Authors: Lenka L. Stepan, Irving S. Scher, Gerhard Ruedl, Jasper E. Shealy
Categories: 24th International Congress on Snowsports Trauma and Safety - The biennial meeting of the International Society for Snowsports Safety (ISSS), Snowsports, Ski, Snowboard, Speed, Helmet, Ability
Source: JSAMS Plus
Authors: Lenka L. Stepan, Irving S. Scher, Gerhard Ruedl, Jasper E. Shealy
To determine typical speeds of skiers and snowboarders on-piste groomed trails across the United States (US).
On-slope speeds of skiers and snowboarders were measured on trails of varying difficulty at 8 ski areas across the US. The trail difficulty designation and slope were documented for each location where speed measurements were taken. The equipment used (skis or snowboard), whether a helmet was worn, and the estimated ability (determined by the researchers) of snowsports participants were recorded. A multiple linear regression analysis was performed to determine the influence of these individual and environmental factors on the speeds of snowsports participants.
4164 speed observations were made between 2004 and 2020 on groomed trails at 8 ski areas representing 5 geographic regions in the United States. Across all observations, the average speed was 34.9 ± 13.6 km/h. The ability of the snowsports participant had the largest effect on speed. Advanced snowsports participants traveled faster (44.5 ± 11.7 km/h) than intermediates (32.4 ± 9.9) and beginners (19.9 ± 7.2). Skiers on average were faster (35.8 ± 13.8 km/h) than snowboarders (33.0 ± 13.2 km/h) and beginner and intermediate snowboarders were slower on average than their skiing counterparts. While the average speeds increased with increasing trail difficulty and slope, the correlation was weak (R^2^ = 0.15).
The ability of the snowsports participant was found to be the most influential factor affecting speed.
Unlike driving motor vehicles on public roads, there are no speed limits (or numerical recommendations) for snowsports participants in the United States (US) and there are no accurate, real-time displays of speed for individuals as they descend mountains. At ski areas in the US, skiers and snowboarders are expected to abide by the Your Responsibility Code that states “Always stay in control. You must be able to stop or avoid people and objects.” [1] To follow this code, snowsports participants must choose an appropriate speed to stay in control, even when challenged with changing environmental factors (such as varying snow conditions, terrain, and skier traffic). A speed that may be appropriate for one snowsports participant may be excessive for another; that is, there is no one speed that works for all snowsports participants at a particular time and location and an appropriate speed maybe influenced by both individual factors (such as ability and equipment) and environmental factors.
Excessive speed is often recorded as a contributing factor in snowsports accidents, injuries, and fatalities [2,3]. For collisions with fixed objects or other people, the pre-impact kinetic energy of a snowsports participant increases as the square of velocity. Because the difference between the pre- and post-impact energies of a snowsports participant must be attenuated by a component of the collision system (such as a helmet, ski area pad, snowsports participant, etc.), higher pre-impact speeds and energies provide more opportunity for injury. To help assess the injury mitigation capabilities of safety devices, it is important to understand the speeds at which snowsports participants travel on the slopes and if there are observable factors that influence their speeds.
Previous research teams have examined the speeds of snowsports participants in the US. Shealy et al. [4] recorded speeds of skiers and snowboarders using a radar gun at three ski areas in the US during the winter of 2002/2003. They measured speeds on groomed, “more difficult” (blue square) trails with slopes between 16 and 20° – anecdotally, the locations were the fastest at each mountain. Shealy et al. [4] found skiers were faster than snowboarders, males were faster than females, and helmeted skiers and snowboarders were faster than those not wearing a helmet. Scher et al. [5] determined the mean speeds of beginner and intermediate snowboarders on “easiest” (green circle) and “more difficult” trails at one California ski resort. Williams et al. [6] reported speed ranges of experienced skiers and snowboarders in gladed areas and on terrain park rails in the Northeast US.
