Training Program Design and Performance in the Swedish Hockey League
Differences in training periodization and programming between differently performing elite ice hockey teams
Enea Moretti & Sebastian Byström
Examensarbete för kandidatexamen i idrottsmedicin, 15hp Tränarprogrammet, 180hp Vt 2020
Abstract Introduction/Background Elite ice hockey is a highly physiological demanding team sport of intermittent character and high levels of performance are required over 6-8 months. There are benefits by designing a training program that includes the manipulation of training through its periodization and programming to achieve peak performance at set dates. Purpose The purpose of this study was to determine whether there are differences in training program design between higher- and lower-performing teams in the Swedish Hockey League. Method Four differently performing teams were selected from a performance ranking system. The teams were divided into a higher-performing and lower-performing group. After receiving their verbal approval, an information document and a consent form were digitally sent to the teams’ representatives to obtain their written consent. Subsequently, the teams received a survey consisting of 177 questions that contained single, multiple, ranking and graded-choice questions about their training program design. Intra- and inter-group differences were analyzed with a descriptive statistical calculation of percentage. Results The intra-group analysis revealed a 77,9% difference in the lower-performing team group and 74,5% difference between teams in the higher-performing group. The inter-group difference was found to be 92,7%. The highest amount of inter-group difference (60,5%) was found in questions with no intra-group similarity, whereas 1,1% reveled intra-group different but intra-group similar results. Conclusion This study shows that there are significant differences in training program design between higher- and lower-performing teams as well as significant differences between teams in the lower-performing and higher-performing-group. Some discussed results seem to indicate that higher-performing teams tend to focus more on power, maximal strength and endurance training as well as on its individualization. However, due to the complexity of elite ice hockey, the intra- and inter-group heterogeneity and the shortcomings of the study design, these variables cannot be taken as team key performance indicators.
Key words: Elite ice hockey, key performance indicators, systematic and methodological variables
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Table of Contents
Introduction ...... 1
Background ...... 3 Physiological demands in elite ice hockey ...... 3 Training periodization and programming for athletic performance ...... 4 Training periodization for athletic performance ...... 4 Training programming for athletic performance ...... 6
Method ...... 8 Methodology ...... 8 Performance ranking system ...... 8 Survey ...... 9 Ethics ...... 9 Statistics ...... 9
Results ...... 11
Discussion ...... 13 Methodologic reflection ...... 16 Performance ranking system ...... 16 Choice of teams ...... 16 Survey design ...... 17 Ethical and social reflections ...... 17 Conclusion ...... 18
References ...... 19
Attachment 1 ...... 26
Attachment 2 ...... 28
Attachment 3 ...... 42
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Introduction Elite ice hockey is a highly physically demanding team sport which requires players to have high levels of strength, power, speed, anaerobic capacity and aerobic power in order to be able to repeat bouts of high intensity over a 60-minute-long game (Cox et al., 1995; Roczniok et al., 2016). During a regular season in the Swedish Hockey League (SHL), which lasts for roughly six months, athletes play an average of two games per week for a total of 52 games. For 10 of the 14 teams, the season is followed by a seven week-long playoff-series where the principle of exclusion is applied. Therefore, elite ice hockey players need to keep high levels of performance over a long period and their performance needs to peak at the end of the season, which is consistent with the demands of other team sports (Mujika, 2006). Interestingly though, research on the physiological changes during a season of elite ice hockey has found an opposite trend of physical deconditioning between the beginning and the end of the season in different groups of male elite ice hockey players (Buck, 2013; Cox et al., 1995; Delisle-Houde et al., 2019; Durocher et al., 2008; Green et al., 2010; Green et al., 2012; Laurent et al., 2014). The potential underlying causes behind these results are inadequate physiological stress imposed (too high or too low) (Delisle-Houde et al., 2019; Green et al., 2010), experienced accumulated fatigue (Laurent et al., 2014) and inhibitory influences associated with a prolonged period of intense exercise (Green et al., 2010; Green et al., 2012). Besides the practical applications suggested, strength and conditioning coaches should also take training periodization and programming into serious consideration when trying to create successful training programs (Bompa & Buzzichelli, 2015). Indeed, these are tools used to systematically structure training variables to peak performance (Fleck, 2008; Turner, 2011), minimize the risk of overtraining (Deweese et al., 2015; Plisk & Stone, 2003; Stone et al., 1999), reduce the risk of injury (Naclerio et al., 2013) and reduce the risk of interference effect (Wilson et al., 2012).
Training periodization is the systematic division of training into timeframes (phases) aimed at the development of specific fitness characteristics in order to increase the potential to achieve peak performance at set dates (Fleck, 2008; Matveyev, 1981; Turner, 2011). Training programming is the manipulation of training variables, e.g. density, load, volume and intensity, at a macro- and micro-cyclical level to provide a training stimulus that elicits the desired adaptations (Bompa & Buzzichelli, 2015; Cunanan et al., 2018; Deweese et al., 2015). The order of execution of periodized phases has been shown to matter for physical and performance outcomes (Arroyo -Toledo, 2017; Arroyo -Toledo et al., 2013; D. J. Prestes et al., 2009; Rhea
1 et al., 2003). The management of training variables, if appropriately done, elicits optimal training stimuli while modulating fatigue and optimizing long-term adaptation (Bompa & Buzzichelli, 2015; Cunanan et al., 2018). Hence, both periodization and programming of training may have a direct and indirect impact on performance. Indeed, excessive accumulative fatigue inhibits the physiological adaptation to the training stimuli, produces non-beneficial physiological effects and increases the risk of injury, illness and overtraining (Bowen et al., 2017; Schwellnus et al., 2016; Soligard et al., 2016). Since, player injury rate negatively correlates with team performance in both elite soccer (Eirale et al., 2013; Hägglund et al., 2013) and elite ice hockey (Warnock, 2018), these mentioned factors could potentially prevent a SHL teams’ chance to success.
Until today there is no consensus on one singular way to periodize training for the best training outcomes. However its periodization has been recommended for team sports athletes (Gamble, 2006; Mujika et al., 2018) and meta-analyses have confirmed its efficacy for gains in maximal strength (Williams et al., 2017) and improvements in power (Rhea & Alderman, 2004). Training programming has also been under the loop of researchers where volume and intensity have been suggested as the most important training variables (Bompa & Buzzichelli, 2015). However, few studies about training program design and performance in elite ice hockey were found and, to our knowledge, no previous research has used the methodology of this study.
The purpose of this study was to determine whether there are differences in the training program design between higher and lower performing SHL teams. We hypothesized that there are differences in the training program design between higher and lower performing SHL teams, possibly due to differences in the education level of the respective teams’ coaches. Hopefully, this study could serve as a guideline for other teams’ training program design as well as for future research.
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Background Physiological demands in elite ice hockey
In elite ice hockey, as a team sport with intermittent character, the physical demands are high. One single game contains three periods of 20 minutes each with 18 minutes of rest between periods. Each player plays about 15 high-intensity shifts per game (Nightingale, 2014) and about 30-80 seconds for each shift (Roczniok et al., 2016). According to the official website of the Swedish Hockey League (SHL) (SHL, 2020), stats showed that players have a different amount of ice time and an average between 5-25 minutes depending on which role the player has in the team.
Strength, aerobic power and capacity, anaerobic abilities, power, speed, acceleration, repeated sprint ability (RSA), change of direction (COD) and individual hockey skills are all physical qualities that have been mentioned in the literature to be important for performance in elite ice hockey (Billaut et al., 2012; Burr et al., 2008; Cox et al., 1995; Montgomery, 2000; Nightingale, 2014). Depending on which role the player has, it can be assumed that there is a difference in the energy system utilization. However, metabolic mechanisms (Tortora & Derrickson, 2018) can be essential to take into consideration when designing a training program (Mattsson, 2014). There are various reports on which metabolic system that is the primary energy system utilized during ice hockey. However, most scientists agree that the high-energy phosphate metabolism and the anaerobic glycolysis are the dominating energy systems in elite ice hockey (Bompa & Buzzichelli, 2015; Burr et al., 2008; Montgomery, 2000; Nightingale, 2014). For example, blood lactate samples have been collected during games, ranging between 8.2 mmol/L and 13.7 mmol/L (Noonan, 2010). Hence, these results indicate that the anaerobic energy system requires extensive recovery (Burr et al., 2008). In addition, substantial evidence suggests that an athlete’s aerobic capacity and power have a significant impact on how athletes can recover from intense intermittent sports (Glaister, 2005) and especially according to the lactate metabolism (Bonen, 2001; Gladden, 2004; Pilegaard et al., 1999). Elite ice hockey is a complex sport and coaches have to consider a lot of physical demands as mentioned above. Therefore, the training program design (periodization and programming) for both ice practices and physical training can be assumed to be of great importance in purpose for each player to recover and perform at a high-level.
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Training periodization and programming for athletic performance
In exercise science, the terms of training periodization and programming have often received different definitions and have, therefore, been used in diverse ways (Mujika et al., 2018). The most common definition of training periodization is to systematically and methodically plan training into different phases and cycles to reach peak performance at specific dates (Mattsson, 2014; Matveyev, 1981). Training programming is the act of filling the structured periodization with training variables based on motor abilities to achieve the intended training outcomes (Figure 1) (Afonso et al., 2019; Cunanan et al., 2018; Suchomel et al., 2018). Therefore, the foundations behind periodization lye on the application of systematic variation and on the prediction of training outcomes from different training loads in order to reach peak performance at set dates (Afonso et al., 2019).
