Academic literature on the topic 'Player selection'
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Journal articles on the topic "Player selection"
Hatem, Belhouchet, and Khatrouch Ikram. "A Methodology for Selection Starting Line-Up of Football Players in Qatar World Cup 2022." European Journal of Sport Sciences 2, no. 2 (April 14, 2023): 46–51. http://dx.doi.org/10.24018/ejsport.2023.2.2.56.
Full textOhtsuki, Hisashi. "Evolutionary dynamics of n -player games played by relatives." Philosophical Transactions of the Royal Society B: Biological Sciences 369, no. 1642 (May 19, 2014): 20130359. http://dx.doi.org/10.1098/rstb.2013.0359.
Full textCarrillo, Juan D., and Thomas R. Palfrey. "The Compromise Game: Two-Sided Adverse Selection in the Laboratory." American Economic Journal: Microeconomics 1, no. 1 (January 1, 2009): 151–81. http://dx.doi.org/10.1257/mic.1.1.151.
Full textSilva, João Vítor Rocha da, and Paulo Canas Rodrigues. "All-NBA Teams’ Selection Based on Unsupervised Learning." Stats 5, no. 1 (February 9, 2022): 154–71. http://dx.doi.org/10.3390/stats5010011.
Full textPratama, Fabio Fahri, and Youllia Indrawaty Nurhasanah. "PENGGUNAAN METODE PROFILE MATCHING DAN NAÏVE BAYES UNTUK MENENTUKAN STARTING ELEVEN PADA SEPAK BOLA." Jurnal Tekno Insentif 14, no. 2 (August 26, 2020): 59–68. http://dx.doi.org/10.36787/jti.v14i2.268.
Full textLindholm, Oliver, Erik Niklasson, John Lind, Daniele A. Cardinale, and Tommy R. Lundberg. "A pilot study on bio-banding in male youth ice hockey: Players’ perceptions and coaches’ selection preferences." PLOS ONE 19, no. 8 (August 12, 2024): e0308676. http://dx.doi.org/10.1371/journal.pone.0308676.
Full textWardana, Ari Kusuma, and Andri Arif Kustiawan. "Optimization of U-23 futsal player selection through a simple additive weighting approach." Fizjoterapia Polska 24, no. 4 (October 31, 2024): 407–11. http://dx.doi.org/10.56984/8zg01a8d6e8.
Full textYu, Kristen K., Matthew Guzdial, and Nathan R. Sturtevant. "Evaluating the Effects of AI Directors for Quest Selection." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 20, no. 1 (November 15, 2024): 245–52. http://dx.doi.org/10.1609/aiide.v20i1.31885.
Full textTowlson, Christopher, Ed Cope, John L. Perry, David Court, and Nick Levett. "Practitioners’ multi-disciplinary perspectives of soccer talent according to phase of development and playing position." International Journal of Sports Science & Coaching 14, no. 4 (May 2019): 528–40. http://dx.doi.org/10.1177/1747954119845061.
Full textMegha Chakole. "Optimal Strategy Formulation for Tic-Tac-Toe Using Minimax Algorithm for Interactive Gaming." Communications on Applied Nonlinear Analysis 31, no. 2s (June 1, 2024): 485–95. http://dx.doi.org/10.52783/cana.v31.662.
Full textDissertations / Theses on the topic "Player selection"
Velentza, Elisavet. "A retrospective analysis of talent selection and progression within England's Rugby Football Union Elite Player Performance Pathway." Thesis, University of Chester, 2017. http://hdl.handle.net/10034/620558.
Full textBuckley, David. "Skill capture in first-person shooters." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/skill-capture-in-firstperson-shooters(a5a4858b-2b48-44f1-a59b-f7e1928ea7df).html.
Full textRichter, Roman. "Inovativní přehrávač hudby pro chytré telefony a PC." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445556.
Full textBen, Jeddou Roukaya. "Football Selection Optimization through the Integration of Management Theories, AI and Multi-criteria Decision Making." Electronic Thesis or Diss., Bourgogne Franche-Comté, 2024. http://www.theses.fr/2024UBFCG009.
