Examination of Factors Affecting Surfski Paddler Speed

Author:
Mark R. Janas
School of Business, Management, & Technology
1315 Oakwood Avenue
Raleigh, NC 27610-2298
919-516-4057

Mark R. Janas, BS, MBA, EdD is a Professor in the School of Business, Management, & Technology at Saint Augustine’s University in Raleigh, North Carolina, where he also serves as the head coach of the cycling team and virtual sports program. He also manages RevoRace.com, a virtual event and race management program.

Examination of Factors Affecting Surfski Paddler Speed

ABSTRACT

The purpose of this study was to determine those factors most likely to affect overall surfski paddler speed. A survey distributed among paddlers was determined to be the best tool to make this determination. The survey included questions about average speed over a 5 kilometer paddle (in neutral conditions), stroke rate, stroke distance, craft and paddle characteristics, training habits, and paddler gender, weight, and age. Correlation coefficients (that measure the strength of the relationship between the variable and paddler speed) were calculated for each variable against the average reported speed by the paddler. Results: The variables that yielded the strongest positive correlation to paddler speed were stroke rate (0.750), ski length-to-width ratio (0.453), erg use (0.449), and training volume (0.430). Paddle blade area (0.323) and distance per stroke (0.320) demonstrated modest correlation to speed. The variables that yielded the strongest negative correlation were ski weight (-0.458) and paddler age (-0.368). Years of experience (0.160) and paddler weight (-0.194) demonstrated only little influence on speed in this data set. The results suggest that paddlers who want to improve their overall average speed could increase their stroke rate and/or training volume, transition to longer/narrower/lighter skis, and/or supplement their “on water” workouts with rowing machine sessions.

Key Words: surfski, kayak, paddling

INTRODUCTION

What is a surfski?

A surfski is a long, narrow, and relatively light kayak designed for speed on open water. Surfskis (also known simply as “skis” in the paddling community) typically include a foot-controlled rudder to steer and use a bailer to keep the cockpit from filling with water, making them an ideal choice for ocean swells, rough water, and even surfing. They are popular in Western Europe, Australia, and South Africa, and are growing in popularity in the United States.

Surfskis are up to 22 feet long, and some may be as little as 17 inches wide, enabling the craft to move very efficiently through the water. The longer, more narrow configurations take more skill to keep upright but offer additional speed to those who can master the required technique (1).

The first surfskis were designed in 1912 by a young inventor and carpenter, Harry McLaren, of Port Macquarie, New South Wales, Australia. McLaren wanted to design a craft that could “shoot the breakers” on his local waterway (2).

Twenty years later surfskis were introduced to beaches in Sydney by Dr. Harry Crackanthorp, one of McLaren’s early customers. The boats were an instant hit on the Sydney beaches There still seems to be some debate over the true origins of the craft, though consensus today credits McLaren for its design and Crackanthorp for bringing it to the masses.

Surfskis made it to the United States in the 1960s. They started to become popular in the 1980s after audiences watched Thomas Magnum (played by Tom Selleck) race a surfski on one episode of the television show, Magnum, PI (2). Arguably, the only cooler vehicle on the show was Magnum’s red Ferrari 308 GTS.

Surfskis Today

Since introduction to the Sydney beaches in the 1930s, surfskis have become an important tool for surf lifesaving. A competitive racing scene has also developed. Today, high profile races take place in South Africa, Hawaii, Australia, Europe, and elsewhere and are hosted by groups such as the International Canoe Federation, the International Life Saving Federation, as well as other regional event organizers (3, 4).

Though ski paddlers are concentrated in coastal areas, flat water ski paddling is getting more popular inland. Paddlers are drawn to the speed of craft, to the ability to re-enter after getting dumped, as well as to the technology and sleek lines associated with the craft. Many have identified ski paddling as a great outdoor workout and a way to get closer to nature.

Ski paddlers are dedicated to their hobby, often spending five thousand dollars or more on a single ski and thousands more on paddles, performance apparel, and associated gear. Many ski paddlers come from other endurance sports or other paddling disciplines. Some use ski paddling as a cross-training tool. Others are dedicated exclusively to the sport and focus on high-level training and competition. To meet and engage others in the relatively small community, many ski paddlers congregate on social media pages, chat rooms, and message boards to exchange information and share their experiences.

METHODS

The purpose of this study was to examine the demographics, equipment, and training habits of surfski paddlers, with a particular emphasis on identifying those factors associated with increased speeds. The tool of choice to perform this examination was an online survey distributed through various social media channels and other online outlets. The survey asked these key questions:

What’s your average distance per stroke (meters) over a 5K paddle in neutral conditions?
What’s your average speed (km/hr) over a 5K paddle in neutral conditions?
What is your average stroke rate per minute over a 5K paddle in neutral conditions?
How old are you? (years)
Gender (man, woman, prefer not to say)
What is your weight (kg)?
What type of surfski do you paddle? (Beginner ski, Intermediate ski, Racing ski, Other)
How much does your ski weigh (kg)?
How many years of experience on a surfski do you have?
What is your average training volume (hours per week)?
Do you use a rowing erg and/or kayak erg in the off season? (yes/no)
What is your paddle blade area? (small, medium, medium-large, large)

Thirty-seven (37) respondents answered the survey over the course of two weeks of data gathering.

