2,000m Rowing

Ergometer 

Calculator

2,000m Rowing Ergometer Time Estimate Calculator

Predicts your 2,000m Erg Time on the Concept 2: Backed by science

This calculator has been made to predict the 2,000m time in fully-able athletes aged 18 or over. It took a sample of 111 rowers from clubs around the UK and Ireland to create a multiple regression equation that predicts performance to a high degree of accuracy.
To learn how to use this calculator, see the guide below.

 

Facts & Figures

111

Participants

10

Independent Variables Tested

82.2%

Accuracy

67.6%

Accuracy for Single Scull Time

 

How to Use This Calculator

Cavan Hagan

Rowing VO2 max test

This calculator requires 5 inputs: age, weight, arm span, 100m ergometer time and 5,000m ergometer time. Results are applicable to the Concept 2 rowing ergometer and fine single sculls. This is used within the following equations:

2,000m Rowing Ergometer Time =

219.367 + 0.198 × 5000m Time + 5.162 × 100m Time - 0.539 × Weight + 0.308 × Age - 0.419 × Arm Span

2,000m Single Scull Time =

140.928 + 0.777 × 2,000m Time

Entering Data:

  1. Age: Years. You may use decimals to indicate months: e.g. 25.5 is 25 and 6 months- though this won't have a significant impact on the end result. An increase in age will worsen 2,000m time*.

  2. Weight: Enter your most recent weight in kilograms (recorded on reliable scales on a hard, flat surface). You may use decimals. An increase in weight will improve 2,000m time*. Coaches may increase weight to improve 2,000m time- but do note that muscle mass is what causes this change and not fat mass. In addition, this correlation may not be as strong on the water due to drag.

  3. Arm Span: Measured by a measuring tape from finger tip to fingertip with arms abducted perpendicular to the torso. A longer arm span improves 2,000m time*.

  4. 100m Time: An indicator of muscular power by doing a maximum effort test for 100m on the Concept 2 rowing ergometer. A faster 100m time will improve 2,000m time*.

  5. 5,000m time: An indicator of aerobic endurance by completing 5,000m in the shortest time possible. A faster 5,000m time will improve 2,000m time*.

*To see the impact each independent variable has on 2,000m time, please consider purchasing the entire paper below.

Help for coaches:

  • This calculator can help identify the most important variables for team selection- though this is an indicator of potential and should not be used in isolation- particularly due to variation in the influence of each variable and other external variables.

  • This calculator can also help set 5,000m and 100m targets for your athletes to get them to their goal 2,000m rowing ergometer time. It can also show the potential impact a change in weight can have.

  • Age is more complicated than this linear model suggests. Age follows a U shaped trend where 2,000m time is lowest at around 30 years old.

  • Water time is only indicative. It's correlation with ergometer time has good accuracy (67.6%), though with a small sample size of 25 and the variation in results, due to a variety of factors, this is an unreliable result.

  • Consider setting up a spreadsheet for all your athletes using these equations- it should be much more time efficient for large teams.

 

Normative Data From Study

Please take caution when using these charts- they are for indicative purposes only. A higher R2 value means that the line is well fit. For an accurate result, use the equation attaches by changing "x" to your personal data. Example (for a female by age):

Average= 0.5712 x 23 years old + 453.89 = 467 seconds ( 7 minutes 47 seconds)

 Being above your line indicates you are above the average (within this sample of up to 111 rowers) for that specific variable.

The calculator on this page is the most accurate means of estimating your 2,000m time. This is simply a means to compare your result against the data.

Please note that some of the R2 values are extremely low, particularly with flexibility. Experience level was excluded due to the small sample size of novices. Finally, take caution as this is a linear model which does not account for non-linear correlations.

If you are in doubt about any of these charts, I recommend that you message me for support or simply ignore them.

Age and 2,000m Rowing Ergometer Time
Height and 2,000m Rowing Ergometer Time
Weight and 2,000m Rowing Ergometer Time
Arm Span and 2,000m Rowing Ergometer Time
Leg Length and 2,000m Rowing Ergometer Time
5,000m and 2,000m Rowing Ergometer Time
100m and 2,000m Rowing Ergometer Time
Flexibility and 2,000m Rowing Ergometer Time
 
 

ANTHROPOMETRIC AND FITNESS VARIABLES AS A PREDICTOR OF 2000M ROWING ERGOMETER TIME

Dissertation (Extended Length Paper)

Dissertation Poster

Abstract

The standard race distance in rowing is 2,000m, and therefore it is important to understand the anthropometric and fitness variables which influence the time taken to complete this time trial. This study aimed to create a predictive calculator using already known and easily measured variables, whereby a rower or their coach could input their anthropometric and fitness data, and estimate the time taken to complete a 2,000m time trail on the rowing ergometer. 111 club rowers participated in the study through an online questionnaire, which collected data on ten independent variables of 2000m time. The predictive variables placed within the multiple linear regression equation (R2=0.822) were 5,000m time (67.7% importance, p<0.001) 100m time (13.6% importance, p=.001), weight (8.6% importance, p<.01), age (5.6% importance, p<.05) and arm span (4.5% importance, p=.051). Linear regression between ergometer time and single scull time had a R2of 0.676. The predictive calculator is practical in club environments and can supplement existing team selection and talent identification criteria, in addition to validating goal setting and training programmes. A larger sample size with more controlled and standardized tests, alongside a more sophisticated predictive model, would help increase the validity and accuracy of the model but at the cost of more invasive and expensive measure.