Objectives • Evidence-based • Performance optimization Strategies • Fatigue • Phase potentiation management (residual/after • Injury prevention effects) • Phasic • Planned
overreaching • Planned variation • Taper • General-to-specific • Ongoing monitoring Training variables • Frequency Timelines • Density • Lifetime • Volume Periodization • Quadrennial Programming • Intensity • Annual • Exercise mode • Macrocycle • Exercise order • Mesocycle • Sets • Microcycle • Repetitions • Daily • Rest duration
• Recovery mode Fitness-phases • Recovery duration • General preparation
(accumulation) • Specific preparation (transmutation) • Competition/peakin g (realization) • Active rest
Figure 1 - Differences between periodization and programming
Training periodization for athletic performance
The benefits of training periodization regimes have extensively been a subject of research, but its usefulness is still to be determined. According to Afonso et al., 2019, research on training periodization has until today failed to prove that periodized programs are more efficient to non- periodized due to a misconception of what non-periodized varied programs implies. Concepts of periodization and variation are often used as synonyms while they are distinct constructs and, 4 until today, researchers have compared periodized programs vs. constant programs (and not against non-periodized varied programs) (Afonso et al., 2017; Afonso et al., 2019; Kiely, 2012). Indeed, a periodized program is not exclusively based on variation (Kiely, 2012) and a non- periodized program can also be varied (Afonso et al., 2019). Variation in a training program is important, but it should not be used randomly. It should be used in a systematical way to reach peak performance while avoiding overtraining (Fleck, 2008; Turner, 2011). However, meta- analyses have raised the evidence to use periodization in an experienced athletic population for better effects from maximal strength training (Williams et al., 2017) and power training (Rhea & Alderman, 2004). Also, to periodize with a taper for better performances in neuromuscular and metabolic fitness has been suggested for team-sport athletes (Vachon et al., 2020).
To achieve the greatest training outcomes from maximal strength, undulating periodization seems to be more effective compared to traditional periodization (Williams et al., 2017). However, since most studies are of short duration and therefore a higher variability in training load is found in undulating periodization compared to traditional periodization, the authors warn for biased results. Indeed, results on the topic are not uniform (Baker et al., 1994; Harries et al., 2015; Hoffman et al., 2003; Monteiro et al., 2009; Peterson et al., 2008; B. J. Prestes et al., 2009; Rhea et al., 2002; Rhea et al., 2003). Block periodization seems to be more effective compared to traditional periodization when training for performance enhancement in endurance sports (Mølmen et al., 2019), elite ice hockey (Rønnestad et al., 2019) and elite handball (Manchado et al., 2018). Though, since there seems not to be one single periodization model to be superior to others, the fact to apply a range of periodization strategies throughout a long- term training cycle is recommended (Gamble, 2006; Mujika et al., 2018). Also, when working with athletes, coaches should not forget the complexity of a human being and, therefore, the importance of a holistic approach. Attempts to periodize other aspects influencing an athletes’ performance have been made and a recent review raised the available scientific evidence supporting the concept of integrated periodization of multiple factors (Mujika et al., 2018). They suggest that practitioners should take into consideration periodization of recovery, periodization of nutrition and periodization of psychological skill acquisition for improved performance in team sport athletes (Mujika et al., 2018).
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Training programming for athletic performance
When programming, different training variables can be manipulated to produce an appropriate workload and a desired physiological stimulus. For instance, training volume, intensity, frequency, load, effort, exercise selection, exercise order and rest intervals should, among others, be controlled (Figure 1) (Bompa & Buzzichelli, 2015; Haff & Triplett, 2016; Kraemer & Ratamess, 2004). Attempts to isolate these variables to understand its influence on training outcomes have been made. For instance, when training for improvements in maximal strength and hypertrophy gains, as long as the necessary volume is achieved, the most critical variables for each category are respectively training load, exercise specificity and the intensity of effort (Morton et al., 2019). However, training variables are highly intercorrelated and the manipulation of one very often influences at least another variable (Bompa & Buzzichelli, 2015).
In team sport (as elite ice hockey), where it is necessary to maintenance of high levels of performance during a long period of time (Mujika, 2006), proper manipulation of the total training load is required to successfully reach and maintain peak performance (Mujika et al., 2018). Indeed, for a periodized training program to be effective, it should also include a prescription of the appropriate training loads (Bourdon et al., 2017) which should be balanced between external and internal load (Fox et al., 2018). The equilibrium between these represents the dose-response between the training stimulus imposed (external load) and the consequent biomechanical, physical and physiological reaction (internal load) (Akubat et al., 2014; Bartlett et al., 2017). Once prescribed, training load should also be monitored for different purposes such as supervising fatigue, identifying injury risk and determining players’ readiness to perform (Bourdon et al., 2017; McLaren et al., 2018). Indeed, excessive loading can cause maladaptive responses, diminished performance, illness or injury (Hulin et al., 2014). However, small training loads can prevent the desired training adaptations or induce a detraining effect (Bourdon et al., 2017; McLaren et al., 2018). In a recent systematic review on the association between training load and performance outcomes in team sports, coaches were recommended to use internal training load before external load in purpose to predict performance. They also suggest using external load measures such as distance, speed, heart rate and to be cautious when using training load models based on session rate of perceived exertion (sRPE) or training impulse (TRIMP) (Fox et al., 2018).
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In summary, the literature suggests that the short- and long-term selection and manipulation of periodization and training variables will affect training outcomes in team sport athletes. However, whether the manipulation of these automatically affects team performance is not clear. Therefore, since such a process can be complicated and should not be undervalued, coaches have been suggested to understand the process of training to build successful training program designs (Cormack, 2001).
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Method This study was designed with an explorative quantitative approach while the data laid the ground for a descriptive inter- and intra-group analysis.
Methodology All SHL teams that consistently played in the SHL during the 2015/16 - 2019/20 regular seasons were initially included in this study. The included teams were part of a performance ranking system (PRS) that was designed to separate between consistently higher-performing and lower- performing teams. Two teams from the upper half and two teams from the lower half of the PRS were then selected and subsequently divided into respectively the higher-performing (HP) and lower-performing (LP) group.
The selected teams were initially contacted and given verbal information about the purpose and design of the study. Following verbal approval of participation in the study, an information document and an approval form (Attachment 1) were sent to the team’s general manager in order to obtain their written informed consent. Thereafter, each team recommended a representative in their coaching staff who was responsible for the management of the team’s training periodization and programming during both off- and in-season periods. To this person we later addressed the survey. Two identical surveys were created, one for the LP and one for the HP group. Data collection was intra-group blinded and the survey has not been validated prior use. Data were collected in May 2020 and subsequently analyzed using Microsoft Excel (Microsoft Corporation, Redmond, WA, U.S.). To protect the participating teams’ identities, these were coded as Team A and Team B (LP group) and Team C and Team D (HP group).
Performance ranking system In order to quantify team performance in the SHL, a performing ranking system (PRS) was made. The PRS took into account the team performance throughout the last five regular seasons (2015/16-2019/20) and the previous four playoff series (2015/16-2018/19). Points were given according to the team’s position at the end of each included regular seasons and upon performance during each included playoff series according to the following system: Regular season - 1st place = 1 point, 2nd place = 2 points, 3rd place = 3 points etc. and Play-off series - 1st place = 0 points, final = 1 point, semifinal = 2 points, quarterfinal = 3 points, play-in = 4 points, 11-12th place = 5 points, 13th place = 6 points. Thus, the PRS ranks the teams in reverse
8 order where the team with the lowest number of points is ranked first and the team with the highest number of points is ranked last.
Survey The survey (Attachment 2) was designed through WebSurvey (Textalk AB; Mölndal, Sweden) and was written in the Swedish language to facilitate the respondents. It included 177 questions, which were divided into 32 different categories and were structured with single, multiple, binary, graded and ranking-choice questions. These were designed to receive information about the team’s regular training periodization, training programming, communication density and educational level during the last three-to-five seasons. The survey contained an introductive paragraph where the respondents were informed about different terminologies as in-season as well as off-season and where they were asked to answer sincerely.
Ethics Each team received an information document and a consent form (Attachment 1) where information about the risks of the study, use of personal data, use of study results and confidentiality were given. They were also informed that participation was voluntary and could be ended whenever it was necessary without giving explications. The participating teams were offered to receive the final study results. If these terms of conditions were accepted, teams gave their written informed consent. The data is stored on an encrypted USB memory stick and will be deleted two years after the publication of this study. All data has been processed according to GDPR. The study was conducted in accordance with the guidelines described in the Declaration of Helsinki (Ethical Principles for Medical Research Involving Human Subjects, 2014).
Statistics Intra and inter-group analysis were conducted through a descriptive statistical calculation of percentage based upon the number of similar results found. These were the possible outcomes: - Intra-group similarity (IGS) was achieved when two teams from the same group gave identical answers. All answers which were not considered as intra-group similarities were instead regarded as intra-group differences (IGD). - Inter-group similarity was achieved when all four teams gave the exact same answer. - Inter-group difference with zero intra-group similarity (IGD-0) was achieved when there was no intra-group similarity in either group.
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- Inter-group difference with one intra-group similarity (IGD-1) was achieved when only one of the two groups achieved intra-group similarity. - Inter-group difference with two intra-group similarities (IGD-2) was achieved when both groups achieved intra-group similarity, but the answers differed between the groups.
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Results The survey provided 177 answers per team and 354 answers per group with a total of 708 answers which are presented in Attachment 3. In the LP group there was an intra-group difference of 77,9% whereas in the HP group the intra-group difference was 74,5%. When comparing the two groups against each other, the overall inter-group difference was found to be 92,7% while the inter-group similarity was 7,3%. The most significant amount of the inter- group difference was found in questions where there was no intra-group similarity in either LP or HP groups (60,5%) and in questions where there only was one intra-group similarity (31,1%). Only two out of 177 questions (1,1%) showed an intra-group difference where both groups answered intra-group similarly (Table 1).
