Sporda Veri Madenciliği

Albert, J., & Grieve, R. (2009). Sports data mining. In Handbook of Research on Sport and Business (s. 537-556). Edward Elgar Publishing.

Baca, A., Mutavcic, D., & Milicic, J. (2016). Application of data mining techniques in football. International Journal of Computer Science in Sport, 15(3), 129-145.

Barros, R. M. L., Misuta, M. S., Menezes, R. P., Figueroa, P. J., Moura, F. A., Cunha, S. A., ... & Leite, N. J. (2007). Analysis of the distances covered by first division Brazilian soccer players obtained with an automatic tracking method. Journal of Sports Sciences, 25(12), 1247-1254.

Bittencourt, N. F., Meeuwisse, W. H., Mendonça, L. D., Nettel-Aguirre, A., Ocarino, J. M., Fonseca, S. T., ... & Del Vecchio, F. B. (2016). Complex systems approach for sports injuries: moving from risk factor identification to injury pattern recognition—narrative review and new concept. British Journal of Sports Medicine, 50(21), 1309-1314.

Bittencourt, N. F., Meeuwisse, W. H., Mendonça, L. D., Nettel-Aguirre, A., Ocarino, J. M., Fonseca, S. T., ... & Del Vecchio, F. B. (2016). Complex systems approach for sports injuries: moving from risk factor identification to injury pattern recognition—narrative review and new concept. British Journal of Sports Medicine, 50(21), 1309-1314.

Buldt, A. K., Heng, H. J., & Wilson, B. (2016). Mining Match Data for Tactical Performance Analysis in Football: A Systematic Review. International Journal of Performance Analysis in Sport, 16(2), 647-665.

Cairo, A. (2013). The functional art: An introduction to information graphics and visualization. New Riders.

Carling, C., & Collins, D. (2014). Comment on "Performance analysis in football: A critical review and implications for future research" by O'Donoghue (2014). Journal of Sports Sciences, 32(1), 31-34.

Ceylan, R., & Tüzün, H. (2019). Data mining applications in sports: A systematic literature review. International Journal of Computer Science in Sport, 18(1), 65-83.

Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey. Mobile Networks and Applications, 19(2), 171-209.

Chen, Y., & Huang, C. (2018). Sports Data Mining: A Review. International Journal of Computer Science in Sport, 17(3), 227-240.

Cortez, P., Silva, A. M., & Rocha, M. P. (2016). Using data mining to predict the final result of football matches. Knowledge-Based Systems, 111, 111-119.

Coşlu, E. (2013). Veri madenciliği. Akademik bilişim, 23-25.

Dean, J., & Ghemawat, S. (2008). MapReduce: simplified data processing on large clusters. Communications of the ACM, 51(1), 107-113.

Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI magazine, 17(3), 37-54.

Few, S. (2012). Show me the numbers: Designing tables and graphs to enlighten. Analytics Press.

Gabbett, T. J., & Hulin, B. T. (2016). Activity and recovery cycles and skill involvements of successful and unsuccessful elite rugby league teams: A longitudinal analysis of evolutionary changes in National Rugby League match-play. Journal of Sports Sciences, 34(14), 1315-1321.

Gürsoy, D., & Kılıç, B. (2018). Data mining in sports management: a systematic literature review. Journal of Data, Information and Management, 1(2), 57-70.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis. Cengage Learning.

Han, J., Kamber, M., & Pei, J. (2011). Data mining: concepts and techniques. Elsevier.

Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media.

Heer, J., & Shneiderman, B. (Eds.). (2012). Interactive dynamics for visual analysis: A taxonomy of tools that support the fluent and flexible use of visualizations. ACM transactions on interactive intelligent systems (TiiS), 2(4), 19.

Hickey, D. T., & Solbeck, J. A. (2018). A systematic review of data mining techniques for injury prediction in field-based sports. Sports Medicine-Open, 4(1), 58.

Hickey, D. T., & Solbeck, J. A. (2018). A systematic review of data mining techniques for injury prediction in field-based sports. Sports Medicine-Open, 4(1), 58.