Researchers have also studied the speeds of snowsports participants outside the US. Bailly et al. [5] reported speeds for skiers and snowboarders measured with a radar gun on trails of varying difficulty at three ski areas in France. They examined skill level, gender, and helmet use as factors related to speed. Ruedl et al. [8] measured speeds of skiers using a radar gun on slopes of “medium difficulty” at four ski areas in Western Austria. Dickson et al. [9,10] conducted studies using GPS (SPI Elite and Ski Tracks app on iPhone 3S devices) to examine speeds of snowsports participants in Western Canada throughout the day. Carus and Castillo [11,12] collected maximum and average speeds of snowboarders and advanced skiers enrolled in lessons at Spanish Pyrenees ski areas using the Ski Tracks App on Android devices. Bailly et al. [5], Ruedl et al. [8], and Dickson et al. [10] all found no significant differences in speed between helmeted and unhelmeted snowsports participants. Several of these previous studies focused on skiers' and snowboarders’ perceived speed and found that snowsports participants generally underestimate how fast they travel [4,5,[8], [9], [10], [11], [12]] when traveling close to the average skiing speed. Table 1 summarizes the data on average maximum speeds of skiers and snowboarders reported in the literature.Table 1Summary of publications reporting speeds of skiers and snowboarders around the world.Table 1Location &Winter SeasonSnowsport ParticipantsTrail DifficultyMaximum Speed, km/h (mean ± st dev)Measurement MethodShealy et al., 2005 [4]Northeast USA &Rocky Mountain USA 2002/2003Skiers and snowboardersAll abilities n = 650More difficult (16–20°)43.0 ± 11.2Radar gunScher et al., 2006 [5]Pacific Southwest USA2003/2004SnowboardersBeginners and intermediates n = 180Green (easiest)Blue (more difficult)27.7 ± 17.3Radar GunWilliams et al., 2007 [6]Northeast USAUnknown yearSkiers and snowboardersExperts n = 113GladesTerrain park rails<18 to 42∗<18 to 26∗Radar GunRuedl et al., 2013 [8]Western Austria2008/2009SkiersAll abilities n = 416Medium difficultly48.2 ± 14.3Radar GunDickson et al., 2012 [9]Western Canada2010/2011Skiers and snowboardersAll abilities n = 102Whole resort62.1 ± 12.9SPI Elite (GPS)Dickson et al., 2017 [10]Western Canada2012/2013Skiers and snowboarders Instructors n = 109Whole resort64.7 ± 17.4Ski Tracks App on iPhone 3sBailly et al., 2017 [7]France2013/2014Skiers and snowboardersAll abilities n = 1399Green (very easy)Blue (easy)Red (medium)Black (hard)43.4 ± 15.2Radar GunCarus & Castillo 2021 [11]Spanish Pyrenees2019/2020Snowboarders in lessonsAll abilities n = 312Unknown43.3 ± 14.1Ski Tracks App for AndroidCarus & Castillo 2021 [12]Spanish Pyrenees2019/2020Skiers in lessonsAdvanced n = 421Green (very easy)Blue (easy)Red (medium)54.1 ± 15.3Ski Tracks App for Android∗Williams et al. did not report the mean for speeds observed, instead they reported the range of observed speeds and the percent of observations below 24 km/h.
Though ski equipment has evolved significantly over the last decade, there have been no recent studies documenting the speeds of snowsports participants in the US. In addition, the influence on speed of observable individual and environmental factors that may be useful in the design of injury mitigation strategies have not been studied and reported for the US. To this end, we measured speeds of skiers and snowboarders across the US to examine the average speeds across different types of trails for snowsports participants of varying abilities.
On-slope speed measurements were collected between the 2003/2004 and the 2019/2020 seasons at eight ski areas in different regions of United States (US) as defined by the US National Ski Areas Association [13]: two in the Pacific Southwest; one in the Pacific Northwest; two in the Rocky Mountain Region; one in the Southeast; and, two in the Northeast. The ski areas represented the range of sizes (from small to large by snowsports participant visits), skiable area (from small to large), and a combination of local participants and destination areas that draw skiers from all over the world. Calibrated radar guns (Stalker ATS II, Plano, Texas, US; 8–161 km/h; 0.3 km/h for measured range, including cosine error) were used to measure the peak downhill speed of snowsports participants while they were in a control volume on a trail; that is, the speed was measured in a fixed 60-m region of a trail and taken when the measurement direction was co-linear with each snowsports participant's direction of travel. While taking measurements, experimenters were positioned behind objects such as trees or rocks and out of sight of the snowsports participants to prevent influencing their speeds. For each observation, the type of equipment (skis or snowboard), the ability level (beginner, intermediate, or advanced), helmet use, and speed were recorded. The ability of the skier or snowboarder was estimated by two experimenters observing the body kinematics and technique of the skier or snowboarder; the experimenters included snowsports biomechanics researchers and snowsports industry professionals, such as instructors and patrollers, that were familiar with skiing and snowboarding technique.