Survey Results

Summary of the responses was as follows:

Question	Average	Median	Standard Dev
Distance per stroke (m)	2.46	2.45	0.21
Speed (km/hr)	10.16	10.10	1.54
Stroke rate/min	73.04	73.00	8.75
Age (years)	48.89	52.00	11.66
Paddler weight (kg)	82.26	80.5	12.41
Years of experience	7.86	5.00	8.38
Training volume (hrs/week)	5.32	5.00	2.54
Paddle blade area (sq. cm)	760.14	750	30.33
Ski Length/Width Ratio	13.43	13.89	1.73
Ski Weight (kg)	14.23	12.70	4.50

All but three of the respondents were male. Respondents were asked to self-assess their average speed, stroke rate, and stroke distance during a 5 kilometer paddle in neutral conditions. For the purposes of this study neutral conditions refer to conditions where there is no significant wind or current to affect paddler speed OR where such conditions are balanced out, for example, during an “out-and-back” paddle. Most respondents derived their stroke rate, speed, and distance per stroke estimates from GPS watches, apps, or other dedicated paddle sport devices. Paddle size answers (eg, small, medium, medium-large, and large) were converted to square centimeters based on the manufacturers’ average size of paddle blades of 735, 750, 820, and 845 square centimeters, respectively. Ski type answers (eg, beginner, intermediate, & racing) were converted to length-to-width ratios based on manufacturers’ average dimensions for such skis of 10.15, 13.89, & 14.92, respectively.

Data Analyses

As mentioned earlier, the primary focus of this study was to determine those factors that are most likely to affect overall paddler speed. It was decided that the best way to make that determination was to calculate correlation coefficients for each variable/survey question against the average reported speed by the paddler. The calculated values measure the strength of the relationship between the relative movements of the variable and paddler speed.

The values range between -1.0 and 1.0, with 1.0 demonstrating a perfect positive correlation and -1.0 demonstrating a perfect negative correlation. Values closer to 0.0 show no relationship between the variable and paddler speed. The calculated correlation coefficients for each paddler variable are summarized below:

Variable	Correlation Coefficient
Distance per stroke (m)	0.320
Erg use	0.449
Stroke rate/min	0.750
Age (years)	-0.368
Paddler weight (kg)	-0.194
Years of experience	0.160
Training volume (hrs/week)	0.430
Paddle blade area (sq. cm)	0.284
Ski Length/Width Ratio	0.453
Ski Weight (kg)	-0.458

DISCUSSION

Not surprisingly, the variables that yielded the strongest positive correlation to paddler speed were stroke rate (0.750), ski length-to-width ratio (0.453), erg use (0.449), and training volume (0.430). The question about use of a rowing ergometer was converted to a binary value (0=no, 1=yes) to calculate its correlation coefficient. Paddle blade area (0.323) and distance per stroke (0.320) demonstrated modest correlation to speed.

The variables that yielded the strongest negative correlation were ski weight (-0.458) and paddler age (-0.368). Years of experience (0.160) and paddler weight (-0.194) demonstrated only little influence on speed in this data set.

While not an exhaustive examination, the study suggests several possible areas of focus for ski paddlers who want to increase their average speed on the water. These paddlers could increase their stroke rate and/or training volume, transition to longer/narrower/lighter skis, and/or supplement their “on water” workouts with rowing machine sessions. What yields the most benefit for a particular paddler would vary based on paddler ability, as well as his or her existing equipment.

IMPLICATIONS FOR FUTURE RESEARCH

It is important to note that this study primarily isolated single variables against the average reported speed. While that may be sufficient to draw general conclusions, it may not tell the complete story. Although the author cross-checked additional trends between variables in the survey data set, a larger data set might reveal that these variables may be impacting each other more than realized, without necessarily the same impact on speed as calculated in isolation. For example, could it be that the ski length-to-width variable has a stronger positive correlation to speed simply because a more fit, experienced paddler is more likely to buy a more expensive racing ski? This particular data set does not suggest that, but more questions and analysis may be required to resolve this and similar questions.

This study could be improved by obtaining more survey data and implementing methods less reliant on respondent self-assessment (which could lead to issues with data accuracy.) For example, additional data could be extracted from race results or digital training logs. Further, more accurate results may be achieved by including more granular survey questions. The yes/no question about ergometer use could be modified to ask for weekly training hours spent on an ergometer. Respondents could also be asked to input their exact ski dimensions and paddle areas. Finally, more questions relative to interval training, racing habits, and cross-training may be beneficial.

CONCLUSION

REFERENCES

1. Deep Cove Kayaking (2015). What Exactly IS Surfskiing. Deep Cove Kayak blog. https://www.deepcovekayak.com/paddling-in-deep-cove/what-exactly-is-surfskiing/

2. Drane, R. (2011). Harry McLaren. Inside Sport (NSW, Australia) https://www.insidesport.com.au/news/harry-mclaren-421479.

3. International Canoe Federation (2021). https://www.canoeicf.com/canoe-ocean-racing-world-championships/lanzarote-2021.

4. International Life Saving Federation (2021). (Antwerp, Belgium) https://www.ilsf.org/lifesaving-sport/disciplines/