Table 1 – Inter-group summary
Inter-group summary Number of questions Percentage Inter-group difference with zero intra-group similarity (IGD-0) 107 60,5% Inter-group difference with one intra-group similarity (IGD-1) 55 31,1% Inter-group difference with two intra-group similarities (IGD-2) 2 1,1% Inter-group similarity (IGS) 13 7,3% Total 177 100%
Examples of inter-group analysis can be found in Table 2. For instance, in Q32, LP Team A answered to perform three, LP Team B five, HP Team C four and HP Team D two strength training sessions per week during their in-season which undergoes category IGD-0. A sample for IGD-1 was found in Q33 where LP Team A, HP Team C and HP Team D respectively performed zero, one and one endurance trainings a week during the in-season and where LP Team B does not know. Other examples for IGD-1 are that HP teams distribute 40% PT volume during the pre-season whereas LP teams distribute 20% or do not know and HP teams distributes 50-60% PT volume during the in-season whereas LP teams distribute 40% PT (Q100; Q117). In IGD-2, Q71 was included where LP teams answered to perform rehabilitation training before 12 o’clock whereas HP teams answered to execute rehabilitation training after 12 o’clock. An IGS was found in Q156 where all teams indicated to perform more than twice a week on-ice small area games.
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Table 2 – Examples of inter-group analysis
IGD-0 LP Team A LP Team B HP Team C HP Team D How is the distribution between these training forms during an average training week in your in-season? (number of sessions) Q32 Strength training 3 5 4 2 IGD-1 How is the distribution between these training forms during an average training week in your in-season? (number of sessions)
Q33 Endurance training 0 Do not know 1 1 How does the volume distribution between these different forms of physical training look like during your pre-season? Q100 Power training 20% Do not know 40% 40% What is the volume distribution between these different types of training during your in-season? Q117 Power training 40% 40% 60% 50% IGD-2 If you perform the following training forms, when during the day do you place them? Q71 Rehabilitation Before 12:00 Before 12:00 After 12:00 After 12:00 IGS During a regular training week in the middle of the in-season, how often do you practice specific endurance training? Q156 Small area games (ON-ICE) > 2gg x week > 2gg x week > 2gg x week > 2gg x week
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Discussion The purpose of this study was to determine whether there are differences in the training program design between differently performing SHL teams. The results showed an inter-group difference of 92,7%, intra-group difference of 77,9% for the LP group and 74,5% for the HP group. A more in-depth analysis found 60,5% of the inter-group differences in questions where there was no intra-group similarity in either LP or HP groups (Table 1).
Due to the heterogeneity in the results and to the small sample size, analysis between groups and determination of variables for team performance were found to be challenging. These findings suggest the complexity of success in elite ice hockey and the complexity of training periodization and programming for team performance enhancement. Indeed, performance in elite ice hockey and other team sports have been shown to be affected by several different factors as franchise economy (Downward, 2000), team cohesion (Beauchamp & Eys, 2014) and player injury rate (Eirale et al., 2013; Hägglund et al., 2013; Warnock, 2018). These factors make the analysis of team key performance indicators (KPI) in elite ice hockey even more challenging. However, it can be discussed whether the found tendencies towards differences in some training program design variables potentially could have an impact on team performance in the SHL.
One of these variables has been found in the volume distribution of power training (PT) where the results showed tendencies toward HP teams to program their pre- and in-season physical training with a higher volume in PT compared to the LP teams (Fel! Hittar inte referenskälla., Q100, Q117). The definition of muscular power is that a higher power is developed when the given resistance (e.g., body mass) is moved at a higher rate (Kenney, 2015). Muscular peak power output has extensively been identified as a key factor for athletic performance in sports (Cormie et al., 2011; Haff et al., 2001; Kraemer & Newton, 2000) and in elite ice hockey (Bracko & George, 2001; Burr et al., 2008; Cox et al., 1995; Mascaro et al., 1992; Roczniok et al., 2016; Twist & Rhodes, 1993). Also, contrast training has been shown to generate Post- Activation Potentiation and to improve on-ice RSA (Lagrange et al., 2020) and skating speed ability (Lee et al., 2014) in elite ice hockey players. Therefore, it could be discussed whether HP teams may have an advantage in physical performance since they tend to perform more PT throughout the whole season. However, PT alone may not automatically result in increased
13 athlete performance and to increase the potential to generate peak power output, other physiological capacities as maximal force and velocity are required (Hill, 1938; Katz, 1939).
The HP teams also seem to give more importance to volume and frequency of maximal strength training (MST) compared to the LP teams (Fel! Hittar inte referenskälla., Q106, Q123, Q133). There is a reversed relationship between force and velocity according to the Force- Velocity-Relationship (Hill, 1938; Katz, 1939). Some benefits with MST are a higher motor unit recruitment, a better intra and inter muscular synchronization and the development of muscle fiber types which may be conducive to the intended stimuli (Bompa & Buzzichelli, 2015; Howard et al., 1985; Kenney, 2015). These raise the potential to generate peak power output (Baker, 2001; Stone et al., 2002), which, as aforementioned, seems important for athletic performance in elite ice hockey (Burr et al., 2008). Due to the length of the regular season and to the benefits of MST, it can be hypothesized whether HP team athletes could have the potential to generate higher peak power output and therefore improve their performance. However, since we have not measured the athletes’ physical capacities, only assumptions can be made.
According to endurance training (ET), we found HP teams to execute more ET volume during the in-season compared to LP teams. Specifically, HP teams consistently perform one specific ET per week during the in-season whereas LP teams seem not to do so (or “do not know”) (Fel! Hittar inte referenskälla., Q33). Also, HP teams perform more than twice a week short interval training (20-60 seconds), a training method that has been found to be effective for elite ice hockey (Naimo et al., 2015), whereas LP teams do it once a week or less (Fel! Hittar inte referenskälla., Q158). Elite ice hockey players have been encouraged to improve skating speed particularly in the context of multiple repetitions of actions (Stanula et al., 2014; Szmatlan- Gabrys et al., 2006) as well as to prioritize high-intensity intermittent training and speed endurance training (Lignell et al., 2018) during both pre- and in-season (Durocher et al., 2008). To raise the potential of these capacities, elite ice hockey players need a well-developed aerobic energy system which is of importance (Glaister, 2005; Lignell et al., 2018; Peterson et al., 2015; Roczniok et al., 2016; Stanula et al., 2014). However, numerous studies have found a discrepancy in intensity and physical demands between average ice practices and game situations (Spiering et al., 2003; Stanula & Roczniok, 2014). Therefore, it can be questioned whether LP teams’ athletes do receive enough physiological stimulus to maintain (or develop) their aerobic fitness during the in-season through their ice-practices and games only. It can be
14 speculated whether a physical deconditioning of their aerobic fitness level may occur during the in-season which has repeatedly been found in previous research (Buck, 2013; Cox et al., 1995; Delisle-Houde et al., 2019; Durocher et al., 2008; Green et al., 2010; Green et al., 2012; Laurent et al., 2014). Interestingly, to prevent this physiological maladaptation, strength and conditioning coaches have been suggested to be aware of the importance of the players’ off-ice physical training especially during the second half of the in-season (Delisle-Houde et al., 2019). During that period, most ice practice time seems to be spent on team tactics and the physical training is decreased (Delisle-Houde et al., 2019). Indeed, the results show that LP teams give less emphasis on the off-ice preparation as the in-season proceeds whereas HP teams are consistent in their volume distribution between ice-practice and off-ice training through the whole in-season (Fel! Hittar inte referenskälla., Q167-169). However, these results cannot determine how teams distribute their time on ice practice between team tactics and physical qualities. To summarize, HP teams seem to perform more ET during the in-season and to give constant importance to the off-ice physical training which can be assumed to be an advantage.
There also seems to be tendencies toward relevant differences in the individualization of ice practices between HP and LP teams. The HP teams individualize their ice practices respectively 80% and 40% whereas LP teams have 20% of their ice practices individualized (Fel! Hittar inte referenskälla., Q59). These answers indicate how much of the ice practices that are with an individual focus, probably to a specific moment of the game. Individualization can be related to 1) The principle of specialization which is described as "you should practice what you want to be good at" and can be explained through the difference in adaptation to a specific stimulus. 2) The principle of individualization arguments that “each individual needs to practice for what they need” when there are differences between each individual, genes and interests (Mattsson, 2014). To specialize in training, it may be worth considering revising the physical demands of elite ice hockey during matches which includes intensity, duration, movement pattern, velocity and equipment etc. (Mattsson, 2014). It could be speculated and discussed whether HP teams have an advantage since their ice practices seem to be more individualized and their players may have an increase in specific ice hockey performance.
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Methodologic reflection
The validity of the surveys’ results can be discussed upon serval factors as the performance ranking system, choice of teams, survey design and respondents’ educational level.
Performance ranking system
In elite ice hockey, attempts to define players’ KPI have been made (Swarén et al., 2018) and KPI have been recommended to manipulate training variables (Donskov, 2020). However, according to the literature, no attempts to identify team KPI have been made in elite ice hockey. Until today, that has been done in other team sports as elite soccer (Lago Ballesteros & Peñas, 2010). Therefore, we felt free to propose our definition of team performance in the SHL through the PRS used in this study. Our PRS was controlled with a different methodological ranking system and the final standing was identical. Therefore, we felt confident enough to use the PRS of this study; however, since it is not based on previous research, we are aware of its limitations. For instance, the PRS does not consider other potential performance variables as team points, +/- statistics and goal chances, which can be discussed whether these among others should have been included. One issue with our PRS was that it was limited to five years and it can be discussed whether other time-lapses could have been more appropriate. We chose five years because we wanted to limit ourselves to an elite ice hockey that is considered more modern and avoid as much recall bias as possible. To facilitate similar research on the interaction between different training variables and team performance, future research on the identification of team sports KPI is needed.
Choice of teams
To elevate our chances to find inter-group differences in training periodization and programming variables, our goal was to select two groups of teams with the most significant inter-group difference in PRS. However, it can be discussed whether there would have been a more appropriate way of selecting teams to avoid confounding, for instance, by making a simple randomized selection where we would have blindly chosen two teams from each upper and lower half of the PRS. A possible risk by making a simple randomized selection could have been that the minimal needed difference in PRS-points between teams, to find a variance in the studied variables, may not have been achieved.