All observations were taken on groomed (on-piste) trails. The trail difficulty, as designated by the ski area, was recorded for each measurement location “easiest” (green circle); “more difficult” (blue square); or, “most difficult” (black diamond). In the US, trail designations relate to the difficulty of a trail compared only to other trails within the same ski area (not relative to difficulty of trails at other ski areas or globally). Because trails with dissimilar characteristics may have the same trail designations (because they are at different ski areas), the average slope of each measurement control volume was determined using a laser range finder (TruPulse 200×, Laser Technology Inc., US; ±0.1°).
The data were analyzed to compare speeds between skiers and snowboarders, participant ability, trail designations, geographic regions, and helmet conditions using T-tests with Bonferroni correction for multiple comparisons (R 4.2.1. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org). The effect of helmet use on skier and snowboarder speed was analyzed for all data, for each ability level, and for subsets of data taken (1) before the 2009/2010 season and (2) in or after the 2009/2010 season, when snowsports helmet use reached 50% in the US. To examine the effect of slope angle on speed, a linear regression analysis was performed in R. A multiple linear regression was also performed (using R) to test how snowsports participants’ ability, type of equipment, helmet use, trail difficulty, and NSAA region predicted speed. The fitted linear model (1)Speed,kph=β0+β1ability+β2equipment+β3helmet+β4traildesignation+β5NSAAgeographicregion
A significance level of 0.05 was used for all statistical comparisons.
A total of 4164 speed observations were recorded for snowsports participants at ski areas in the US; the average speeds were 34.9 ± 13.6 km/h across all observations, 35.8 ± 13.8 km/h for skiers, and 33.0 ± 13.2 km/h for snowboarders. The largest differences in speeds were found between ability groups; advanced snowsports participants traveled faster (44.5 ± 11.7 km/h) than intermediates (32.4 ± 9.9, p < 0.001) and beginners (19.9 ± 7.2, p < 0.001). Beginner and intermediate snowboarders were slower on average than skiers of the same ability levels (p < 0.001 for both). See Table 2 for a summary of results.Table 2Speed (mean ± standard deviation) in km/h by equipment, ability, and trail difficulty designation (left). Coefficients, standard error, and p-values results from the multiple linear regression analysis (right).Table 2
The slope of the trails where measurements were recorded ranged from 0 to 13° for the “easiest” trails, 10 to 19° for “more difficult” trails, and 21 to 30° for “most difficult” trails. The average speeds increased with trail difficulty designation (26.5 ± 11.8 km/h on “easiest” trails, 37.6 ± 12.6 km/h on “more difficult” trails, and 42.6 ± 15.4 km/h on “most difficult” trails), however the correlation between speed and trail difficulty was weak (R^2^ = 0.15, F(3, 4136) = 251, p < 0.001). When examining each ability level, speed increased slightly with increasing slope angle, but the relationship remained weak; see Fig. 1.Fig. 1Box and whisker plots of beginner, intermediate, and advanced snowsports participants' speeds for trails with different slope angles. The bold black line represents the median value, the box is the interquartile range, IQR, (from Q1, 25th percentile to Q3, 75th percentile, the whiskers show the minimum (Q1-1.5∗IQR) and maximum (Q3+1.5∗IQR), and the circles represent outliers.Fig. 1
The average speeds of intermediate and advanced snowsports participants were compared for different regions of the US. The average speed for intermediates in the Northeast (36.0 km/h ± 10.6) was 5 km/h faster than intermediates in all other regions (t = 8.6, df = 690, p < 0.001); this held true for both skiers and snowboarders. Advanced skiers in the Northeast (50.3 km/h ± 12.4) also skied significantly faster than advanced skiers in the Pacific Northwest and the Pacific Southwest (t = 7.1, df = 298, p < 0.001). Advanced snowboarders in the Pacific Northwest (39.0 km/h ± 12.4) on average traveled 7 km/h slower than snowboarders of the same ability in other regions (t = 6.7, df = 335, p < 0.001).
