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Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer

References Audas, R., Dobson, S., & Goddard, J. (2002). The impact of managerial change on team performance in professional sports. Journal of Economics and Business , 54 , 633–650. Cain, M., Law, D., & Peel, D. (2000). The favourite–longshot bias and market efficiency in UK football betting. Scottish Journal of Political Economy , 47 , 25–36. Dixon, M. & Pope, P. (2004). The value of statistical forecasts in the UK association football betting market. International Journal of Forecasting , 20 , 697–711. Dobson, S. & Goddard, J

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Performance in Team Sports: Identifying the Keys to Success in Soccer

-270. Carling C, Reilly T, Williams A. Performance assessment for field sports: Physiological, psychological and match notational assessment in practice. London: Routledge, 2009. Carling C, Williams A, Reilly T. Handbook of soccer match analysis: a systematic approach to improving performance. London: Routledge, 2005. Carmichael F, Thomas D, Ward R. Production and efficiency in Association Football. J Sports Econ, 2001; 2(3): 228-243. Carmichael F, Thomas D, Ward R. Team performance: the case of

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Analyzing passing networks in association football based on the difficulty, risk, and potential of passes

-team activity in attacking phases of professional football. International Journal of Performance Analysis in Sport , 14, 692–708. Gonçalves, B., Coutinho, D., Santos, S., Lago-Penas, C., Jiménez, S., & Sampaio, J. (2017). Exploring team passing networks and player movement dynamics in youth association football. PloS One , 12, e0171156. Håland, E., Wiig, A., Stålhane, M., & Hvattum, L. (2019). Evaluating passing ability in association football. IMA Journal of Management Mathematics , forthcoming. Kang, B., Huh, M., & Choi, S. (2015). Performance analysis

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Physical Demands of Top-Class Soccer Friendly Matches in Relation to a Playing Position Using Global Positioning System Technology

, Helsen W. Activity profile of top-class association football referees in relation to fitness-test performance and match standard. J Sports Sci , 2009; 27: 9-17 McLellan CP, Lovell DI, Gass GC. Biochemical and endocrine responses to impact and collision during elite rugby league match play. J Strength Cond Res , 2011; 25: 1553-1562 Mohr M, Krustrup P, Bangsbo J. Match performance of high-standard soccer players with special reference to development of fatigue. J Sports Sci , 2003; 21: 519-528 Osgnach C, Poser S, Bernardini R, Rinaldo R, Di Prampero

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Offensive Sequences in Youth Soccer: Effects of Experience and Small-Sided Games

The present study aimed to analyze the interaction and main effects of deliberate practice experience and smallsided game format (3 vs. 3 and 6 vs. 6 plus goalkeepers) on the offensive performance of young soccer players. Twentyeight U-15 male players were divided into 2 groups according to their deliberate practice experience in soccer (i.e., years of experience in federation soccer): Non-Experienced (age: 12.84 ± 0.63 years) and Experienced (age: 12.91 ± 0.59 years; experience: 3.93 ± 1.00 years). The experimental protocol consisted of 3 independent sessions separated by one-week intervals. In each session both groups performed each small-sided game during 10 minutes interspersed with 5 minutes of passive recovery. To characterize the recorded offensive sequences we used the Offensive Sequences Characterization System, which includes performance indicators previous applied in other studies. No interaction effects on the offensive performance were found between both factors. Non-parametric MANOVA revealed that the factor “experience level” had a significant effect (p<0.05) on performance indicators that characterize the development of offensive sequences, especially in 6 vs. 6 + GKs. While experienced players produced longer offensive sequences with greater ball circulation between them, the non-experienced participants performed faster offensive sequences with a predominance of individual actions. Furthermore, significant differences were observed (p<0.05) in the development and finalization of offensive sequences within each group, when comparing small-sided game formats. Evidence supports that small-sided games can serve several purposes as specific means of training. However, the manipulation of game format should always consider the players’ individual constraints.

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Combined Small‐Sided Game and High‐Intensity Interval Training in Soccer Players: The Effect of Exercise Order

Abstract

The aim of the present study was to compare combined small‐sided game (SSG) and high‐intensity interval training (HIT) with different order. Twenty‐one semi‐professional soccer players were divided into two groups: SSG+HIT (n = 10) and HIT+SSG (n = 11), and underwent similar four‐week training programs. Players completed the 30‐15 Intermittent Fitness Test (30‐15IFT) before and after the experiment; maximum speed (VIFT) was recorded. During the experiment, seven sessions of SSG (3 vs 3) and HIT (15ʺ‐15ʺ with 95‐100% VIFT) were implemented. Weekly accumulated training loads for both groups during the experiment were similar. Moderate improvements in VIFT were observed in both SSG+HIT (+6.2%, 90% confidence limits, [CL] 4.6; 7.7 and Effect Size, [ES] +0.96) and HIT+SSG (+6.9%, 90% CL 4.6; 9.3 and ES +0.97) groups. Between‐group difference in changes of VIFT was trivial (+0.7%, 90% CL ‐1.8; 3.3 and ES +0.11). Combining SSG and HIT in different order elicited the same enhancement in high‐intensity intermittent performance in soccer players.

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Football does not improve mental health: a systematic review on football and mental health disorders

Introduction Football is a global game and a huge international business. The game is played for 90 min by two teams of 11 players, both teams trying to score by hitting the one ball with the foot (or leg or head, but not the hands) into the opponents’ goal. The game is called football in Europe, Asia and South America, but soccer (shortened form Association football) in North America, Australia and South Africa, essentially to distinguish football, respectively soccer, from other versions of regional football games such as American or Australian football

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Croatian First Football League: Teams' performance in the championship

References 1. Arabzad, A.C. (2014). Football Match Results Prediction Using Artificial eural Networks: The Case of Iran Pro League. International Journal of Applied Research on Industrial Engineering. Vol. 1, No. 3, pp 159-179. 2. Constantinou, A.C., Fenton, N.E., Neil, M. (2012). pi-football: A Bayesian network model for forecasting Association Football match outcomes. Knowledge-Based Systems, 36, pp. 322-339. 3. Dixon, M.J., Coles, S.G. (1997). Modelling Association Football Scores and Inefficiencies in the

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The Elements of Executive Attention in Top Soccer Referees and Assistant Referees

Expert Assistant Referees in Association Football: Perception and Recall of Spatial Positions in Complex Dynamic Events. J Exp Psychol - Appl, 2008; 14: 21 - 35 Gomes LM, Martinho AJ, Castelo NA. Effects of occupational exposure to low frequency noise on cognition. Aviat Space Envir Md, 1999; 70(2): A115 - A118 Helsen W, Bultynck JB. Physical and perceptual - cognitive demands of top - class refereeing in association football. J Sport Sci, 2004; 22: 179-189 Helsen W, Gilis B, Weston M. Errors in judging “offside” in

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The training of soccer assistant referees beyond on-field experience: the use of the Interactive Video Test

., & Morya, E. (2002). Flag errors in soccer games: The flash-lag effect brought to real life. Perception, 31, 1205–1210. Catteeuw, P., Helsen, W., Gilis, B., & Wagemans, J. (2009). Decision-making skills, role specificity, and deliberate practice in association football refereeing. Journal of Sports Sciences, 27 (11), 1125-1136. Catteeuw, P., Gilis, B., García-Aranda, J. M., Tresaco, F., Wagemans, J., & Helsen, W. (2010). Offside decision making in the 2002 and 2006 FIFA World Cups. Journal of Sports Sciences, 28 (10), 1027-1032. Ericsson, K. A

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