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Survey design
The survey used for this study was built with an explorative quantitative approach and has been presented descriptively. We introduced the survey by informing the respondents to aim at a mean from the last three-to-five seasons. This lapse of time raises the risk of recall bias since the respondents may have had problems remembering the training program designs over previous seasons. Another issue with our survey was the questions and the given answer alternatives. As earlier mentioned, the survey was not validated prior use and therefore, we could not entirely rely on its’ quality and usefulness. Indeed, we found several errors in our results. For instance, some answers exceed 100% (Fel! Hittar inte referenskälla., Q122-128, Q115-121). To avoid this, we could have written questions with more precise information and give alternative answers with more adaptable different percentages. Also, we found teams not being able to answer our questions as it can be seen in Fel! Hittar inte referenskälla. (Q98- 111) where Team B answers “do not know” on all possible variables, which made the data analysis difficult. Last but not least, it can be discussed whether the alternative answers we proposed were adequate to give the respondents enough freedom to answer what best suited them. For instance, some alternative answers did not cover the whole spectra of possible answers and, therefore, respondents may have been pushed to answer to something else compared to reality.
Three out of four respondents have at least a bachelor’s degree in the field of sports science (Attachment 3, Q2). This may indicate that most teams are familiar with the topic, which strengthens the validity of our results. However, the level of education alone does not form the basis for how skilled a coach is, rather aspects such as experience also have a significant impact on the coaches' ability to implement and evaluate training (Cushion et al., 2003). Questions about the respondents’ coaching experience in the field could have helped to receive even more valid data. However, since this information could have caused the identification and, therefore, ethical problems, we chose to refrain from asking these questions.
Ethical and social reflections The possible risks associated with this study were discussed as well as evaluated and the biggest concern was the identification of teams. However, since data was coded, it significantly lowered this risk. Because of the small sample size and the shortcomings in the study design, findings
17 and conclusions from this study cannot be generalizable for all Swedish elite ice hockey. More studies are needed in the field to find team KPI in for elite ice hockey. Conclusion This study shows that there are significant differences in training program design between higher- and lower-performing teams as well as significant differences between teams in the lower-performing-group and higher-performing-group. Some discussed results seem to indicate that HP teams tend to focus more on power, maximal strength, endurance and individualization training in certain periods of their training program. Because of the significant intra- and inter- group heterogeneity, the shortcomings of the study design, the lack of statistical analysis and the inconsistent answers, it cannot be concluded whether these systematical and methodological variables indicate the difference in team performance. Furthermore, since team performance in elite ice hockey is affected by a complexity of factors as players’ physical demands, economics and team cohesion among others, it is even more challenging to find reliable team key performance indicators. However, one benefit of this study is the confirmation of the importance of training periodization and the systematic manipulation of training variables in elite ice hockey. Also, this study can be used as a guideline for future research on the topic since, to our knowledge, no previous studies has used this methodology. For future research we suggest that a similar method with a prospective approach is used where data is collected every month for two-to-three years since it could help to lower the risk for recall bias and reach closer to elite sports reality.
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References Afonso, J., Nikolaidis, P. T., Sousa, P., & Mesquita, I. (2017). Is Empirical Research on Periodization Trustworthy? A Comprehensive Review of Conceptual and Methodological Issues. Journal of Sports Science and Medicine, 16(1), 27-34. Afonso, J., Rocha, T., Nikolaidis, P. T., Clemente, F. M., Rosemann, T., & Knechtle, B. (2019). A Systematic Review of Meta-Analyses Comparing Periodized and Non- periodized Exercise Programs: Why We Should Go Back to Original Research. Frontiers in Physiology, 10. https://doi.org/10.3389/fphys.2019.01023 Akubat, I., Barrett, S., & Abt, G. (2014). Integrating the internal and external training loads in soccer. International journal of sports physiology and performance, 9(3), 457. https://doi.org/10.1123/ijspp.2012-0347 Arroyo -Toledo, J. (2017). Concentrated Load on A Reverse Periodization, Propel Higher Positives Effects to Track Test Performance, than Traditional Sequence. "Imperial Journal of Interdisciplinary Research (IJIR), 3, 470-476. Arroyo -Toledo, J., Clemente-Suárez, V., & Gonzalez Rave, J. M. (2013). The effects of ten weeks block and reverse periodization training on swimming performance and body composition of moderately trained female swimmers. Journal of Swimming Research, 21. Baker, D. (2001). Acute and long-term power responses to power training: Observations on the training of an elite power athlete. Strength & Conditioning Journal, 23(1), 47-56. Baker, D., Wilson, G., & Carlyon, R. (1994). Periodization: The Effect on Strength of Manipulating Volume and Intensity. Journal of Strength and Conditioning Research, 8(4), 235-242. https://doi.org/10.1519/00124278-199411000-00006 Bartlett, J. D., O'Connor, F., Pitchford, N., Torres-Ronda, L., & Robertson, S. J. (2017). Relationships Between Internal and External Training Load in Team-Sport Athletes: Evidence for an Individualized Approach. International journal of sports physiology and performance, 12(2), 230. https://doi.org/10.1123/ijspp.2015-0791 Beauchamp, M. R., & Eys, M. A. (2014). Group dynamics in exercise and sport psychology. Billaut, F., Gore, C. J., & Aughey, R. J. (2012). Enhancing team-sport athlete performance. Sports medicine, 42(9), 751-767. Bompa, T. O., & Buzzichelli, C. (2015). Periodization training for sports. Human Kinetics. Bonen, A. (2001). The expression of lactate transporters (MCT1 and MCT4) in heart and muscle. European journal of applied physiology, 86(1), 6-11. Bourdon, P. C., Cardinale, M., Murray, A., Gastin, P., Kellmann, M., Varley, M. C., Gabbett, T. J., Coutts, A. J., Burgess, D. J., Gregson, W., & Cable, N. T. (2017). Monitoring Athlete Training Loads: Consensus Statement. International journal of sports physiology and performance, 12(Suppl 2), S2161. https://doi.org/10.1123/IJSPP.2017- 0208 Bowen, L., Gross, A. S., Gimpel, M., & Li, F.-X. (2017). Accumulated workloads and the acute:chronic workload ratio relate to injury risk in elite youth football players. British Journal of Sports Medicine, 51(5), 452. https://doi.org/10.1136/bjsports-2015-095820 Bracko, R. M., & George, D. J. (2001). Prediction of Ice Skating Performance With OffIce Testing in Womenʼs Ice Hockey Players. Journal of Strength and Conditioning Research, 15(1), 116-122. https://doi.org/10.1519/1533- 4287(2001)015<0116:POISPW>2.0.CO;2 Buck, D. (2013). Seasonal changes in various performance measurements in ice-hockey players (Publication Number 2013:63) [Student thesis, DiVA. http://urn.kb.se/resolve?urn=urn:nbn:se:gih:diva-3098
19
Burr, J. F., Jamnik, R. K., Baker, J., Macpherson, A., Gledhill, N., & McGuire, E. (2008). Relationship of physical fitness test results and hockey playing potential in elite-level ice hockey players. The Journal of Strength & Conditioning Research, 22(5), 1535- 1543. Cormack, S. (2001). The effect of regular travel on periodisation. Strength and Conditioning Coach, 9, 19-24. Cormie, P., McGuigan, M., & Newton, R. (2011). Developing Maximal Neuromuscular Power. Sports Medicine, 41(1), 17-38. https://doi.org/10.2165/11537690-000000000- 00000 Cox, M. H., Miles, D. S., Verde, T. J., & Rhodes, E. C. (1995). Applied physiology of ice hockey. Sports medicine (Auckland, N.Z.), 19(3), 184. https://doi.org/10.2165/00007256-199519030-00004 Cunanan, A., DeWeese, B., Wagle, J., Carroll, K., Sausaman, R., Hornsby, W., Haff, G., Triplett, N., Pierce, K., & Stone, M. (2018). The General Adaptation Syndrome: A Foundation for the Concept of Periodization. Sports Medicine, 48(4), 787-797. https://doi.org/10.1007/s40279-017-0855-3 Cushion, C. J., Armour, K. M., & Jones, R. L. (2003). Coach Education and Continuing Professional Development: Experience and Learning to Coach. Quest, 55(3), 215-230. https://doi.org/10.1080/00336297.2003.10491800 Delisle-Houde, E. R. P., Reid, A. R., Insogna, A. J., Chiarlitti, E. N., & Andersen, E. R. (2019). Seasonal Changes in Physiological Responses and Body Composition During a Competitive Season in Male and Female Elite Collegiate Ice Hockey Players. Journal of Strength and Conditioning Research, 33(8), 2162-2169. https://doi.org/10.1519/JSC.0000000000002338 Deweese, B. H., Hornsby, G., Stone, M., & Stone, M. H. (2015). The training process: Planning for strength–power training in track and field. Part 1: Theoretical aspects. Journal of Sport and Health Science, 4(4), 308-317. https://doi.org/10.1016/j.jshs.2015.07.003 Donskov, A. (2020). The Gain, Go, Grow Manual: Programming for High Performance Hockey Players. AuthorHouse. Downward, P. (2000). The economics of professional team sports. Durocher, J. J., Leetun, D. T., & Carter, J. R. (2008). Sport-specific assessment of lactate threshold and aerobic capacity throughout a collegiate hockey season. Applied Physiology, Nutrition, and Metabolism, 33(6), 1165-1171. https://doi.org/10.1139/H08-107 Eirale, C., Tol, J. L., Farooq, A., Smiley, F., & Chalabi, H. (2013). Low injury rate strongly correlates with team success in Qatari professional football. British Journal of Sports Medicine, 47(12), 807. https://doi.org/10.1136/bjsports-2012-091040 Fleck, S. J. (2008). Periodization of Training. Wiley Blackwell. https://doi.org/10.1002/9780470698754.ch4 Fox, J., Stanton, R., Sargent, C., Wintour, S.-A., & Scanlan, A. (2018). The Association Between Training Load and Performance in Team Sports: A Systematic Review. Sports Medicine, 48(12), 2743-2774. https://doi.org/10.1007/s40279-018-0982-5 Gamble, P. (2006). Periodization of Training for Team Sports Athletes. Strength and Conditioning Journal, 28(5), 56-66. https://doi.org/10.1519/00126548-200610000- 00009 Gladden, L. (2004). Lactate metabolism: a new paradigm for the third millennium. The Journal of physiology, 558(1), 5-30. Glaister, M. (2005). Multiple sprint work. Sports medicine, 35(9), 757-777.
