University of Limerick
Harrison_2018_Aforce.pdf (604.6 kB)

A force profile analysis comparison between functional data analysis, statistical parametric mapping and statistical non-parametric mapping in on-water single sculling

Download (604.6 kB)
journal contribution
posted on 2022-12-05, 12:12 authored by John Warmenhoven, ANDREW HARRISONANDREW HARRISON, Mark J. Robinson, Jos Vanrenterghem, NORMA BARGARYNORMA BARGARY, Richard Smith, Stephen Cobley, Conny Draper, Cryil Donnelly, Todd Pataky
Objectives: To examine whether the Functional Data Analysis (FDA), Statistical Parametric Mapping (SPM) and Statistical non-Parametric Mapping (SnPM) hypothesis testing techniques differ in their ability to draw inferences in the context of a single, simple experimental design. Design: The sample data used is cross-sectional (two-sample gender comparison) and evaluation of differences between statistical techniques used a combination of descriptive and qualitative assessments. Methods: FDA, SPM and SnPM t-tests were applied to sample data of twenty highly skilled male and female rowers, rowing at 32 strokes per minute in a single scull boat. Statistical differences for gender were assessed by applying two t-tests (one for each side of the boat). Results: The t-statistic values were identical for all three methods (with the FDA t-statistic presented as an absolute measure). The critical t-statistics (tcrit) were very similar between the techniques, with SPM tcrit providing a marginally higher tcrit than the FDA and SnPM tcrit values (which were identical). All techniques were successful in identifying consistent sections of the force waveform, where male and female rowers were shown to differ significantly (p < 0.05). Conclusions: This is the first study to show that FDA, SPM and SnPM t-tests provide consistent results when applied to sports biomechanics data. Though the results were similar, selection of one technique over another by applied researchers and practitioners should be based on the underlying parametric assumption of SPM, as well as contextual factors related to the type of waveform data to be analysed and the experimental research question of interest.



Journal of Science and Medicine in Sport;21 (10), pp. 1100-1105





Other Funding information

Society of Biomechanics in Sport


This is the author’s version of a work that was accepted for publication in Journal of Sport and Medicine in Sport. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Science and Medicine in Sport , 2018, 21 (10), pp. 1100-1105,



Department or School

  • Mathematics & Statistics
  • Physical Education and Sports Science

Usage metrics

    University of Limerick


    No categories selected


    Ref. manager