The goal of this study was to find the relationship between time of day of workout and the performance at that time. Ultimately, we want to answer the question of whether there is a specific time of day in which an individual's workout is at the optimum level. A study carried out by Facer-Childs and Branstaetter concluded that there is indeed an optimum time of day in which an individual's workout will be at it's peak and this time is dependent on the circadian phenotype of an individual. Circadian rhythm is one of the many factors that regulates physiological processes involved in athletic performance. This also means that the time in which one's performance is peak differs across individuals.
Tying this to our study, we found that the time of day at which a subject's level of performance is at peak differs drastically by comparing their power output and % exertion. A more direct way to make this comparison is by comparing the time taken to complete a 100 m sprint at different times of the day. The graph of comparison is shown in the Figure 3. Since time of sprint is related to the power output of an individual, this variable can also be used to measure the level of performance at a given time of day. Ideally, it would take a shorter time to complete a 100 m sprint if the subject is at his/her peak performance time.
Based on the results from Figure 3, Ashley's optimum time of day to workout is at 8 am, Marissa's would be at 3 pm and Matt;s would be at 8 pm. all in all, these results is aligned to the study done by Facer-Childs and Branstaetter. In order to get a better understanding of when is an individual's peak performance times, we need to consider many different factors and one of which is their circadian phenotype.
Reference
Facer-Childs, Elise, and Roland Branstaetter. "The Impact of Circadian Phenotype and Time since Awakening on Diurnal Performance in Athletes." Current Biology. Cross Mark, 29 Jan. 2015. Web. 2 May 2017.
Figure 3 Plot of time of sprint vs. time of day across all subjects
ConclusioN BY ASHLEY
ConclusioN BY MArissa
As mentioned before, the main agenda of this experiment is to see if there is a relationship between the time of the day and the performance of an individual. ANOVA and T-tests showed that for certain individuals there was an optimum time of the day that their workout would peak. Ashley's optimum time of the day according to the advanced statistics would be at 8:00 AM and Matt's would be at 8:00 PM. However, for me (Marissa), there was no trend in the data when only looking at the ANOVA and T-test values.. This could just be because I don't prefer a specific time of the day to work out and therefore perform relatively the same at all times. As Ashley will state in her conclusion below, there has been a study done that has shown there is an optimum time of the day for an individual to workout. Our study has been limited to using everyday equipment like a stopwatch and heart rate monitor, and yet we still were able to determine an optimum time of the day for two of the three participants.
Figure 1 Plot of time of sprint vs. time of day across all subjects
Figure 1
Figure 2
Figures 1 and 2 show the two ways we measured performance in our study and compare them to each individual at each time of the day. These graphs are a good visual tool in order to see the relationships between the times of day and the individual.
CONCLUSIONS
Throughout this project we aimed to find out if there is an optimum time of the day where an individuals performance is at its peak. Our null hypothesis predicted that there is not an optimum time of the day to workout and there would be no correlation between power output and percent exertion with respect to the time of the day. We performed this experiment and established quantitative measurements to compare to one another and ultimately see if there is a relationship between performance (power and percent exertion) and time of the day.
ConclusioN BY ashley
ConclusioN BY MAtt
When looking at the graph on the left, one can see that the power output is at its minimum at 8 am, then increases rapidly at noon, and decreases slightly at 8 pm. Next, we overlayed a blue line above Marissa's power output as shown by the blue line in figure 5. This is to demonstrate that that the representative average of all three test subjects is very similar to Marissa's power output throughout the course of the day. Her values increased steadily and then drop off in the evening, just as our overall average on the sensitivity does in figure 4. This may be because Ashley's power decreases throughout the day and mine (Matt's) increases, so the average of these two graphs would be a shape that is similar to Marissa's. This is an interesting find, and still proves our hypothesis that one's performance during a workout will hit a peak at some point during the day, but it varies by the individual.
Figure 4
Looking at the sensitivity analysis as a numeral power output, one can see that the time of day does have a large effect on the power exerted during a workout. By averaging each of our sprint power outputs at 8 am, 12 pm and 8 pm, some of the accuracy of the data was lost , since there was a fairly range of values. However, our representative average seemed to hit a peak in the performance of a workout in the middle of the day, as shown in Figure 4.
Figure 5
Overall conclusion
This study has shown that there is indeed a specific of day in which an individual's performance is at it's peak and this time differs between individuals. With that said, the hypothesis can be accepted.