Full textThe research outlined in this thesis falls within the context of professional football club management, where establishing a balance between human and financial aspects is essential for long-term viability of sports organizations. In football management, the traditional methods of player selection have historically guided decision-making processes within clubs. This strategic decision-making process, which is often subjective and uncertain, can have a significant impact on the club's financial, economic and sporting situation.As football is increasingly becoming a data-driven sport, there is a growing recognition that traditional approaches need to be complemented by scientific methods based on artificial intelligenceomenclature{AI}{Artificial Intelligence} and multi-criteria decision makingomenclature{MCDM}{Multi-Criteria Decision Making} approaches to optimize player selection and improve both sporting and financial performance. It is becoming increasingly important to find an optimal balance between sporting success and financial performance to optimize the results of a specific entity: the football club.In this respect, the main purpose of this thesis is to propose a model that combines machine learning techniques with multi-criteria analysis methods to improve the efficiency and objectivity of the football player selection process, while taking into account financial and managerial considerations. Our first contribution is to prioritize the physical, technical, tactical, and behavioral criteria of players using Random Forest, Entropy, and CRITIComenclature{CRITIC}{CRiteria Importance Through Intercriteria Correlation}algorithms. The second contribution is to rank players based on their performance using the TOPSIS method.To validate these contributions, we designed a decision support system that assists the sports decision maker by proposing players in order of performance. Our model does not aim to replace coaches but rather to integrate subjective and objective evaluations to provide a thorough understanding of the factors influencing sporting and managerial performance, thereby improving the accuracy of player selection. As football moves towards more data-oriented approaches, the combination of AI and MCDM can further optimize player selection processes by leveraging the benefits of objective data analysis and subjective expertise.The results obtained show the effectiveness of our approach in improving the performance of football teams, especially when supported and promoted by emotional intelligence, which refers to the manager's ability to recognize the substantial state of the players
Brettenny, Warren James. "Integer optimisation for the selection of a fantasy league cricket team." Thesis, Nelson Mandela Metropolitan University, 2010. http://hdl.handle.net/10948/1230.
Full textCroft, Chris. "Factors influencing Big 12 Conference college basketball male student-athletes' selection of a university." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2008. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.
Full textLourens, Mark. "Integer optimization for the selection of a twenty20 cricket team." Thesis, Nelson Mandela Metropolitan University, 2008. http://hdl.handle.net/10948/1000.
Full textLilja, Henric. "SELECTION AND PSYCHOSOCAL PREDICTORS OF WELLBEING: A STUDY AMONG FOTBALL ACADEMY PLAYERS." Thesis, Högskolan i Halmstad, Centrum för forskning om välfärd, hälsa och idrott (CVHI), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-16605.
Full textSvenska fotbollsförbundet
DUCA, MARCO. "EFFECTS OF RESISTANCE TRAINING ON SELECTION AND PERFORMANCE IN RUGBY UNION PLAYERS." Doctoral thesis, Università degli Studi di Milano, 2021. http://hdl.handle.net/2434/818776.
Full textIntroduction: Rugby union players must cope with diverse match demands depending on the playing position. Forwards (FWS) are more often engaged in static exertions (scrums, rucks, mauls) while backs (BKS) exhibition more dynamic actions (sprints, jumps, change of direction). These match demands dictate the anthropometrical and physical characteristics required to players to be successful. FWS are heavier and stronger, while BKS are leaner and faster. Despite the literature shows an overall advantage for stronger and heavier players to selection for international competition, limited data is present for Italian players. Body size, strength, power, and speed can be effectively improved by resistance training (RT). Yet, the debate is still open on the most effective RT modality for athletes. For instance, the efficacy of training to momentary muscular failure (FAIL), which seemed paramount towards increase muscle hypertrophy and strength, have recently been debated as RT not to failure (NO-FAIL) showed superior improvement in athletes’ strength and power. Aim: The aim of this thesis is two folds. First, which characteristics are predictor of selection for international competitions in Italian U20 players. Secondly, to assess the superior efficacy of either FAIL or NO-FAIL RT programs on improving players’ anthropometric and physical characteristics. Methods: For the first aim, anthropometric and physical characteristics, collected testing the variables of 72 U20 players, were retrospectively analyzed. Two-way analysis of variance, with selection for international tournaments and playing position as between subjects’ factors, was completed. Selection was also chosen as the dependent variable of multiple logistic regressions. For the second aim, 16 amateur rugby players were assigned to one of two groups (FAIL or NO-FAIL) and completed a seven weeks long RT program. Players’ anthropometric and physical variables were tested before and after the intervention. Results: ANOVA did not detect any significant interaction effects. The players’ body mass and lower body maximal strength resulted predictors of selection for U20 players. Analysis of the 13 effect sizes qualified that NO-FAIL RT allowed for superior improvements in lower body maximal strength and power, vertical jump height and power, linear sprint and change of direction. Conclusions: players’ body size and maximal strength are crucial for international selection in rugby. RT to FAIL elicits inferior improvements in these variables, and it should therefore be avoided. Strength and conditioning coaches should favor methods that allow for a better training intensity management in rugby players and exploit superior improvements in strength, power and speed.
