This aim of this study was to examine the validity of energy expenditure derived from microtechnology when measured during a repeated-effort rugby protocol. Sixteen male rugby players completed a repeated-effort protocol comprising 3 sets of 6 collisions during which movement activity and energy expenditure (EE) were measured using microtechnology. In addition, energy expenditure was estimated from open-circuit spirometry (EE). While related (r = .63, 90%CI .08-.89), there was a systematic underestimation of energy expenditure during the protocol (-5.94 ± 0.67 kcal/min) for EE (7.2 ± 1.0 kcal/min) compared with EE (13.2 ± 2.3 kcal/min). High-speed-running distance (r = .50, 95%CI -.66 to .84) was related to EE, while PlayerLoad was not (r = .37, 95%CI -.81 to .68). While metabolic power might provide a different measure of external load than other typically used microtechnology metrics (eg, high-speed running, PlayerLoad), it underestimates energy expenditure during intermittent team sports that involve collisions.

It is important to understand the extent to which physical contact changes the internal and external load during rugby simulations that aim to replicate the demands of match play. Accordingly, this study examined the role of physical contact on the physiological and perceptual demands during and immediately after a simulated rugby league match. Nineteen male rugby players completed a contact (CON) and a noncontact (NCON) version of the rugby league match-simulation protocol in a randomized crossover design with 1 wk between trials. Relative distance covered (ES = 1.27; ± 0.29), low-intensity activity (ES = 1.13; ± 0.31), high-intensity running (ES = 0.49; ± 0.34), heart rate (ES = 0.52; ± 0.35), blood lactate concentration (ES = 0.78; ± 0.34), rating of perceived exertion (RPE) (ES = 0.72; ± 0.38), and session RPE (ES = 1.45; ± 0.51) were all higher in the CON than in the NCON trial. However, peak speeds were lower in the CON trial (ES = -0.99; ± 0.40) despite unclear reductions in knee-extensor (ES = 0.19; ± 0.40) and -flexor (ES = 0.07; ± 0.43) torque. Muscle soreness was also greater after CON than in the NCON trial (ES = 0.97; ± 0.55). The addition of physical contact to the movement demands of a simulated rugby league match increases many of the external and internal demands but also results in players' slowing their peak running speed during sprints. These findings highlight the importance of including contacts in simulation protocols and training practices designed to replicate the demands of real match play.

Entrepreneurship has been variously defined. Schumpeter [1], for example, suggested it involves "the carrying out of new combinations of activities". Drucker[2] describes it as "searching for, responding to, and exploiting opportunities". McMullan and Long[3] define it as "involving uncertainty and risk, managerial competence, and creative opportunism". Teaching entrepreneurship and providing managers with the opportunity to learn about entrepreneurship continues to be actively discussed as the field evolves and develops [4].This article explores how a particular type of experiential activity can be a vehicle to help people to learn how to enhance their entrepreneurial behaviour. Our particular interest is in behavioural simulations[5], wherein people experience the unique character, complexity, and often ill-structured nature of both management in general and entrepreneurship in particular. The empirical work of Hills[6] and a discussion of entrepreneurship education research by Block and Stumpf [7] suggest that goals for entrepreneurship education include abilities to: acquire knowledge and concepts germane to entrepreneurship; acquire skill in the use of such techniques in analysing business situations and synthesising action plans; identify and stimulate entrepreneurial drive, talent and skill; undo the risk-averse bias of many analytical techniques; develop empathy and support for the unique aspects of entrepreneurship; and alter attitudes towards change in such a way that individuals use change as a stimulus for learning rather than denying or resisting it. If one accepts these learning objectives, then behavioural simulations appear to be an underutilised technology that can help people learn to behave entrepreneurially. Simulating EntrepreneurshipSimulations have been designed to model many different processes, events, and things. For example, the flight simulators used in the training of pilots by airlines and the military recreate the cockpit of an aircraft along with most takeoff, in-flight, and landing conditions. The trainee actually sits in the simulator, moves the rudders, ailerons and throttle, both seeing and feeling the effect of the simulation capsule moving in response to his or her actions. In contrast, much simpler "flight simulators" can be run on a personal computer in the comfort of one's home and can simulate the attitudes of the aircraft on a screen. What one is able to learn from the former flight simulator is very different from

Pacing and performance during simulated rugby league match play depend on an accurate understanding of the exercise endpoint. Applied practitioners should consider informing players of their likely exercise duration to maximize running.

Purpose: To identify the association between several contextual match factors, technical performance, and external movement demands on the subjective task load of elite rugby league players. Methods: Individual subjective task load, quantified using the National Aeronautics and Space Administration Task Load Index (NASA-TLX), was collected from 29 professional rugby league players from one club competing in the European Super League throughout the 2017 season. The sample consisted of 26 matches (441 individual data points). Linear mixed modeling revealed that various combinations of contextual factors, technical performance, and movement demands were associated with subjective task load. Results: Greater number of tackles (effect size correlation ± 90% confidence intervals; η2 = .18 ± .11), errors (η2 = .15 ± .08), decelerations (η2 = .12 ± .08), increased sprint distance (η2 = .13 ± .08), losing matches (η2 = .36 ± .08), and increased perception of effort (η2 = .27 ± .08) led to most likely–very likely increases in subjective total task load. The independent variables included in the final model for subjective mental demand (match outcome, time played, and number of accelerations) were unclear, excluding a likely small correlation with technical errors (η2 = .10 ± .08). Conclusions: These data provide a greater understanding of the subjective task load and their association with several contextual factors, technical performance, and external movement demands during rugby league competition. Practitioners could use this detailed quantification of internal loads to inform recovery sessions and current training practices.