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Green, H. J., Batada, A., Cole, B., Burnett, M. E., Kollias, H., McKay, S., Roy, B., Schertzer, J., Smith, I., & Tupling, S. (2010). Cellular responses in skeletal muscle to a season of ice hockey. Applied Physiology, Nutrition, and Metabolism, 35(5), 657-670. https://doi.org/10.1139/H10-060 Green, H. J., Batada, A., Cole, B., Burnett, M. E., Kollias, H., McKay, S., Roy, B., Schertzer, J. D., Smith, I. C., & Tupling, S. (2012). Muscle cellular properties in the ice hockey player: a model for investigating overtraining? Canadian Journal of Physiology and Pharmacology, 90(5), 567-578. https://doi.org/10.1139/y2012-017 Haff, G., & Triplett, N. T. (2016). Essentials of strength training and conditioning. Human Kinetics. Haff, G. G., Whitley, A., & Potteiger, J. A. (2001). A Brief Review: Explosive Exercises and Sports Performance. Strength and Conditioning Journal, 23(3), 38-38. https://doi.org/10.1519/1533-4295(2001)0232.0.CO;2 Harries, K. S., Lubans, R. D., & Callister, R. R. (2015). Systematic Review and Meta-analysis of Linear and Undulating Periodized Resistance Training Programs on Muscular Strength. Journal of Strength and Conditioning Research, 29(4), 1113-1125. https://doi.org/10.1519/JSC.0000000000000712 Hill, A. V. (1938). The heat of shortening and the dynamic constants of muscle. Proceedings of the Royal Society of London. Series B-Biological Sciences, 126(843), 136-195. Hoffman, R. J., Wendell, R. M., Cooper, R. J., & Kang, R. J. (2003). Comparison Between Linear and Nonlinear In-Season Training Programs in Freshman Football Players. Journal of Strength and Conditioning Research, 17(3), 561-565. https://doi.org/10.1519/1533-4287(2003)017<0561:CBLANI>2.0.CO;2 Howard, J., Ritchie, M., Gater, D., Gater, D., & Enoka, R. (1985). Roundtable: Determining factors of strengthPhysiological Foundations. Strength & Conditioning Journal, 7(6), 16-22. Hulin, B. T., Gabbett, T. J., Blanch, P., Chapman, P., Bailey, D., & Orchard, J. W. (2014). Spikes in acute workload are associated with increased injury risk in elite cricket fast bowlers. British Journal of Sports Medicine, 48(8), 708. https://doi.org/10.1136/bjsports-2013-092524 Hägglund, M., Waldén, M., Magnusson, H., Kristenson, K., Bengtsson, H., & Ekstrand, J. (2013). Injuries affect team performance negatively in professional football: an 11- year follow-up of the UEFA Champions League injury study. British Journal of Sports Medicine, 47(12), 738. https://doi.org/10.1136/bjsports-2013-092215 Katz, B. (1939). The relation between force and speed in muscular contraction. The Journal of Physiology, 96(1), 45-64. Kenney, W. L. (2015). Physiology of sport and exercise. Kiely, J. (2012). Periodization paradigms in the 21st century: evidence-led or tradition- driven? International journal of sports physiology and performance, 7(3), 242. https://doi.org/10.1123/ijspp.7.3.242 Kraemer, J. W., & Ratamess, A. N. (2004). Fundamentals of Resistance Training: Progression and Exercise Prescription. Medicine & Science in Sports & Exercise, 36(4), 674-688. https://doi.org/10.1249/01.MSS.0000121945.36635.61 Kraemer, W. J., & Newton, R. U. (2000). Training for Muscular Power. Physical Medicine & Rehabilitation Clinics of North America, 11(2), 341-368. https://doi.org/10.1016/S1047-9651(18)30133-5 Lago Ballesteros, J., & Peñas, C. (2010). Performance in Team Sports: Identifying the Keys to Success in Soccer. Journal of Human Kinetics, 25. https://doi.org/10.2478/v10078- 010-0035-0
21
Lagrange, S., Ferland, P.-M., Leone, M., & Comtois, A. S. (2020). Contrast Training Generates Post-Activation Potentiation and Improves Repeated Sprint Ability in Elite Ice Hockey Players. International journal of exercise science, 13(6), 183. Laurent, M. C., Fullenkamp, M. A., Morgan, L. A., & Fischer, A. D. (2014). Power, Fatigue, and Recovery Changes in National Collegiate Athletic Association Division I Hockey Players Across a Competitive Season. Journal of Strength and Conditioning Research, 28(12), 3338-3345. https://doi.org/10.1519/JSC.0000000000000554 Lee, C., Lee, S., & Yoo, J. (2014). The effect of a complex training program on skating abilities in ice hockey players. Journal of physical therapy science, 26(4), 533. https://doi.org/10.1589/jpts.26.533 Lignell, E., Fransson, D., Krustrup, P., & Mohr, M. (2018). Analysis of High-Intensity Skating in Top-Class Ice Hockey Match-Play in Relation to Training Status and Muscle Damage. Journal of Strength and Conditioning Research, 32(5), 1303-1310. https://doi.org/10.1519/JSC.0000000000001999 Manchado, M. C., Cortell-Tormo, M. J., & Tortosa-Martínez, M. J. (2018). Effects of Two Different Training Periodization Models on Physical and Physiological Aspects of Elite Female Team Handball Players. Journal of Strength and Conditioning Research, 32(1), 280-287. https://doi.org/10.1519/JSC.0000000000002259 Mascaro, T., Seaver, B. L., & Swanson, L. (1992). Prediction of skating speed with off-ice testing in professional hockey players. The Journal of orthopaedic and sports physical therapy, 15(2), 92. https://doi.org/10.2519/jospt.1992.15.2.92 Mattsson, C. M. (2014). Träningsplanering. SISU idrottsböcker. Matveyev, L. (1981). Fundamentals of sports training. Progress Publishers. McLaren, S., Macpherson, T., Coutts, A., Hurst, C., Spears, I., & Weston, M. (2018). The Relationships Between Internal and External Measures of Training Load and Intensity in Team Sports: A Meta-Analysis. Sports Medicine, 48(3), 641-658. https://doi.org/10.1007/s40279-017-0830-z Monteiro, G. A., Aoki, S. M., Evangelista, L. A., Alveno, A. D., Monteiro, A. G., Piçarro, D. C. I., & Ugrinowitsch, D. C. C. (2009). Nonlinear Periodization Maximizes Strength Gains in Split Resistance Training Routines. Journal of Strength and Conditioning Research, 23(4), 1321-1326. https://doi.org/10.1519/JSC.0b013e3181a00f96 [Record #10 is using a reference type undefined in this output style.] Morton, R. W., Colenso-Semple, L., & Phillips, S. M. (2019). Training for strength and hypertrophy: an evidence-based approach. Current Opinion in Physiology, 10, 90-95. https://doi.org/10.1016/j.cophys.2019.04.006 Mujika, I. (2006). Thoughts and Considerations for TEAM-SPORT PEAKING. Olympic Coach, 18(4), 9-9. Mujika, I., Halson, S., Burke, L. M., Balagué, G., & Farrow, D. (2018). An Integrated, Multifactorial Approach to Periodization for Optimal Performance in Individual and Team Sports. International journal of sports physiology and performance, 13(5), 538. https://doi.org/10.1123/ijspp.2018-0093 Mølmen, K. S., Øfsteng, S. J., & Rønnestad, B. (2019). Block periodization of endurance training - a systematic review and meta-analysis. Open Access Journal of Sports Medicine, 10, 145-160. Naclerio, D. F., Faigenbaum, A. A., Larumbe-Zabala, T. E., Perez-Bibao, T. T., Kang, T. J., Ratamess, T. N., & Triplett, T. N. (2013). Effects of Different Resistance Training Volumes on Strength and Power in Team Sport Athletes. Journal of Strength and Conditioning Research, 27(7), 1832-1840. https://doi.org/10.1519/JSC.0b013e3182736d10
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Naimo, M., De Souza, E., Wilson, J., Carpenter, A., Gilchrist, P., Lowery, R., Averbuch, B., White, T., & Joy, J. (2015). High-intensity interval training has positive effects on performance in ice hockey players. International journal of sports medicine, 36(01), 61-66. Nightingale, S. C. (2014). A strength and conditioning approach for ice hockey. Strength & Conditioning Journal, 36(6), 28-36. Noonan, B. C. (2010). Intragame blood-lactate values during ice hockey and their relationships to commonly used hockey testing protocols. The Journal of Strength & Conditioning Research, 24(9), 2290-2295. Peterson, D. M., Dodd, J. D., Alvar, A. B., Rhea, R. M., & Favre, R. M. (2008). Undulation Training for Development of Hierarchical Fitness and Improved Firefighter Job Performance. Journal of Strength and Conditioning Research, 22(5), 1683-1695. https://doi.org/10.1519/JSC.0b013e31818215f4 Peterson, J. B., Fitzgerald, S. J., Dietz, C. C., Ziegler, S. K., Ingraham, J. S., Baker, E. S., & Snyder, M. E. (2015). Aerobic Capacity Is Associated With Improved Repeated Shift Performance in Hockey. Journal of Strength and Conditioning Research, 29(6), 1465- 1472. https://doi.org/10.1519/JSC.0000000000000786 Pilegaard, H., Terzis, G., Halestrap, A., & Juel, C. (1999). Distribution of the lactate/H+ transporter isoforms MCT1 and MCT4 in human skeletal muscle. American Journal of Physiology-Endocrinology And Metabolism, 276(5), E843-E848. Plisk, S. S., & Stone, H. M. (2003). Periodization Strategies. Strength and Conditioning Journal, 25(6), 19-37. https://doi.org/10.1519/00126548-200312000-00005 Prestes, B. J., Frollini, F. A., De Lima, J. C., Donatto, J. F., Foschini, J. D., De Cássia Marqueti, J. R., Figueira, J. A., & Fleck, J. S. (2009). Comparison Between Linear and Daily Undulating Periodized