Hughes, M. G., & Bartlett, R. M. (2008). What is skill in sport? In T. Reilly, K. Davids, & J. Burkett (Eds.), Kinanthropometry and exercise physiology laboratory manual: Tests, procedures, and data (Vol. 1, pp. 81-100). Routledge.

Hulin, B. T., Gabbett, T. J., Blanch, P., Chapman, P., Bailey, D., & Orchard, J. W. (2016). Spikes in acute workload are associated with increased injury risk in elite cricket fast bowlers. British Journal of Sports Medicine, 50(16), 231-236.

James, D. A., & Lesser, V. M. (2019). Data mining and analytics in sports. Journal of Sports Analytics, 5(3), 129-134.

Jin, X., Han, J., & Chen, C. (2017). A Study of Basketball Player Performance Prediction Based on Data Mining Technology. Journal of Applied Mathematics, 2017.

Ko, Y. J., & Pastore, D. L. (2005). A hierarchical model of service quality for the recreational sport industry. Sport Management Review, 8(1), 1-27.

Lim, Y., & Chow, K. L. (2017). Predicting sports performance using data mining techniques: a systematic review. International Journal of Sports Science & Coaching, 12(3), 298-319.

Lin, H. C., & Chen, C. F. (2018). Application of data mining techniques in team sports: A survey. International Journal of Performance Analysis in Sport, 18(4), 551-574.

Liu, F., & Cao, L. (2018). Sports data mining and analytics: Enhancing performance and exploring strategies. CRC Press.

Liu, F., & Zhang, J. (2012). Sports data mining based on association rules. Procedia Engineering, 29, 775-780.

Liu, H., & Li, L. (2020). Big data analytics for team sports: A systematic review. Frontiers in Psychology, 11, 780.

Macdonald, J. R. (2012). Data mining in sports: A systematic review. International Journal of Performance Analysis in Sport, 12(1), 159-176.

Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to information retrieval. Cambridge University Press.

McCall, A., Nedelec, M., Carling, C., Le Gall, F., Berthoin, S., Dupont, G., & Buchheit, M. (2015). Reliability and sensitivity of a simple isometric posterior lower limb muscle test in professional football players. Journal of Sports Sciences, 33(14), 1457-1466.

Medeiros, A. K., & Bampouras, T. M. (2018). Data Mining in Sports: A Systematic Review. International Journal of Performance Analysis in Sport, 18(5), 695-745.

Medeiros, M. F., Avolio, F. C., Ribeiro, C. H., & Voss, M. L. (2019). Sports data mining: a review of literature and its applications. Journal of Sports Analytics, 5(2), 75-96.

Meza, I., Parra, D., & Brizuela, C. (2017). Optimization Techniques in Data Mining: A Survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7(4), e1219.

Murray, S. (2017). Interactive data visualization for the web: An introduction to designing with D3. O'Reilly Media.

Rabbani, A., Schaefer, D., & Liu, Y. (2015). A data mining approach to optimize performance of players in team sports. Journal of Sports Analytics, 1(2), 111-120.

Schwab, R., Memmert, D., & Raabe, D. (2019). Data science in elite soccer: A systematic review. Journal of Sports Sciences, 37(11), 1291-1303.

Smith, A. (2019). The Role of Data Mining in Sports Analytics. Journal of Sports Analytics, 5(1), 1-19.

Smith, J. (2019). The Impact of Internet Technology on Data Collection and Storage. Journal of Data and Information Science, 4(1), 1-12.

Tufte, E. R. (2001). The visual display of quantitative information. Graphics press.

Tufte, E. R. (2001). The visual display of quantitative information. Graphics press.

Ware, C. (2004). Information visualization: Perception for design. Morgan Kaufmann.

Yang, Y., & Swartz, T. B. (2019). Predicting player performance in basketball using machine learning techniques. PloS One, 14(6), e0217410.

Yu, C., & Yen, D. C. (2012). Mining social media data for understanding users' opinions on sport events. Decision Support Systems, 53(4), 772-782.

Zhang, S., Liu, Y., Liu, H., & Li, C. (2018). Data mining in sports: A systematic review. IEEE Access, 6, 12612-12623.

