seymour, Mark J., and Magnus K. Herrlin. "Data Center Optimization Using Performance Metrics." In ASME 2015 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems collocated with the ASME 2015 13th International Conference on Nanochannels, Microchannels, and Minichannels. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/ipack2015-48400.

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Data centers are rapidly growing in size and number and consume an increasing and also significant proportion of energy production. Yet, their mission critical nature means they are constructed and operated at almost any cost. The data center industry is becoming more aware of the need to manage energy alongside managing capacity and availability. A vital element — and one that cannot be ignored — is how well cooling is delivered to IT equipment. Monitoring allows you to understand how well you are currently operating and whether you are within acceptable bounds. Meanwhile, simulation of the airflow and heat transfer allows you to predict future performance and understand current and future cooling issues. The challenge with both approaches is that they provide large volumes of data and interpretation can become a challenging task. Consider two scenarios: i. One configuration results in a lot of ‘hot spots’ in the data center, resulting in equipment permanently operating in the ASHRAE Allowable range for intake air temperature. ii. A second configuration has one ‘hot spot’ where equipment is operating above the ASHRAE Allowable range, but the remainder is within the ASHRAE Recommended range. Which is better? One solution is to use metrics to help understand the performance. However, existing metrics are not always well known and understood. The only metric that is currently in common use is Power Usage Effectiveness (PUE). While PUE is useful as a measure of data center cooling efficiency, it does not address the cool air delivery effectiveness within the IT space. However, high-level cooling delivery metrics such as Rack Cooling Index (RCI), Return Temperature Index (RTI), Supply Heat Index (SHI), and Return Heat Index (RHI) have been recognized for producing key information but are not as widely used as they could be. Other metrics have been developed that give more detailed understanding of delivery performance. Capture Index, or more specifically Cold Aisle Capture Index (CACI) and Hot Aisle Capture Index (HACI) provide a measure of whether cooling systems targeting specific equipment work effectively. Simulation also allows diagnostic performance ‘measurement’ with detailed indices such as Rack and Room Recirculation. Since data center airflow is complex, this paper uses case studies to show how using metrics provides a rapid insight into both performance and what might need to be addressed to improve and optimize performance.
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Rabia, Sédick, Herman M. K. Wong, Zhenfeng Zhuang, and Simon Thibault. "Versatile Experimental Setup for Quantifying Key Metrics of 3D Light Field Displays." In 3D Image Acquisition and Display: Technology, Perception and Applications. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/3d.2022.3f2a.3.

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We developed a versatile experimental setup able to characterize the optical performance of different 3D display designs based on far-field (spot size, lateral color) and near-field (contrast, spatial resolution, MTF) measurements.
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Liu, Guiliang, and Oliver Schulte. "Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/478.

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A variety of machine learning models have been proposed to assess the performance of players in professional sports. However, they have only a limited ability to model how player performance depends on the game context. This paper proposes a new approach to capturing game context: we apply Deep Reinforcement Learning (DRL) to learn an action-value Q function from 3M play-by-play events in the National Hockey League (NHL). The neural network representation integrates both continuous context signals and game history, using a possession-based LSTM. The learned Q-function is used to value players' actions under different game contexts. To assess a player's overall performance, we introduce a novel Game Impact Metric (GIM) that aggregates the values of the player's actions. Empirical Evaluation shows GIM is consistent throughout a play season, and correlates highly with standard success measures and future salary.
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Kodali, Satish, Liangshan Chen, Yuting Wei, Tanya Schaeffer, and Chong Khiam Oh. "Application of Novel Low Current OBIRCH Amplifier and Nanoprobing to Identify Subtle Leakages in Advanced Node Technologies." In ISTFA 2018. ASM International, 2018. http://dx.doi.org/10.31399/asm.cp.istfa2018p0303.

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Abstract Optical beam induced resistance change (OBIRCH) is a very well-adapted technique for static fault isolation in the semiconductor industry. Novel low current OBIRCH amplifier is used to facilitate safe test condition requirements for advanced nodes. This paper shows the differences between the earlier and novel generation OBIRCH amplifiers. Ring oscillator high standby leakage samples are analyzed using the novel generation amplifier. High signal to noise ratio at applied low bias and current levels on device under test are shown on various samples. Further, a metric to demonstrate the SNR to device performance is also discussed. OBIRCH analysis is performed on all the three samples for nanoprobing of, and physical characterization on, the leakage. The resulting spots were calibrated and classified. It is noted that the calibration metric can be successfully used for the first time to estimate the relative threshold voltage of individual transistors in advanced process nodes.
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Rue, Chad. "Methodologies for Quantifying FIB “Milling Acuity”." In ISTFA 2009. ASM International, 2009. http://dx.doi.org/10.31399/asm.cp.istfa2009p0097.

