ISSN: 1899-1955
Human Movement
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2/2018
vol. 19
 
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abstract:
Original paper

Does anthropometry influence technical factors in competitive mixed martial arts?

Christopher Kirk

Online publish date: 2018/06/05
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Purpose
Previous research has found grappling and strikes to the head to be the determining factors for success in MMA, whilst anthropometry in the form of stature and wingspan has been found to have a negligible effect. The current study was designed to determine if a relationship between technique use and anthropometry exists in MMA.

Methods
The in-competition technique data of 461 elite, professional MMA bouts were compared using Bayes factor t-tests (BF10) to determine which techniques display the highest likelihood of distinguishing between winners and losers. The differences in technique numbers between winners and losers was also compared to the anthropometric differences between winners and losers using either Bayesian Pearson’s r or Bayesian Kendall’s Tau. Simple linear regression (p < 0.05) was used to calculate predictive ability of anthropometrics on chosen fighting techniques.

Results
Heavyweight competitors were distinguished by striking only (BF10 = 399 – 10). Light heavyweight, middleweight, featherweight, bantamweight, women’s bantamweight and women’s straw weight competitors were distinguished predominately by striking (BF10 = 791661 - 7) and moderately by grappling (BF10 = 75 - 7). Welterweight, lightweight and flyweight competitors were distinguished by striking techniques (BF10 = 3.533e+6 – 221) to achieve dominant grappling positions (BF10 = 17100 – 50). In turn, it was found that stature and/or wingspan are correlated to and can predict key technique variables at heavyweight, welterweight, lightweight and featherweight.

Conclusions
The results provide evidence of which techniques are influenced by the anthropometric differences between competitors, allowing coaches and competitors to make more informed tactical decisions in competition preparation.

keywords:

MMA, anthropometry, combat sports, Bayes factor, key performance variables

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