Forslund, Ola. "Scattering and propagation of electromagnetic waves in planar and curved periodic structures - applications to plane wave filters, plane wave absorbers and impedance surfaces." Doctoral thesis, KTH, Alfvén Laboratory, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3825.
Full textThe subject of this thesis is scattering of electromagneticwaves from planar and curved periodic structures. The problemspresented are solved in the frequency domain.
Scattering from planar structures with two-dimensionalperiodic dependence of constitutive parameters is treated. Theconstitutive parameters are assumed to vary continuously orstepwise in a cross section of a periodically repeating cell.The variation along a longitudinal coordinate z is arbitrary. Ageneral skew lattice is assumed. In the numerical examples, lowloss and high loss dielectric materials are considered. Theproblem is solved by expanding the .elds and constitutiveparameters in quasi-periodic and periodic functionsrespectively, which are inserted into Maxwells equations.Through various inner products de.ned with respect to the cell,and elimination of the longitudinal vector components, a linearsystem of ordinary di.erential equations for the transversecomponents of the .elds is obtained. After introducing apropagator, which maps the .elds from one transverse plane toanother, the system is solved by backward integration.Conventional thin metallic FSS screens of patch or aperturetype are included by obtaining generalised transmission andre.ection matrices for these surfaces. The transmission andre.ection matrices are obtained by solving spectral domainintegral equations. Comparisons of the obtained results aremade with experimental results (in one particular case), andwith results obtained using a computer code based on afundamentally di.erent time domain approach.
Scattering from thin singly curved structures consisting ofdielectric materials periodic in one dimension is alsoconsidered. Both the thickness and the period are assumed to besmall. The .elds are expanded in an asymptotic power series inthe thickness of the structure, and a scaled wave equation issolved. A propagator mapping the tangential .elds from one sideto the other of the structure is derived. An impedance boundarycondition for the structure coated on a perfect electricconductor is obtained.
Keywords:electromagnetic scattering, periodicstructure, frequency selective structure, frequency selectivesurface, grating, coupled wave analysis, electromagneticbandgap, photonic bandgap, asymptotic boundary condition,impedance boundary condition, spectral domain method,homogenisation
Books on the topic "Player selection"
Fudenberg, Drew. Reputation and equilibrium selection in games with a patient player. Cambridge, Mass: Dept. of Economics, Massachusetts Institute of Technology, 1987.
Find full textHerzberg, Frank. Assessing an assessment center with regard to construct validity, interrater reliability, and inter-role-player reliability. Dublin: University College Dublin, 1997.
Find full textRensbergen, Henk van. Abandoned places: The photographer's selection. Tielt: Uitg. Lannoo N.V., 2014.
Find full textDk Publishing. Plants for Places. London: DK Pub., 2011.
Find full textSociety, American Horticultural, ed. AHS plants for places. New York: DK Pub., 2002.
Find full textJenkins, Paul Rigel. Natural selection. London: Nick Hern Books, 2008.
Find full textWhaley, George. Dad & Dave on our selection: The screenplay. St. Lucia, Qld., Australia: University of Queensland Press, 1995.