Resistance Training to Increase Strength. Journal of Strength and Conditioning Research, 23(9), 2437-2442. https://doi.org/10.1519/JSC.0b013e3181c03548 Prestes, D. J., Lima, B. C., Frollini, F. A., Donatto, F. F., & Conte, F. M. (2009). Comparison of Linear and Reverse Linear Periodization Effects on Maximal Strength and Body Composition. Journal of Strength and Conditioning Research, 23(1), 266-274. https://doi.org/10.1519/JSC.0b013e3181874bf3 Rhea, M. R., & Alderman, B. L. (2004). A Meta-Analysis of Periodized versus Nonperiodized Strength and Power Training Programs. Research Quarterly for Exercise and Sport, 75(4), 413-422. https://doi.org/10.1080/02701367.2004.10609174 Rhea, R. M., Ball, D. S., Phillips, T. W., & Burkett, N. L. (2002). A Comparison of Linear and Daily Undulating Periodized Programs with Equated Volume and Intensity for Strength. Journal of Strength and Conditioning Research, 16(2), 250-255. https://doi.org/10.1519/00124278-200205000-00013 Rhea, R. M., Phillips, T. W., Burkett, N. L., Stone, J. W., Ball, D. S., Alvar, A. B., & Thomas, B. A. (2003). A Comparison of Linear and Daily Undulating Periodized Programs With Equated Volume and Intensity for Local Muscular Endurance. Journal of Strength and Conditioning Research, 17(1), 82-87. https://doi.org/10.1519/00124278- 200302000-00014 Roczniok, R., Stanula, A., Maszczyk, A., Mostowik, A., Kowalczyk, M., Fidos-Czuba, O., & Zając, A. (2016). Physiological, physical and on-ice performance criteria for selection of elite ice hockey teams. Biology of sport, 33(1), 43. Rønnestad, B. R., Øfsteng, S. J., & Ellefsen, S. (2019). Block periodization of strength and endurance training is superior to traditional periodization in ice hockey players. Scandinavian journal of medicine & science in sports, 29(2), 180. https://doi.org/10.1111/sms.13326
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Schwellnus, M., Soligard, T., Alonso, J.-M., Bahr, R., Clarsen, B., Dijkstra, H. P., Gabbett, T. J., Gleeson, M., Hägglund, M., Hutchinson, M. R., Janse Van Rensburg, C., Meeusen, R., Orchard, J. W., Pluim, B. M., Raftery, M., Budgett, R., & Engebretsen, L. (2016). How much is too much? (Part 2) International Olympic Committee consensus statement on load in sport and risk of illness. British Journal of Sports Medicine, 50(17), 1043. https://doi.org/10.1136/bjsports-2016-096572 Soligard, T., Schwellnus, M., Alonso, J.-M., Bahr, R., Clarsen, B., Dijkstra, H. P., Gabbett, T., Gleeson, M., Hägglund, M., Hutchinson, M. R., Janse van Rensburg, C., Khan, K. M., Meeusen, R., Orchard, J. W., Pluim, B. M., Raftery, M., Budgett, R., & Engebretsen, L. (2016). How much is too much? (Part 1) International Olympic Committee consensus statement on load in sport and risk of injury. British Journal of Sports Medicine, 50(17), 1030. https://doi.org/10.1136/bjsports-2016-096581 Spiering, A. B., Wilson, H. M., Judelson, A. D., & Rundell, W. K. (2003). Evaluation of Cardiovascular Demands of Game Play and Practice in Womenʼs Ice Hockey. Journal of Strength and Conditioning Research, 17(2), 329-333. https://doi.org/10.1519/00124278-200311000-00031 Stanula, A., & Roczniok, R. (2014). Game Intensity Analysis of Elite Adolescent Ice Hockey Players. Journal of Human Kinetics, 44(1), 211-221. https://doi.org/10.2478/hukin- 2014-0126 Stanula, A., Roczniok, R., Maszczyk, A., Pietraszewski, P., & Zając, A. (2014). The role of aerobic capacity in high-intensity intermittent efforts in ice-hockey. Biology of sport, 31(3), 193. https://doi.org/10.5604/20831862.1111437 Stone, H. M., Oʼbryant, S. H., Schilling, K. B., Johnson, L. R., Pierce, C. K., Haff, G. G., & Koch, J. A. (1999). Periodization: Effects Of Manipulating Volume And Intensity. Part 1. Strength and Conditioning Journal, 21(2), 56-56. https://doi.org/10.1519/00126548-199904000-00019 Stone, M. H., Moir, G., Glaister, M., & Sanders, R. (2002). How much strength is necessary? Physical Therapy in Sport, 3(2), 88-96. Suchomel, T., Nimphius, S., Bellon, C., & Stone, M. (2018). The Importance of Muscular Strength: Training Considerations. Sports Medicine, 48(4), 765-785. https://doi.org/10.1007/s40279-018-0862-z Swarén, M., Fredrik, H., Larsson, A., & Björklund, G. (2018, 2018). Key performance indicators of ice hockey sprint performance BASES Conference, Harrogate, UK, 27- 28 November, 2018, http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34993 Szmatlan-Gabrys, U., Langfort, J., Stanula, A., Chalimoniuk, M., & Gabrys, T. (2006). Changes in aerobic and anaerobic capacity of junior ice hockey players in response to specific training. Journal of Human Kinetics, 15, 75. Tortora, G. J., & Derrickson, B. H. (2018). Principles of anatomy and physiology. John Wiley & Sons. Turner, A. (2011). The Science and Practice of Periodization: A Brief Review. Strength and Conditioning Journal, 33(1), 34-46. https://doi.org/10.1519/SSC.0b013e3182079cdf Twist, P., & Rhodes, T. (1993). The Bioenergetic And Physiological Demands Of Ice Hockey. Journal of the National Strength and Conditioning Association, 15, 68-70. Vachon, A., Berryman, N., Mujika, I., Paquet, J.-B., Arvisais, D., & Bosquet, L. (2020). Effects of tapering on neuromuscular and metabolic fitness in team sports: a systematic review and meta-analysis. European Journal of Sport Science, ahead-of- print(ahead-of-print), 1-12. https://doi.org/10.1080/17461391.2020.1736183 Warnock, R. (2018). The Effect of Injuries on Player and Team Performance: An Empirical Analysis of the Production Function in the National Hockey League.
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Williams, T., Tolusso, D., Fedewa, M., & Esco, M. (2017). Comparison of Periodized and Non-Periodized Resistance Training on Maximal Strength: A Meta-Analysis. Sports Medicine, 47(10), 2083-2100. https://doi.org/10.1007/s40279-017-0734-y Wilson, J. M., Marin, P. J., Rhea, M. R., Wilson, S. M., Loenneke, J. P., & Anderson, J. C. (2012). Concurrent training: a meta-analysis examining interference of aerobic and resistance exercises. The Journal of Strength & Conditioning Research, 26(8), 2293- 2307.
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Attachment 1
Adressat till verksamhetschefen 2020-04-17 och till den ansvarige över lagets Sid 1 (2) träningsplaneringens upplägg i:
UMEÅ UNIVERSITET
Informationsbrev och samtyckesblankett
Härmed informeras samt tillfrågas ni om deltagande i följande undersökning som ingår i vårt examensarbete på kandidatnivå i idrottsmedicin:
”Training Program design and performance in the Swedish Hockey League - can differences in training program design explain performance differences in the SHL?”
Syftet med undersökningen ifråga är att analysera skillnader mellan olika SHL-lags träningsupplägg och se om dessa kan förklara prestationsskillnader i ligan. Vi vill därför analysera olikheter i uppläggens systematiska och metodologiska träningsvariabler och därefter diskutera dess påverkan över lagens prestation.
Ishockey på elitnivå är en komplex sport där framgång beror på flera interdisciplinära faktorer. Till vilken grad dessa faktorer bidrar till lagets prestation och framgång är idag inte känt men varje del spelar stor roll för att skapa optimala förutsättningar. Fram till idag har ingen svarat på vår frågeställning och vi anser därför att dess resultat kommer att vara till stor hjälp för sportens utveckling och för föreningarnas samt tränarnas fortbildning inom området.
Urval Vi har valt fyra SHL-föreningar utifrån en egen skapat “rankingsystem” som bygger på hur lagen har presterat i seriespel och slutspel de senaste fem åren. Vi har därefter plockat ut två lag som placerat sig i den övre halvan och två lag som har placerat sig i den undre halvan av rankingsystemet.
Vad förväntas av er? ● Du föreningens verksamhetschef samt du som är ansvarig över träningsplaneringens upplägg kommer att kontaktas och informeras om syftet och nyttan med deltagandet i arbetet.
● Du som är ansvarig över träningsplaneringen, kommer att få svara på en enkät med frågor om träningens planering, belastning och upplägg. Att besvara frågorna kommer ta ungefär 30 minuter. Du förväntas att svara sanningsenligt eftersom du med ditt deltagande hjälper oss att samla viktig information om ämnet.
● När arbetet är klart kommer ni att få möjligheten att ta del av den färdigställda uppsatsen vilket kan ge er chansen att jämföra ert resultat med de andra deltagande föreningarna.
Vad händer med era uppgifter? Uppgifterna, som kommer att samlas in med ett enkätformulär (Textalk Websurvey), kommer att pseudoanymiseras så att föreningarna inte kan identifieras och sedan lagras på ett krypterat USB minne i högst 2 år. Endast vi skribenter och vår handledare kommer att ha tillgång till samtliga uppgifter, och för att skydda er verksamhet kommer vi att behandla dessa med sekretess och konfidentialitet. Detta gäller även efter avslutat arbete. Studiens resultat kan komma att användas i vetenskapliga publikationer.