The average speed of helmeted skiers and snowboarders across all observations was 36.1 ± 13.3 km/h and was higher (t = 6.5, df = 1852, p < 0.001) than the average speed of non-helmeted snowsports participants (32.9 ± 14.1 km/h). There was no significant difference in speed between helmeted and non-helmeted snowsports participants for data collected before the 2009/2010 season when helmet use was less than 50% (t = 0.50, df = 1017, p = 0.618). For data taken after the 2009/2010 season, when helmet use was greater than 50%, helmeted snowsports participants on average traveled slower (37.6 ± 13.0 km/h) compared to those that were unhelmeted (39.0 ± 13.6 km/h; t = 2.0, df = 709, p = 0.044).
The overall multiple linear regression was statistically significant (R^2^ = 0.48, F(11, 4143) = 317, p < 0.001). The ability of the snowsports participant was shown to have the greatest affect on speed, while wearing a helmet, trail difficulty, and equipment type had little influence. The results of the multiple linear regression analysis are provided in Table 2.
In this study, we conducted on-slope speed measurements of skiers and snowboarders across the US to examine the effect of equipment, ability, trail designation and slope, helmet use, and geographic location on speed. The trails used in this study provided the potential for skiers and snowboarders to travel at fast speeds; the snowsports participants chose their on-slope speed, as opposed to being limited by the terrain. The overall mean speed for all observations on “more difficult” trails was 37.6 ± 12.6 km/h in this study – this is lower than the speeds reported by Shealy et al. [4] (43.0 ± 11.2 km/h), by Bailly et al. [7] (49.9 ± 15.2 km/h), and by Ruedl et al. [8] (48.2 ± 14.3) for groomed trails with similar difficulty designations. These differences likely reflect a differentiation in ability levels found in the geographic areas for each study and the local snowsports culture. When comparing the distribution of ability levels among the studies, Bailly et al. [7] and Ruedl et al. [8] had higher percentages of advanced snowsports participants (52% and 69%) than the current study (37%); because advanced skiers and snowboarders travel faster than their less skilled counterparts (on average), it follows that datasets with larger percentages of beginner and intermediate level skiers and snowboarders (such as the data set presented here) will have lower average speeds. One explanation for the larger percentage of less skilled skiers and snowboarders in the current study maybe due to the local snowsports culture – for example, at some ski areas in the Western US, many more experienced skiers and snowboarders prefer to ski on ungroomed, off-piste terrain and use ski equipment that, while suited to their preferred terrain, is not ideal for on-piste hardpack conditions.
Others have examined the differences in speed between skiers and snowboarders. Similar to the results of Shealy et al. [4] and Bailly et al. [7], the data collected in this study showed that snowboarders traveled slower than skiers (by 1.7 km/h). This was not the case when considering only advanced skiers and snowboarders, as there was no significant difference in average speed on trails of similar difficulty. The difference in speed between lower ability skiers and snowboarders may be due to inherent differences in techniques to control speed. Beginner snowboarders often employ the “falling leaf” technique that requires the snowboard be positioned perpendicular to the fall line, creating more drag and slowing the snowboarder. On the other hand, beginner skiers often use a “snowplow” technique where the skis are generally pointed downhill and parallel to the fall line. As snowboarders master new skills, such as S-turns, their snowboards are more parallel to the fall line (and more similar to the position of skis), reducing drag and allowing for faster speeds.
Higher ability (as judged by at least two experimenters) was correlated positively with increased speed; the average speed increase between ability levels was approximately 12 km/h. Most snowsports participants were able to select appropriate terrain and employ techniques to control their speed in accordance with their ability. For example, almost all beginner observations were on “easiest” and “more difficult” runs; even though the “more difficult” trails had steeper slopes, beginners traversing “more difficult” trails only went 3.3 km/h faster than on the “easiest” runs and traveled significantly slower than intermediates and advanced snowsports participants on runs of similar difficulty.
Snowsports participant speed was not an indication of control in our observations and faster than average speeds did not necessarily indicate that a skier was “out of control” or being reckless. For example, on one more difficult trail, three advanced skiers were observed traveling more than 80 km/h; even though their speeds were more than three standard deviations higher than the average speed for advanced skiers on more difficult trails, these skiers were in control, making large radius turns, and remained distant from others on the trail. On that same trail (at a different time), an intermediate skier was traveling slower (64 km/h), but appeared “out of control” and unable to make turns and slow. These observations show that speed and control are not always coupled and highlight that there is not a particular speed that is “safe” for all snowsports participants. Our results show that overall snowsports participants, even beginners, can select appropriate speeds and terrain to remain in control based on their ability and skill level.
