So I got the swimming bug again after the World Championships so I decided yesterday to do a swim meet without having swam at all in 12 years. It was more fun than I expected and I swam about as fast as I was when I stopped swimming (at age 17).
What changed since then? (1) I have no cardio (i.e. died on 35-40m of the 50m LCMs I swam) and (2) 40 extra pounds of muscle with not a lot of extra fat.
I have always been of the view that strength/weight training is vastly underutilized in sports in general and am going to put it to the test in swimming.
My training will consist of only technique training, sprints, kick and very very little yardage (like ~1200 yards a WEEK).
I figure that will be enough to get my cardio to where I can sprint a 50 without dying and I figure all you need for a sprint is to be able to go all out for the whole race, with the remaining factors being power and technique which don't require much yardage I don't think.
Anyone ever try it?
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ABSTRACT
Zampagni, ML, Casino, D, Benelli, P, Visani, A, Marcacci, M, and De Vito, G.
"Anthropometric and strength variables to predict freestyle performance times in elite master swimmers. J Strength Cond Res 22: 1298–1307, 2008—The aims of this study were to determine in elite master swimmers of both genders whether, using anthropometric variables and the hand grip strength measure, it was possible to predict freestyle performance time, whether the considered predictors were related similarly to different events (50, 100, 200, 400, 800 m), and whether they were the same in male and female master swimmers. The relationships between performance times and age, body mass, height, arm length, forearm length, forearm muscle volume, and hand grip strength were examined in 135 elite master swimmers. Pearson’s simple correlation coefficients were calculated and then prediction equations were developed. Age, height, and hand grip strength were the best predictors in short-distance events, whereas only age and height were predictors in middle- and long-distance events. The correspond- ing coefficient of determination (R2) of performance times were 0.84 in the 50-m event, 0.73 in the 100-m event, 0.75 in the 200-m event, 0.66 in the 400-m event, and 0.63 in the 800-m event. These regression equations were then cross-validated in a control group of 126 nonelite, age-matched swimmers, obtaining significant and good correlations for all distances (range, r = 0.67 and 0.83; p , 0.01), indicating that predictors are valid in an extended sample of master swimmers. Differences between sexes were not found in 50-m event, but were present in all other events. These models might be useful to determine individual performance times by contributing to improving the individual’s training program and the selection of master swimmers. Coaches could have better accuracy in determining whether an athlete needs a strength training program in order to optimize performance time."
+
ABSTRACT
Zampagni, ML, Casino, D, Benelli, P, Visani, A, Marcacci, M, and De Vito, G.
"Anthropometric and strength variables to predict freestyle performance times in elite master swimmers. J Strength Cond Res 22: 1298–1307, 2008—The aims of this study were to determine in elite master swimmers of both genders whether, using anthropometric variables and the hand grip strength measure, it was possible to predict freestyle performance time, whether the considered predictors were related similarly to different events (50, 100, 200, 400, 800 m), and whether they were the same in male and female master swimmers. The relationships between performance times and age, body mass, height, arm length, forearm length, forearm muscle volume, and hand grip strength were examined in 135 elite master swimmers. Pearson’s simple correlation coefficients were calculated and then prediction equations were developed. Age, height, and hand grip strength were the best predictors in short-distance events, whereas only age and height were predictors in middle- and long-distance events. The correspond- ing coefficient of determination (R2) of performance times were 0.84 in the 50-m event, 0.73 in the 100-m event, 0.75 in the 200-m event, 0.66 in the 400-m event, and 0.63 in the 800-m event. These regression equations were then cross-validated in a control group of 126 nonelite, age-matched swimmers, obtaining significant and good correlations for all distances (range, r = 0.67 and 0.83; p , 0.01), indicating that predictors are valid in an extended sample of master swimmers. Differences between sexes were not found in 50-m event, but were present in all other events. These models might be useful to determine individual performance times by contributing to improving the individual’s training program and the selection of master swimmers. Coaches could have better accuracy in determining whether an athlete needs a strength training program in order to optimize performance time."