Albert, J., & Grieve, R. (2009). Sports data mining. In Handbook of Research on Sport and Business (s. 537-556). Edward Elgar Publishing.

Baca, A., Mutavcic, D., & Milicic, J. (2016). Application of data mining techniques in football. International Journal of Computer Science in Sport, 15(3), 129-145.

Barros, R. M. L., Misuta, M. S., Menezes, R. P., Figueroa, P. J., Moura, F. A., Cunha, S. A., ... & Leite, N. J. (2007). Analysis of the distances covered by first division Brazilian soccer players obtained with an automatic tracking method. Journal of Sports Sciences, 25(12), 1247-1254.

Bittencourt, N. F., Meeuwisse, W. H., Mendonça, L. D., Nettel-Aguirre, A., Ocarino, J. M., Fonseca, S. T., ... & Del Vecchio, F. B. (2016). Complex systems approach for sports injuries: moving from risk factor identification to injury pattern recognition—narrative review and new concept. British Journal of Sports Medicine, 50(21), 1309-1314.

Bittencourt, N. F., Meeuwisse, W. H., Mendonça, L. D., Nettel-Aguirre, A., Ocarino, J. M., Fonseca, S. T., ... & Del Vecchio, F. B. (2016). Complex systems approach for sports injuries: moving from risk factor identification to injury pattern recognition—narrative review and new concept. British Journal of Sports Medicine, 50(21), 1309-1314.

Buldt, A. K., Heng, H. J., & Wilson, B. (2016). Mining Match Data for Tactical Performance Analysis in Football: A Systematic Review. International Journal of Performance Analysis in Sport, 16(2), 647-665.

Cairo, A. (2013). The functional art: An introduction to information graphics and visualization. New Riders.

Carling, C., & Collins, D. (2014). Comment on "Performance analysis in football: A critical review and implications for future research" by O'Donoghue (2014). Journal of Sports Sciences, 32(1), 31-34.

Ceylan, R., & Tüzün, H. (2019). Data mining applications in sports: A systematic literature review. International Journal of Computer Science in Sport, 18(1), 65-83.

Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey. Mobile Networks and Applications, 19(2), 171-209.

Chen, Y., & Huang, C. (2018). Sports Data Mining: A Review. International Journal of Computer Science in Sport, 17(3), 227-240.

Cortez, P., Silva, A. M., & Rocha, M. P. (2016). Using data mining to predict the final result of football matches. Knowledge-Based Systems, 111, 111-119.

Coşlu, E. (2013). Veri madenciliği. Akademik bilişim, 23-25.

Dean, J., & Ghemawat, S. (2008). MapReduce: simplified data processing on large clusters. Communications of the ACM, 51(1), 107-113.

Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI magazine, 17(3), 37-54.

Few, S. (2012). Show me the numbers: Designing tables and graphs to enlighten. Analytics Press.

Gabbett, T. J., & Hulin, B. T. (2016). Activity and recovery cycles and skill involvements of successful and unsuccessful elite rugby league teams: A longitudinal analysis of evolutionary changes in National Rugby League match-play. Journal of Sports Sciences, 34(14), 1315-1321.

Gürsoy, D., & Kılıç, B. (2018). Data mining in sports management: a systematic literature review. Journal of Data, Information and Management, 1(2), 57-70.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis. Cengage Learning.

Han, J., Kamber, M., & Pei, J. (2011). Data mining: concepts and techniques. Elsevier.

Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media.

Heer, J., & Shneiderman, B. (Eds.). (2012). Interactive dynamics for visual analysis: A taxonomy of tools that support the fluent and flexible use of visualizations. ACM transactions on interactive intelligent systems (TiiS), 2(4), 19.

Hickey, D. T., & Solbeck, J. A. (2018). A systematic review of data mining techniques for injury prediction in field-based sports. Sports Medicine-Open, 4(1), 58.

Hickey, D. T., & Solbeck, J. A. (2018). A systematic review of data mining techniques for injury prediction in field-based sports. Sports Medicine-Open, 4(1), 58.