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Abstract FIB column performance can be difficult to evaluate, and the traditional metrics of imaging resolution and minimum spot size give little indication of how a FIB system will perform its intended daily tasks. A series of supplemental FIB performance tests is proposed to quantify “milling acuity” under real-world conditions. A quantitative measuring scheme for evaluating the quality of High Aspect Ratio (HAR) vias is proposed, and an example is shown in which the HAR measuring scheme can be used for process development.
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Salahshoor, Shadi. "Data-Driven Characterization of Shale Reservoirs Towards Facilitation of Production Performance Evaluation." In SPE Western Regional Meeting. SPE, 2021. http://dx.doi.org/10.2118/200835-ms.

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Abstract Leveraging publicly available data is a crucial stepfor decision making around investing in the development of any new unconventional asset.Published reports of production performance along with accurate petrophysical and geological characterization of the areashelp operators to evaluate the economics and risk profiles of the new opportunities. A data-driven workflow can facilitate this process and make it less biased by enabling the agnostic analysis of the data as the first step. In this work, several machine learning algorithms are briefly explained and compared in terms of their application in the development of a production evaluation tool for a targetreservoir. Random forest, selected after evaluating several models, is deployed as a predictive model thatincorporates geological characterization and petrophysical data along with production metricsinto the production performance assessment workflow. Considering the influence of the completion design parameters on the well production performance, this workflow also facilitates evaluation of several completion strategies toimprove decision making around the best-performing completion size. Data used in this study include petrophysical parameters collected from publicly available core data, completion and production metrics, and the geological characteristics of theNiobrara formation in the Powder River Basin. Historical periodic production data are used as indicators of the productivity in a certain area in the data-driven model. This model, after training and evaluation, is deployed to predict the productivity of non-producing regions within the area of interest to help with selecting the most prolific sections for drilling the future wells. Tornado plots are provided to demonstrate the key performance driversin each focused area. A supervised fuzzy clustering model is also utilized to automate the rock quality analyses for identifying the "sweet spots" in a reservoir. The output of this model is a sweet-spot map that is generated through evaluating multiple reservoir rock properties spatially. This map assists with combining all different reservoir rock properties into a single exhibition that indicates the average "reservoir quality"of the formation in different areas. Niobrara shale is used as a case study in this work to demonstrate how the proposed workflow is applied on a selected reservoir formation whit enough historical production data available.
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Tolman, Sean S., Amanda Beatty, Anton E. Bowden, and Larry L. Howell. "Parameter Characterization for Elastic Energy Absorption of an Embedded Corrugated Wave Padding Concept." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59342.

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The parameters of an innovative padding concept were investigated using Finite Element Analyses (FEA) and physical testing. The concept relies on a compliant corrugation embedded in an elastic foam to provide stiffness for force distribution and elastic deformation for energy absorption. The shape of the corrugation cross section was explored as well as the wavelength and amplitude by employing a full factorial design of experiments. FEA results were used to choose designs for prototyping and physical testing. The results of the physical tests were consistent with the FEA predictions although the FEA tended to underestimate the peak pressure compared to the physical tests. A performance metric is proposed to compare different padding configurations. The concept shows promise for sports padding applications. It may allow for designs which are smaller, more lightweight, and move better with an athlete than current technologies yet still provide the necessary protective functions.
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Maißer, P. "Differential-Geometric Methods in Multibody Dynamics and Control." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-84860.

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This paper presents a differential-geometric approach to the multibody system dynamics regarded as a point dynamics in a n-dimensional configuration space Rn. This configuration space becomes a Riemannian space Vn the metric of which is defined by the kinetic energy of the multibody system (MBS). Hence, all concepts and statements of the Riemannian geometry can be used to study the dynamics of MBS. One of the key points is to set up the non-linear Lagrangian motion equations of tree-like MBS as well as of constrained mechanical systems, the perturbed equations of motion, and the motion equations of hybrid MBS in a derivative-free manner. Based on this approach transformation properties can be investigated for application in real-time simulation, control theory, Hamilton mechanics, the construction of first integrals, stability etc. Finally, a general Lyapunov-stable force control law for underactuated systems is given that demonstrates the power of the approach in high-performance sports applications.
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Kashani, Reza, and Joseph E. Strelow. "Fuzzy Logic Semi-Active Control of a Suspension for Off-Road Vehicles." In ASME 1997 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/imece1997-0463.