Frivillighet Er deltagande i undersökningen är helt frivilligt och ni kan när som helst avbryta er deltagande utan närmare motivering. Undersökningen kommer att presenteras i form av en uppsats vid Umeå Universitet.
Institutionen för samhällsmedicin och rehabilitering, Umeå universitet, 901 87 UMEÅ
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Adressat till verksamhetschefen 2020-04-17 och till den ansvarige över lagets Sid 1 (2) träningsplaneringens upplägg i:
UMEÅ UNIVERSITET
Samtyckesblankett till deltagande i den ovannämnda undersökning som ingår i vårt examensarbete.
Genom min underskrift ger jag min och verksamhetens medgivande till vår deltagande i denna undersökning baserat utifrån den ovannämnda informationen.
Medgivande
● Jag har tagit del av informationen kring projektet samt de dokument som berör mig och är därmed medveten om hur materialet kommer att hanteras, presenteras och den tid den tar i anspråk.
● Jag har rätt att företräda klubben samt jag ansvarar för att den data och information som delas ut eller berättas är sann.
● Jag har fått tillfälle att få mina frågor angående uppsatsen besvarade innan den påbörjas och vet vem jag ska vända mig till med frågor.
● Jag deltar i datainsamlingen frivilligt och har blivit informerad om syftet med deltagandet.
● Jag är medveten att min data kommer att användas med konfidentialitet.
● Jag är medveten om att jag när som helst under och efter uppsatsen kan avbryta mitt deltagande utan att jag behöver förklara varför.
● Jag ger mitt medgivande till studenterna att dokumentera, bearbeta och arkivera den information som samlas in under uppsatsen samt att resultatet kommer publiceras på DiVA. Materialet från uppsatsen kommer att behandlas konfidentiellt i den meningen att namn aldrig kommer att publiceras, samt att organisationstillhörighet kopplade till enskilda utsagor inte heller kommer att publiceras.
Ort / Datum Namnförteckning
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Namnförtydligande
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Ytterligare upplysningar lämnas av nedanstående ansvariga.
Enea Moretti Sebastian Byström Robert Nilsson Studerande Studerande Handledare +46 70 880 23 81 +46 70 267 74 78 +46 90 786 69 52 [email protected] [email protected] [email protected]
Institutionen för samhällsmedicin och rehabilitering, Umeå universitet, 901 87 UMEÅ
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Attachment 3
Lower-performing-team group Higher-performing-team group Team A Team B Team C Team D Educational level Q1 General Bachelor’s Bachelor’s degree Bachelor’s degree Bachelor’s degree degree Course at university Master’s degree (60 Course at other hp) institution Course at university Course at other institution Q2 In the field of Sports Sciences/Medicine Bachelor’s Bachelor’s degree Course at Bachelor’s degree degree Course at university university Master’s degree (60 Course at other hp) institution Course at university Course at other institution Communication level about the interaction between ice and other trainings Q3 Frequency (1-5 scale) 5 4 5 5 Q4 Detail level (1-5 scale) 3 3 4 4 Periodization during the pre-season Q5 How many weeks consists a normal pre- 16 15 12 15 season in your franchise? In how many, of the different periodization categories, do you divide your pre-season? Q6 Phases 4 4 1 3 Q7 Meso-cycles 4 6 2 0 Q8 Macro-cycles 1 4 5 3 Q9 Micro-cycles More 2 10 6 Q10 Other 0 Do not know Do not know 0 Training volume during the pre-season Q11 How many training sessions per week 8 10 12 7 do you do on average during your pre- season? Q12 How many training hours per week do 12 11 14 12 your do on average during your pre- season? Training volume distribution during the pre-season How is the distribution between these sessions during an average training week during your pre-season? (number of sessions) Q13 Strength training 4 4 5 3 Q14 Endurance training 5 3 4 2 Q15 Rehabilitation training 0 Do not know Do not know 0 Q16 Prehab training 1 4 6 5 Q17 Eventual Ice practice 1 2 4 0 Q18 Other 4 0 Do not know 2 Training volume distribution during the pre-season How is the time distribution between these sessions during an average training week during your pre-season? (time in hours) Q19 Strength training 4 5 6 4 Q20 Endurance training 5 2 3 3 Q21 Rehabilitation training 0 More Do not know 0 Q22 Prehabilitation training 2 1 2 3 Q23 Eventual Ice practice 1 3 3 0 Q24 Other 3 0 Do not know 2 Periodization during the in-season In how many of the different periodization categories do you divide your in-season? Q25 Phases 4 7 2 2
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Q26 Meso-cycles 4 4 5 0 Q27 Macro-cycles 1 7 10 3 Q28 Micro-cycles More Do not know More 4 Q29 Other 0 0 Do not know 0 Training volume during the in-season Q30 How many training sessions per week 8 10 7 9 do your do on average during your in- season? Q31 How many training hours per week do 8 11 9 14 your do on average during your in- season? Training volume distribution during the in-season How is the distribution between these training forms during an average training week in your in-season? (number of sessions) Q32 Strength training 3 5 4 2 Q33 Endurance training 0 Do not know 1 1 Q34 Rehabilitation training 0 More Do not know Do not know Q35 Prehabilitation training 1 5 4 4 Q36 Eventual Ice practice 4 5 5 6 Q37 Other 2 0 0 0 Training volume distribution during the in-season How is the time distribution between these sessions during an average training week in your in-season? (time in hours) Q38 Strength training 2 2 4 2 Q39 Endurance training 1 Do not know 1 1 Q40 Rehabilitation training 0 Do not know Do not know Do not know Q41 Prehabilitation training 1 2 2 2 Q42 Eventual Ice practice 4 7 6 9 Q43 Other 1 0 Do not know 0 Physical tests How many times per year do you perform these physical tests? (1-10 or more) Q44 Maximal strength (t.ex 1RM) More 3 More 3 Q45 Power (t.ex CMJ) More 3 More 4 Q46 Anaerobic capacity (t.ex Wingate test) More 2 4 1 Q47 Aerobic power (t.ex VO2max) 4 2 4 1 Q48 Aerobic capacity 4 2 4 1 Q49 Lactate threshold 4 0 4 1 Q50 Off-ice RSA (Repeated Sprint Ability) More 2 0 1 Q51 On-ice RSA (Repeated Sprint Ability) More 1 3 1 Q52 Agility test (t.ex Illinois Agility Test) More 2 4 1 Q53 Mobility 3 2 4 1 Q54 "Specific" injury preventive screening 3 1 4 1 (t.ex FMS; Y-balance) Q55 Other More Do not know More 4 Q56 During which month do you usually May June June August May June August June August perform your physical test battery? August December April September October December April November November January December January February Individualization Q57 How individualized is the players 2 3 4 3 training program during pre-season? Q58 How individualized is the players 1 3 6 6 physical training during in-season? Q59 How individualized is the players Ice 6 6 2 5 practice during in-season?
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Alternative answers: 1 = 100% pure individual adapted ; 2 = 80% mostly individual adapted ; 3 = 60% quite individual adapted ; 4 = 50% individual adapted ; 5 = 40% somehow individual adapted ; 6 = 20% a little individual adapted ; 7 = 0% not individual adapted ; 8 = do not know Training load periodization model Which training load periodization model are you using during the following training categories? Q60 Strength training during the pre-season Block ; daily Block ; weekly Linear ; block ; Block ; daily undulating undulating weekly undulating undulating ; weekly undulating
Q61 Endurance training during the pre- Block ; daily Linear ; weekly Consistent training Block ; daily season undulating undulating load undulating ; weekly undulating
Q62 Strength training during the in-season Daily Block Block ; daily Block ; daily undulating undulating ; weekly undulating undulating
Q63 Endurance training during the in-season Block We do not use any Other: "Ice practice Daily undulating periodization model as endurance training"
Q64 Ice practice during the in-season Block ; daily We do not use any Daily undulating ; Daily undulating ; undulating periodization model weekly undulating weekly undulating
Timing of training during a day If you perform the following training forms, when during the day do you place them? Q65 Ice practice Before 12:00 Before 12:00 Before 12:00 Before 12:00 Q66 Power, explosivity and speed Before 12:00 Before 12:00 Before 12:00 Before 12:00 Q67 Maximum strength Before 12:00 Before 12:00 Before 12:00 Before 12:00 Q68 Hypertrophy After 12:00 Before 12:00 Before 12:00 Do not know Q69 Aerobic abilities After 12:00 After 12:00 Before 12:00 After 12:00 Q70 Anaerobic abilities Before 12:00 After 12:00 Before 12:00 After 12:00 Q71 Rehabilitation Before 12:00 Before 12:00 After 12:00 After 12:00 Q72 Prehabilitation Before 12:00 Before 12:00 Before 12:00 Before 12:00 Q73 Other Before 12:00 Do not know After 12:00 After 12:00 Monitoring training load How do you monitor the players training load in these different training categories? Q74 Strength training Through Volume, resistance Volume, resistance Volume, resistance effort, other (%RM), exertion (%RM), effort (%RM), effort (= auto- (close to failure) (velocity) (velocity) regulated weight training) Q75 Endurance training Volume, HR, Volume, estimated Volume, HR Volume, HR, estimated intensity, velocity velocity, distance intensity, velocity, distance Q76 Ice practice Volume, HR, Volume, estimated Volume, HR, Volume, estimated estimated intensity estimated intensity intensity intensity
Q77 Total (resistance-, endurance- & Ice Volume Volume (time), Volume (number of Volume (number of practice) (time), estimated intensity workouts), Volume workouts), Volume estimated (time), estimated (time), HR intensity, intensity, HR other (= sensors) Monitoring daily readiness/freshness
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Q78 Through which method do you monitor Power test We do not monitor Power test (CMJ, We do not monitor the players' readiness/freshness? (CMJ, SJ, players' SJ, etc.), other (= players' etc.), readiness/freshness, more options readiness/freshness questionnaire other (= verbally) coming next season) about freshness, questionnaire about recovery quality (sleep, diet, etc.), questionnaire about motivation level How often do you measure the players' readiness/freshness during the pre-season? Q79 Power test (CMJ, SJ, etc.) Daily We do not measure Once a week Once a month this Q80 Estimated freshness/readiness Daily Daily We do not measure Daily this Q81 Estimated recovery Daily Daily We do not measure Daily this Q82 Estimated motivation Daily Daily We do not measure Daily this Q83 Other way Once a week Do not know Once a week We do not measure this How often do you measure the players' readiness/freshness during the in-season? Q84 Power test (CMJ, SJ, etc.) Daily We do not measure Once a week Once a month this Q85 Estimated freshness/readiness Daily Daily We do not measure Daily this Q86 Estimated recovery Daily Daily We do not measure Daily this Q87 Estimated motivation Daily Daily We do not measure Daily this Q88 Other way Once a week Do not know Once a week Once a month Training intensity measurement Which intensity measures do you use for the following training forms? Q89 Maximum strength Velocity Rate of Perceived %1RM %1RM Exertion (RPE)
Q90 Power training Velocity Velocity %1RM Power (Watt) Q91 Speed training Velocity Velocity Here we do not use Velocity intensity measures
Q92 Hypertrophy training Other Reps in Reserve Here we do not use Here we do not use intensity (RIR) intensity measures intensity measures measures
Q93 Endurance training Velocity Rate of Perceived Here we do not use HR Exertion (RPE) intensity measures
Q94 Ice practice RPE-Borg Rate of Perceived Here we do not use HR Exertion (RPE) intensity measures
Training volume measurement How do you measure training volume?