Hughes, M. G., & Bartlett, R. M. (2008). What is skill in sport? In T. Reilly, K. Davids, & J. Burkett (Eds.), Kinanthropometry and exercise physiology laboratory manual: Tests, procedures, and data (Vol. 1, pp. 81-100). Routledge.

Hulin, B. T., Gabbett, T. J., Blanch, P., Chapman, P., Bailey, D., & Orchard, J. W. (2016). Spikes in acute workload are associated with increased injury risk in elite cricket fast bowlers. British Journal of Sports Medicine, 50(16), 231-236.

James, D. A., & Lesser, V. M. (2019). Data mining and analytics in sports. Journal of Sports Analytics, 5(3), 129-134.

Jin, X., Han, J., & Chen, C. (2017). A Study of Basketball Player Performance Prediction Based on Data Mining Technology. Journal of Applied Mathematics, 2017.

Ko, Y. J., & Pastore, D. L. (2005). A hierarchical model of service quality for the recreational sport industry. Sport Management Review, 8(1), 1-27.

Lim, Y., & Chow, K. L. (2017). Predicting sports performance using data mining techniques: a systematic review. International Journal of Sports Science & Coaching, 12(3), 298-319.

Lin, H. C., & Chen, C. F. (2018). Application of data mining techniques in team sports: A survey. International Journal of Performance Analysis in Sport, 18(4), 551-574.

Liu, F., & Cao, L. (2018). Sports data mining and analytics: Enhancing performance and exploring strategies. CRC Press.

Liu, F., & Zhang, J. (2012). Sports data mining based on association rules. Procedia Engineering, 29, 775-780.

Liu, H., & Li, L. (2020). Big data analytics for team sports: A systematic review. Frontiers in Psychology, 11, 780.

Macdonald, J. R. (2012). Data mining in sports: A systematic review. International Journal of Performance Analysis in Sport, 12(1), 159-176.

Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to information retrieval. Cambridge University Press.

McCall, A., Nedelec, M., Carling, C., Le Gall, F., Berthoin, S., Dupont, G., & Buchheit, M. (2015). Reliability and sensitivity of a simple isometric posterior lower limb muscle test in professional football players. Journal of Sports Sciences, 33(14), 1457-1466.

Medeiros, A. K., & Bampouras, T. M. (2018). Data Mining in Sports: A Systematic Review. International Journal of Performance Analysis in Sport, 18(5), 695-745.

Medeiros, M. F., Avolio, F. C., Ribeiro, C. H., & Voss, M. L. (2019). Sports data mining: a review of literature and its applications. Journal of Sports Analytics, 5(2), 75-96.

Meza, I., Parra, D., & Brizuela, C. (2017). Optimization Techniques in Data Mining: A Survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7(4), e1219.

Murray, S. (2017). Interactive data visualization for the web: An introduction to designing with D3. O'Reilly Media.

Rabbani, A., Schaefer, D., & Liu, Y. (2015). A data mining approach to optimize performance of players in team sports. Journal of Sports Analytics, 1(2), 111-120.

Schwab, R., Memmert, D., & Raabe, D. (2019). Data science in elite soccer: A systematic review. Journal of Sports Sciences, 37(11), 1291-1303.

Smith, A. (2019). The Role of Data Mining in Sports Analytics. Journal of Sports Analytics, 5(1), 1-19.

Smith, J. (2019). The Impact of Internet Technology on Data Collection and Storage. Journal of Data and Information Science, 4(1), 1-12.

Tufte, E. R. (2001). The visual display of quantitative information. Graphics press.

Tufte, E. R. (2001). The visual display of quantitative information. Graphics press.

Ware, C. (2004). Information visualization: Perception for design. Morgan Kaufmann.

Yang, Y., & Swartz, T. B. (2019). Predicting player performance in basketball using machine learning techniques. PloS One, 14(6), e0217410.

Yu, C., & Yen, D. C. (2012). Mining social media data for understanding users' opinions on sport events. Decision Support Systems, 53(4), 772-782.

Zhang, S., Liu, Y., Liu, H., & Li, C. (2018). Data mining in sports: A systematic review. IEEE Access, 6, 12612-12623.