SBBD

Paper Registration

1

Select Book

2

Select Paper

3

Fill in paper information

4

Congratulations

Fill in your paper information

English Information

(*) To change the order drag the item to the new position.

Authors
# Name
1 Lucas Calmon(lucas.calmon@aluno.cefet-rj.br)
2 Rodrigo Ferro(rodrigo.ferro@aluno.cefet-rj.br)
3 Carlos Pereira(carlos.pereira.1@aluno.cefet-rj.br)
4 Caio Souza(caio.souza.4@aluno.cefet-rj.br)
5 Lucas Tavares(lucas.giusti@eic.cefet-rj.br)
6 Glauco Amorim(glauco.amorim@eic.cefet-rj.br)
7 Eduardo Ogasawara(eogasawara@ieee.org)

(*) To change the order drag the item to the new position.

Reference
# Reference
1 Al-Asadi, M. A. and Tasdemir, S. (2022). Predict the Value of Football Players Using FIFA Video Game Data and Machine Learning Techniques. IEEE Access, 10:22631 – 22645.
2 Beal, R., Norman, T. J., and Ramchurn, S. D. (2019). Artificial intelligence for team sports: a survey. Knowledge Engineering Review, 34.
3 Bezuglov, E., Morgans, R., Butovskiy, M., Emanov, A., Shagiakhmetova, L., Pirmakhanov, B., Waskiewicz, Z., and Lazarev, A. (2023). The relative age effect is widespread among European adult professional soccer players but does not affect their market value. PLoS ONE, 18(3 March).
4 Chi, Y. K., Kim, T. H., Han, J. W., Lee, S. B., Park, J. H., Lee, J. J., Youn, J. C., Jhoo, J. H., Lee, D. Y., and Kim, K. W. (2012). Impaired design fluency is a marker of pathological cognitive aging; results from the Korean longitudinal study on health and aging. Psychiatry Investigation, 9(1):59 – 64.
5 da Silva Muniz, L. and da Silva, M. (2020). Análise das demonstrações contábeis dos clubes brasileiros de futebol: comparação entre a situação econômica e financeira e o aproveita- mento nas partidas oficiais de 2015 a 2017. CAFI, 3(1):17–32.
6 Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64:135 – 168.
7 Mello, M., Belloni, V., Vasconcellos, F., Soares, J., Ogasawara, E., and Giusti, L. (2021). Funções Executivas e Idade Relativa como Preditores de Sucesso no Futebol. In Anais da Escola Regional de Informática do Rio de Janeiro (ERI-RJ), pages 111–118. SBC.
8 Scarpina, F. and Tagini, S. (2017). The stroop color and word test. Frontiers in Psychology, 8(APR).
9 Shibuya-Tayoshi, S., Sumitani, S., Kikuchi, K., Tanaka, T., Tayoshi, S., Ueno, S.-I., and Oh- mori, T. (2007). Activation of the prefrontal cortex during the Trail-Making Test detec- ted with multichannel near-infrared spectroscopy. Psychiatry and Clinical Neurosciences, 61(6):616 – 621.
10 Soliman, G., El-Nabawy, A., Misbah, A., and Eldawlatly, S. (2017). Predicting all star player in the national basketball association using random forest. In 2017 Intelligent Systems Con- ference, IntelliSys 2017, volume 2018-January, pages 706 – 713.
11 Van Bulck, D., Vande Weghe, A., and Goossens, D. (2023). Result-based talent identification in road cycling: discovering the next Eddy Merckx. Annals of Operations Research, 325(1):539 – 556.
12 Verburgh, L., Scherder, E., van Lange, P., and Oosterlaan, J. (2016). The key to success in elite athletes? Explicit and implicit motor learning in youth elite and non-elite soccer players. Journal of Sports Sciences, 34(18):1782 – 1790.
13 Werneck, R. and Figueiredo, A. (2024). Goldfit Soccer: A Multidimensional Model for Talent Identification of Young Soccer Players. Research Quarterly for Exercise and Sport, 0(0):1– 15.