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Q95 Strength training Sets x Sets x repetitions Sets x repetitions, Sets x repetitions x repetitions x Sets x repetitions x weight weight weight, number of workouts
Q96 Endurance training Time Time (workout number of workouts Time (workout (workout hours), number of hours), number of hours) workouts, distance workouts
Q97 Ice practice Training time Training time on ice Training time on ice Training time on ice on ice (active (active time only) (active + passive (active + passive + passive time), number of time) time), workouts Training time on ice (active time only) Training volume distribution during the pre-season How does the volume distribution between these different forms of physical training look like during your pre-season? Q98 Maximal strength training 30% Do not know 30% 50% Q99 Hypertrophy training 10% Do not know 10% 0% Q100 Power training 20% Do not know 40% 40% Q101 Speed training 20% Do not know 10% 10% Q102 Circuit training 0% Do not know 0% 0% Q103 Plyometric training 20% Do not know 10% 0% Q104 Other 0% Do not know 0% 0% Training volume distribution (intensity) during the pre-season How does the volume distribution between these different intensities of strength training look in your pre-season? Q105 Supermax > 100 %1RM 20% Do not know 10% 0% Q106 Max 91-100 %1RM Do not know Do not know 50% 40% Q107 Heavy 81-90 %1RM 30% Do not know 30% 40% Q108 Medium high 71-80 %1RM 10% Do not know Do not know 20% Q109 Medium low 51-70 %1RM 10% Do not know 10% 0% Q110 Low 30-50 %1RM 10% Do not know 0% 0% Q111 Very low 0-29 %1RM 20% Do not know 0% 0% Distribution between unilateral / bilateral exercises during the pre- season What is the volume distribution between unilateral vs bilateral exercises in your pre-season? Q112 Strength/resistance training 50-50 % 80-20 % 60-40 % 50-50 % Q113 Power training 20-80 % 60-40 % 50-50 % 50-50 % Q114 Plyometric training 60-40 % 80-20 % 20-80 % 80-20 % Training volume distribution during the in-season What is the volume distribution between these different types of training during your in-season? Q115 Maximal strength training 20% 40% 30% 40% Q116 Hypertrophy training 0% 0% 10% 0% Q117 Power training 40% 40% 60% 50% Q118 Speed training 10% 20% 0% 10% Q119 Circuit training 0% 0% 0% 0% Q120 Plyometric training 30% 0% 10% 0% Q121 Other 0% Do not know Do not know 0% Training volume distribution (intensity) during the in-season What is the volume distribution between these different intensities in your in-season? Q122 Supermax > 100 %1RM 20% 0% 0% 0% Q123 Max 91-100 %1RM 0% 30% 70% 40% Q124 Heavy 81-90 %1RM 20% 20% 20% 20%
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Q125 Medium high 71-80 %1RM 0% 0% 0% 40% Q126 Medium low 51-70 %1RM 20% 30% 10% 0% Q127 Low 30-50 %1RM 0% 20% 0% 0% Q128 Very low 0-29 %1RM 40% 10% 0% 0% Distribution between unilateral / bilateral exercises during the in-season What is the volume distribution between unilateral vs bilateral exercises in your in-season? Q129 Strength training 50-50 % 60-40 % 40-60 % 50-50 % Q130 Power training 20-80 % 80-20 % 60-40 % 50-50 % Q131 Plyometric training 60-40 % 80-20 % 20-80 % 80-20 % Frequency strength training intensities during the in-season During a regular training week in the middle of the in-season, how often do you practice these forms of strength training? Q132 Supermax > 100 %1RM Always once Never Never Never a week Q133 Max 91-100 %1RM Never Once a month several times a week Always once a week Q134 Heavy 81-90 %1RM Always once Once every two several times a week Always once a a week weeks week Q135 Medium high 71-80 %1RM Once a month Always once a week Always once a week Once every two weeks Q136 Medium low 51-70 %1RM Always once More rarely than More rarely than Never a week once a month once a month Q137 Low 30-50 %1RM Once a month several times a week More rarely than Never once a month Q138 Very low 0-29 %1RM several times several times a week Never Never a week
Frequency power training during the in-season During a regular training week in the middle of the in-season, how often do you practice specific speed and power training? Q139 Sprint training (ON-ICE) several times several times a week several times a week At least once a a week week Q140 Sprint training (OFF-ICE) At least once several times a week Less than once a Never a week month Q141 Change of direction (COD) (ON-ICE) several times several times a week several times a week several times a a week week Q142 Change of direction (COD) (OFF-ICE) Never Once every two Never Once a month weeks Q143 Power exercise (OFF-ICE) At least once several times a week several times a week At least once a a week week Q144 Plyometric training (OFF-ICE) At least once Once every two Once a month Once a month a week weeks Q145 Other way Never Do not know Do not know Never Interaction strength / power training & Ice practice During a regular training week in the middle of the in-season, when during the week you practice these forms of strength training? Q146 Maximum strength training Before heavy Before easy ice After heavy ice Separate, not in ice practice practice practice conjunction with other training Q147 Hypertrophy training We do not We do not practice We do not practice We do not practice practice these these during the these during the these during the during the competition period competition period competition period competition period
Q148 Power training Before easy Before easy ice Before easy ice Before easy ice ice practice practice practice practice Q149 Speed training Before easy Before heavy ice Before easy ice Before easy ice ice practice practice practice practice
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Q150 Plyometric training Before easy We do not practice Before easy ice We do not practice ice practice these during the practice these during the competition period competition period Training methods Q151 What kind of training methods do you Super set, Super set, Giant set, Super set, Drop set, Myo-Paus / use during your physical training? Circuit Myo-Paus / Forced reps/sets, Clusterset / rest- training, Clusterset / rest- Contrast training pause, Forced Contrast pause, Contrast reps/sets, CrossFit, training, training, Occlusion Contrast training, Velocity training, Overspeed Occlusion training, based training, STAC Overspeed training, training, Velocity based Eccentric training, Eccentric overload overload training training Volume distribution of endurance training during the pre-season What is the volume distribution between these different endurance sub capacities during your pre-season? Q152 Aerobic capacity 40% 20% 30% 10% Q153 Aerobic power 30% 0% 30% 40% Q154 Anaerobic capacity 10% 50% 10% 40% Q155 Anaerobic power 20% 30% 30% 10% Frequency endurance training during the in-season During a regular training week in the middle of the in-season, how often do you practice specific endurance training? Q156 Small sided games > 2gg x week > 2gg x week > 2gg x week > 2gg x week Q157 Repeated sprint ability (RSA) 2gg x month > 2gg x week 2gg x week 1gg x week Q158 Short intervals (20-60 seconds) 2gg x month 1gg x week > 2gg x week > 2gg x week Q159 Medium intervals (1-2 minutes) more rarely 2gg x month more rarely 1gg x week Q160 Long intervals (3-8 minutes) don't practice more rarely don't practice this 1gg x week this Q161 Aerobic capacity (9-120 minutes) 2gg x month don't practice this don't practice this 1gg x week
Q162 Other way don't practice Do not know Do not know don't practice this this Volume distribution endurance training during the in-season What is the volume distribution between these different endurance sub capacities during your in-season? Q163 Aerobic capacity 20% 10% 60% 10% Q164 Aerobic power 20% 0% Do not know 40% Q165 Anaerobic capacity 40% 50% 10% 40% Q166 Anaerobic power 20% 40% 30% 10% Volume distribution during different moments of the in-season period What is the volume distribution between ice practices and physical training during different periods of the in-season? (first number is for ice practice) Q167 Start of competition season (august) 60-40 % 60-40 % 60-40 % 80-20 % Q168 Middle of competition season 80-20 % 60-40 % 60-40 % 80-20 % (December) Q169 End of competition season (march) 100-0 % 80-20 % 60-40 % 80-20 % Volume distribution during the in-season What is the volume distribution between ice practice and different forms of physical training during your in-season? Q170 Ice practice 60% 60% 60% 80% Q171 Strength/resistance training 10% 20% 20% 20% Q172 Power training 10% 10% 30% Do not know Q173 Speed/jump training 10% 10% 10% Do not know Q174 Mobility training Do not know Do not know Do not know Do not know Q175 Cardio training 10% 0% Do not know Do not know Q176 Recovery training Do not know Do not know Do not know Do not know Q177 Other 0% Do not know Do not know Do not know
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