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Abstract A fuzzy-logic approach to semi-active vehicle suspension design is developed, with the goal of improving the speed of the vehicle over very rough, off-road, terrain. The ride metric used for quantifying improvements is the absorbed power of the sprung mass of the vehicle. Particular attention is made to the proper modeling of the suspension using both the full kinematic constraints and the more convenient two degree of freedom model of the quarter vehicle suspension. Nonlinearities of the suspension, including tire stiffness and bumpstops are included at all stages to demonstrate the controller performance advantages. The semi-active control law is developed on the less complex model, and the results of tuning in the fully constrained environment are compared. The results of this work have broad appeal, from the ease of development of the fuzzy-logic based algorithms, to the cost effectiveness of the semi-active hardware implementation. Improvements in the performance of the suspension system are desirable to the increasingly popular sport utility and light truck markets, as well as to military and emergency vehicle designs.
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Reports on the topic "Sports performance metrics"

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Ferraz, António, Pedro Duarte-Mendes, Hugo Sarmento, João Valente-dos-Santos, and Bruno Travassos. A Review of the use of the Electronic Tracking Systems on the Performance of Elite Athletes in Team Sports – Trends and Future Directions. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2022. http://dx.doi.org/10.37766/inplasy2022.11.0080.

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Review question / Objective: To understand the applicability of tracking systems in team sports on the last decade by emerging an understanding of how the use of different variables and research goals may be profitable to develop a comprehensive framework that might help to shed a light into team sports performance and athlete´s well-being. Rationale: To implement a training monitoring system, there is a need to understand how the different metrics available in training and competition may be manipulated to enhance the understanding of the context of performance in team sports. Additionally, how the information from tracking technology devices have been applied and what are the main issues that have being studied, in order to improve further research and practice.
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Sousa, Honorato, Filipe Manuel Clemente, Élvio Rúbio Gouveia, Adam Field, and Hugo Sarmento. Effects of changing the head coach on soccer team’s performance: A systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, June 2022. http://dx.doi.org/10.37766/inplasy2022.6.0060.

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Review question / Objective: The aim of this systematic review is to analyze the effects of changing the soccer head coach on the overall team’s performance, locomotor demands of players, technical/tactical responses of players, and psychological responses of players. Eligibility criteria: P: Among professional soccer players what is the effect of head-coach replacement; E: Exposure to the change of the head-coach; C: Last weeks of the fired head-coach compared with the first weeks of the new head-coach; O: locomotor performance, sports results, mental health metrics. Inclusion criteria will be: (1) articles written in English; (2) carried out in professional football teams. Studies will be excluded if: (1) written in another language other than the one selected; (2) in the case of theses, books and non-scientific articles.
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Mathew, Jijo K., Deborah Horton, and Darcy M. Bullock. Utilization of Dedicated Electric Vehicle Plug-In Charging Stations in a College Campus Environment. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317436.

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As electric mobility is expanding at a rapid pace, the standardized availability of gas stations compared to a scarcity of charging stations continues to be the greatest challenge for electric vehicles. With cities, university campuses and businesses promoting electric vehicle infrastructure and incentives, it is necessary to develop key performance metrics and visualizations that can track the utilization of the charging infrastructure. This study performs a manual data collection at dedicated plug-in charging stations across Purdue University to assess their utilization. Approximately 2,800 observations were conducted over 50 days across seven level 2 plug-in charging stations. Results showed that for large portion of the observations, vehicles were parked at the spots (40%) but not plugged in. Vehicles plugged in to charging stations accounted for 34% of observations. Charging station spots were vacant for 25% of observations indicating that current infrastructure meets the demand. There were 74 unique vehicles that used the spots, of which 27% were plugged in more than 10 times. Illegally parked vehicles accounted for less than 1% with only 4 repeat offenders who used these spots more than once. As electric deployment continues to increase, performance metrics will be an integral tool for agencies and decision makers to help with the maintenance and expansion of electric vehicle infrastructure.
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