Find full textDonald, Bradman. The Bradman albums: Selections from Sir Donald Bradman's official collection. London: Macdonald, 1988.
Find full textOdegbami, Segun. Me, football and more: A selection of the media writings of "Mathematical" Segun Odegbami. [Nigeria?]: KD Books, 2013.
Find full textWilson, Robert. Robert Wilson: Portrait, still life, landscape : a selection. Rotterdam: The Museum, 1993.
Find full textBook chapters on the topic "Player selection"
Gil-Aluja, Jaime, and Anna M. Gil-Lafuente. "Affinity in the Selection of a Player." In Optimal Strategies in Sports Economics and Management, 1–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13205-6_1.
Full textMariano, Pedro, Luís Correia, and Carlos Grilo. "Selection of Cooperative Partners in n-Player Games." In Advances in Artificial Life. Darwin Meets von Neumann, 482–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21283-3_60.
Full textHoffman, Jay R. "Player Selection and Physical Attributes for Football Playing Success." In The Science of American Football, 57–76. New York, NY : Routledge, 2020.: Routledge, 2020. http://dx.doi.org/10.4324/9781003027881-4.
Full textMo, Jinyu, and Hong Xie. "A Multi-player MAB Approach for Distributed Selection Problems." In Advances in Knowledge Discovery and Data Mining, 243–54. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-33377-4_19.
Full textDivakarla, Usha, K. Chandrasekaran, K. Hemanth Kumar Reddy, and Manjula Gururaj. "Comprehensive Prediction Model for Player Selection in FIFA Manager Mode." In International Conference on Innovative Computing and Communications, 821–30. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2535-1_67.
Full textMishra, Poonam, Isha Talati, and Azharuddin Shaikh. "Supply Chain Network Optimization Through Player Selection Using Multi-objective Genetic Algorithm." In Asset Analytics, 281–315. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9698-4_16.
Full textSharma, Rizul, Upinder Kaur, and Rahul Singh. "Prediction on most-valuable player selection in NBA using machine learning algorithm." In Advances in Networks, Intelligence and Computing, 424–30. London: CRC Press, 2024. http://dx.doi.org/10.1201/9781003430421-41.
Full textKong, Xiangshen, Mu Fan, and Hui Zhang. "Factors Affecting NBA Player Draft Selection: An Analysis Based on a Generalized Linear Mixed Model." In Proceedings of the 14th International Symposium on Computer Science in Sport (IACSS 2023), 131–46. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2898-5_14.
Full textKhandelwal, Mayank, Jayant Prakash, and Tribikram Pradhan. "An Analysis of Best Player Selection Key Performance Indicator: The Case of Indian Premier League (IPL)." In Advances in Intelligent Systems and Computing, 173–90. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23036-8_16.
Full textKumar Mishra, Amit, Nisheeth Joshi, and Iti Mathur. "Using Analytic Hierarchal Processing in 26/11 Mumbai Terrorist Attack for Key Player Selection and Ranking." In Social Networking and Computational Intelligence, 401–26. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2071-6_33.
Full textConference papers on the topic "Player selection"
Raajesh, Sanjay, Noel Martin, Jyothsna Jiji, Aakash Nair, and Haritha H. "Cricket Team Selection and Player Analysis using Data Analytics." In 2024 IEEE Recent Advances in Intelligent Computational Systems (RAICS), 1–6. IEEE, 2024. http://dx.doi.org/10.1109/raics61201.2024.10689923.
Full textDutt, Rudra, Tarun Aditya Kusupati, Akshat Srivastava, and Debirupa Hore. "IPL Player Selection using Fuzzy Logic." In 2022 IEEE Industrial Electronics and Applications Conference (IEACon). IEEE, 2022. http://dx.doi.org/10.1109/ieacon55029.2022.9951755.
Full textYannakakis, Georgios N., and John Hallam. "Game and Player Feature Selection for Entertainment Capture." In 2007 IEEE Symposium on Computational Intelligence and Games. IEEE, 2007. http://dx.doi.org/10.1109/cig.2007.368105.