Shealy et al. [4] found that helmet users skied or snowboarded faster than individuals who were not wearing a helmet during the 2002/2003 winter season. These results led some to theorize that helmets increase risk-taking behavior, in a process called “risk homeostasis” or “risk compensation” [[13], [14], [15]]. While this has been examined by others using questionnaires that ask for self-reported risk taking behaviors [[15], [16], [17]], another indirect method for assessing risk taking behavior has been to examine speed of individuals on the ski slopes [4]. The concept of risk homeostasis suggests that wearing a helmet would decrease the risk of injury for an individual, and therefore that individual would engage in more risky behaviors (such as skiing or snowboarding faster) in order to maintain the same level of risk. Overall, the results of this study showed that the average speed of helmeted snowsports participants was faster than those that were unhelmeted, however this is likely due to a smaller proportion of advanced snowsports participants in the unhelmeted group (28%) compared to the helmeted population (41%).
According to the NSAA helmet usage data [18], helmet use increased from 28% to 86% over the course of the study from the 2003/2004 to the 2019/2020 winter season. When examining a subset of the data taken before the 2009/2010 season, when helmet use was below 50% in the US, there is no significant difference in speed between helmeted and unhelmeted snowsports participants. For the subset of speed data taken after the 2009/2010 season when helmet use increased beyond 50%, helmeted snowsports participants traveled 1.4 km/h slower than those that were unhelmeted. This small, but statistically significant difference, does not support the concept of risk homeostasis for helmet use in skiing and snowboarding.
Regional differences in speed were quite strong and support differences between our data and those reported from other countries and locations. For example, intermediate snowsports participants in the Northeast traveled faster than their counterparts in other regions, while advanced snowsports participants in the Pacific Northwest were slower than in other regions. One explanation for these speed differences may be typical environmental variations from region to region, such as snow conditions; although all observations were taken on groomed, on-piste trails, typical snow conditions in the Pacific Northwest (often soft, heavy, wet snow) can be very different from the hard-packed snow in the Northeast. The hard-packed conditions are favored for ski races and facilitate faster speeds compared to the softer, wet snow conditions found in the Pacific Northwest. Because snow conditions were not recorded in a consistent fashion throughout the course of the study, it is unclear whether regional differences in speed can be explained by different snow conditions and more research should be conducted to examine the effects of snow properties on the speeds of recreational snowsports participants.
The speeds reported in this study can help examine the impact mitigation potential of ski area padding. Collisions with fixed objects (including trees) represent about 5% of all injury incidents in the US [19], but are responsible for 78% of fatalities [3], with 8% resulting from an impact with a manmade object [20]. Even though beginners were more likely to be injured while skiing or snowboarding [19], Shealy et al. found advanced and expert snowsports participants accounted for 78% of on-piste fatalities in the US [20]. Based on the data reported in this study, the kinetic energy of a 50th-percentile male (77 kg) traveling at a beginner speed (19.9 km/h) is 1181 J; the same individual traveling at advanced snowsports participants’ speed (44.5 km/h) has 5900 J of kinetic energy, approximately 5 times the energy than when traveling at a beginner speed. Because snowsports padding can attenuate only limited quanta of energy (in the US, this can be on the order of a few hundred Joule), padding may be able to absorb the energy of a person travelling at a beginner speed but not at speeds of more advanced individuals. The speed data reported in this study can be used by individuals developing ski area padding, methods to test padding, and performance standards used to evaluate ski area padding.
In the present study, we were not able to monitor all factors that could influence the speeds of snowsports participants. The multiple linear regression analysis revealed that the parameters examined in this study accounted for about half of the variation in speeds observed, indicating there are other factors that influence speed on the ski slopes. Additional environmental factors such as snow conditions, visibility, skier traffic, and trail width should be examined in future studies to determine their effect on speed. Individual factors such as risk taking behavior, age, and gender may also play a role as suggested by previous studies [4,7,8,16].
This research study revealed that the ability of the snowsports participant was the largest contributing factor to speed at ski areas across the United States; more advanced skiers and snowboarders traveled significantly faster than their less skilled counterparts.
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.