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Zachary Zenko, Panteleimon Ekkekakis and Dan Ariely

There is a paucity of methods for improving the affective experience of exercise. We tested a novel method based on discoveries about the relation between exercise intensity and pleasure, and lessons from behavioral economics. We examined the effect of reversing the slope of pleasure during exercise from negative to positive on pleasure and enjoyment, remembered pleasure, and forecasted pleasure. Forty-six adults were randomly assigned to a 15-min bout of recumbent cycling of either increasing intensity (0–120% of watts corresponding to the ventilatory threshold) or decreasing intensity (120–0%). Ramping intensity down, thereby eliciting apositive slope of pleasure during exercise, improved postexercise pleasure and enjoyment, remembered pleasure, and forecasted pleasure. The slope of pleasure accounted for 35–46% of the variance in remembered and forecasted pleasure from 15 min to 7 days postexercise. Ramping intensity down makes it possible to combine exposure to vigorous and moderate intensities with a pleasant affective experience.

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Óscar Martínez de Quel, Ignacio Ara, Mikel Izquierdo and Carlos Ayán

majority of them included judo 9 and Olympic wrestling 10 fighters with no previous studies including karate athletes. Thus, in the light of all this, this research aims at assessing the discriminative ability of several fitness dimensions and anthropometric attributes for forecasting competitive success

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Jasmin C. Hutchinson, Zachary Zenko, Sam Santich and Paul C. Dalton

having similar mean affective responses during exercise, the decreasing intensity group reported more positive postexercise pleasure, remembered pleasure, forecasted pleasure, and enjoyment of exercise. Based upon the contributions of Focht et al. ( 2015 ), Greene and Petruzzello ( 2015 ), and Zenko et

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Marcus J. Colby, Brian Dawson, Peter Peeling, Jarryd Heasman, Brent Rogalski, Michael K. Drew and Jordan Stares

injury risk, identifying 50% of injuries in this cohort. As such, preventive strategies should ensure AF players attain >150 m of sprint volume per week to maintain a minimum workload for competitive demands. 2 Practitioners may also take a selective prevention approach 29 for players forecasted to

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Kristin D. Morgan

cruciate ligament deficient knee . Clin Biomech . 2004 ; 19 ( 9 ): 957 – 963 . doi:10.1016/j.clinbiomech.2004.06.008 10.1016/j.clinbiomech.2004.06.008 15. Box GEP , Jenkins GM . Time Series Analysis: Forecasting and Control, revised ed. San Francisco, CA : Holden-Day ; 1976 . 16. Montgomery

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Anna Sverdlik, Robert J. Vallerand, Ariane St-Louis, Michael Sam Tion and Geneviève Porlier

, & Lavigne, 2009 , Study 2). Finally, some scientists have begun to explore the role of passion in the use of future temporal processes, such as affective forecasting. Wilson and Gilbert ( 2003 ) defined affective forecasting as the ability to predict how one will feel in a future situation. Their research

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Stuart R. Graham, Stuart Cormack, Gaynor Parfitt and Roger Eston

mesocycles of training. 1 – 3 The majority of investigations assessing the efficacy of using a mathematical model approach to optimally guide the periodicity of physical training and forecast future physical performance outcomes have used empiric training and performance data from athletes competing in

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Tania Pereira, John Durocher and Jamie Burr

physical demand of snowmobiling. Using the linear regression of HR and VO 2 established during the graded exercise test, the expected HR while riding was forecast using the riding VO 2 and compared with the concurrently measured HR to determine offset. Muscular Strength and Power Strength and power tests

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Job Fransen, Adam Baxter-Jones and Stephen Woodcock

, Wheelwright SC , Hyndman RJ . Forecasting: Methods and Applications . New York, NY : Wiley ; 1998 . 6. Mirwald RL , Baxter-Jones AD , Bailey DA , Beunen GP . An assessment of maturity from anthropometric measurements . Med Sci Sports Exerc . 2002 ; 34 ( 4 ): 689 – 94 . PubMed 11932580 7

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Tanya R. Berry, Wendy M. Rodgers, Alison Divine and Craig Hall

forecasting (i.e., predicting how you will feel about a situation in the future); such forecasting is based exclusively on explicit evaluations even though implicit evaluations are also an important factor in how one feels ( Shoda et al., 2014b ). Brand and Ekkekakis ( 2017 ) also argue that implicit