Full textRajesh, P., Bharadwaj, Mansoor Alam, and Mansour Tahernezhadi. "A Data Science Approach to Football Team Player Selection." In 2020 IEEE International Conference on Electro Information Technology (EIT). IEEE, 2020. http://dx.doi.org/10.1109/eit48999.2020.9208331.
Full textTouazi, Azzedine, Fatiha Mokdad, and Djamel Bouchaffra. "Feature Selection Scheme Based on Zero-Sum Two-Player Game." In 2014 22nd International Conference on Pattern Recognition (ICPR). IEEE, 2014. http://dx.doi.org/10.1109/icpr.2014.240.
Full textRuifei Xie, Bin Han, Lihua Li, Juan Zhang, and Lei Zhu. "Professional tennis player ranking strategy based Monte Carlo feature selection." In 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW). IEEE, 2011. http://dx.doi.org/10.1109/bibmw.2011.6112370.
Full textMohammad, Walid, and Sadia Sharmin. "Player selection in cricket based on similarity of playing conditions." In CHI '19: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3309700.3338441.
Full textChionas, Giorgos, Bogdan S. Chlebus, Dariusz R. Kowalski, and Piotr Krysta. "Adversarial Contention Resolution Games." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/289.
Full textNagarajan, Ramya, and Lin Li. "Optimizing NBA Player Selection Strategies Based on Salary and Statistics Analysis." In 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech). IEEE, 2017. http://dx.doi.org/10.1109/dasc-picom-datacom-cyberscitec.2017.175.
Full textChen, Yuefei, Junyan Dai, and Changjiang Zhang. "A Neural Network Model of the NBA Most Valued Player Selection Prediction." In the 2019 the International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3357777.3357786.
Full textReports on the topic "Player selection"
VEDESHKINA, NATALIA A., and VALENTINA A. MAXIMENKO. COMPUTER GAME "THE WAY TO A SECURE INTERNET". SIB-Expertise, November 2023. http://dx.doi.org/10.12731/er0743.18112023.
Full textWuxi, Bi, and Chen Zhenhua. PR469-173604-R01 Guidelines on the Selection and Application of Cathodic Protection Coupons. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), April 2021. http://dx.doi.org/10.55274/r0012092.
Full textSantiago, Ana, and Mariana Alfonso. Selection into Teaching: Evidence from Enseña Perú. Inter-American Development Bank, October 2010. http://dx.doi.org/10.18235/0008836.
Full textA. B. Robinson, G. S. Chang, Jr D. D. Keiser, D. M. Wachs, and D. L. Porter. Irradiation Performance of U-Mo Alloy Based ?Monolithic? Plate-Type Fuel ? Design Selection. Office of Scientific and Technical Information (OSTI), August 2009. http://dx.doi.org/10.2172/968567.
Full textSutipatanasomboon, Arpaporn. Petri Dishes with Agar: How to Make Agar Plates. ConductScience, June 2022. http://dx.doi.org/10.55157/cs20220627.
Full textNoor, Juliet, and Mohamed Noor. Finding Selection in All the Right Places: A College Genetics Laboratory Inquiry-Based Learning Exercise. Genetics Society of America Peer-Reviewed Education Portal (GSA PREP), February 2013. http://dx.doi.org/10.1534/gsaprep.2013.001.
Full textLeaver, Clare, Owen Ozier, Pieter Serneels, and Andrew Zeitlin. Recruitment, Effort, and Retention Effects of Performance Contracts for Civil Servants: Experimental Evidence from Rwandan Primary Schools. Research on Improving Systems of Education (RISE), September 2020. http://dx.doi.org/10.35489/bsg-rise-wp_2020/048.
Full textDaniel. L52353 Materials Selection, Welding and Weld Monitoring - Optimized Welding Solutions for X100 Line Pipe. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), April 2012. http://dx.doi.org/10.55274/r0010650.
Full textWang and Zhou. L52334 Curved Wide Plate Test Results and Transferability of Test Specimens. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), December 2011. http://dx.doi.org/10.55274/r0010008.
Full textGrabau, Ashley. Exploring event planner preferences in venue selection and the role of virtual events in the post Covid-19 era. Ames (Iowa): Iowa State University, December 2023. http://dx.doi.org/10.31274/cc-20240624-699.
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