1. Activity Profile of Winners and Losers within Varying
Weight Categories in Elite Amateur Boxing
Performance analysis (PA) primarily attempts to quantify the physical,
technical and tactical aspects of performance. However, El-Ashker (2011)
notes that PA research within boxing is limited.
Hughes and Bartlett (2002) state that performance results should be
interpreted by relating key performance indicators (KPI’s) to normative data,
to construct a ‘performer profile’. Performance profiling thus attempts to
circumvent this issue of large inter-match/bout variations by relating data to
the population of interest.
Although Davis et al. (2015) already quantified activity profiles of winners
and losers at the 2012 Olympics, the study preceded recent international
governing body rule changes in 2013, which included the adoption of the 10-
point ‘Must System’ present in professional boxing. Profiling specific weight
classes, rather than all boxers as a whole population, aims to provide a
more comprehensive and specific profile of each individual, closely related
to their weight category. Weight is known to affect performance in other
combat sports such as taekwondo (Bridge et al., 2013), thus warranting
consideration in boxing, which in turn could inform future performance and
training.
Thus, the purpose of the study was to produce a more recent activity profile
for elite amateur boxers within contrasting weight categories.
The study was comprised of 38 performances of elite amateur male boxers
(age 23.5 ± 2.8 y), competing in 19 semi-final bouts at the 2015 AIBA World
Boxing Championships, across 10 weight classes, ranging from light
flyweight (49 kg) to super heavyweight (91+ kg). For the purpose of the
study, the 10 weight classes were separated into three different groups; 46-
56 kg; 60-75 kg; 81-91+ kg.
Each bout, consisting 3 x 3-minute rounds, was analysed using Dartfish
analysis software (Version 8, Switzerland). All analysis was completed using
an adapted version of a previously developed tagging template, which
recorded the punch type, target and outcome (See Figure 1).
Punch efficiency was found to be higher in the winning heavy
group, opposing findings of Smith et al. (2000), in which
middleweights were found to more efficient.
Results could inform future practice and training, to allow boxers
to implement a specific rounded approach to a fight, appropriate to
each weight category. However, coaches and boxers should take
caution when implementing training regimes upon a fighter’s
weight category alone, as ability level is ultimately the most
important variable of performance (Thomson & Lamb, 2016).
Boxers fluctuating between weight categories is becoming more
prevalent in boxing, and for those moving between ‘light’ and
middle’ for example, would need to be aware of differences
between tactical and technical strategies within this weight class
and prepared for such changes.
James Latham
Intra and inter-analyst reliability was assessed, and deemed
acceptable (i.e. > 95% agreement).
Head
Body
Punch Type
Target
Outcome
Unknown
US Miss
US Defended
US Hit
Successful
Very Successful
Jab
Backhand
Lead Hook
Rear Hook
Lead Uppercut
Rear Uppercut
Figure 1. Key performance variables measured.
Methods
Conclusions
References
Results
Statistical Analysis
Introduction
Reliability
Ashker, S. E. (2011). Technical and tactical aspects that differentiate winning and losing performances in
boxing. International journal of performance analysis in sport, 11(2), 356-364.
Bridge, C., Jones, M., & Drust, B. (2011). The activity profile in international taekwondo competition is modulated
by weight category. International Journal of Sports Physiology and Performance, 6(3), 344-357.
Davis, P., Benson, P. R., Pitty, J. D., Connorton, A. J., & Waldock, R. (2015). The activity profile of elite male
amateur boxing. International Journal of Sports Physiology and Performance, 10(1), 53-57.
Hughes, M. D., & Bartlett, R. M. (2002). The use of performance indicators in performance analysis. Journal of
Sports Sciences, 20(10), 739-754.
Smith, M. S., Dyson, R. J., Hale, T., & Janaway, L. (2000). Development of a boxing dynamometer and its punch
force discrimination efficacy. Journal of Sport Sciences, 18(6), 445-450.
Thomson, E., & Lamb, K. (2016). The technical demands of amateur boxing: Effect of contest outcome, weight
………… . and ability. International Journal of Performance Analysis in Sport, 16, 203-215.
Figure 3. A profile of punch type thrown by winners and losers, across
different weight categories.
Figure 2. Profile of punch output and efficiency of winners and losers,
across different weight categories.
There were no significant differences found between punch output,
amongst winners and losers across the weight categories (P >
0.05).
However, there were significant differences found between punch
efficiency of Heavy Winners, when compared to Light Losers,
Middle Losers and Heavy Losers respectively (P < 0.05).
There were no significant differences between the frequency of
each punch type, across the different weight categories (P > 0.05).
1. Shapiro-Wilk test.
2. Kruskal-Wallis test with post-hoc Mann-Whitney U tests.
3. Effect size estimates (z/√sample size)
Participants
Procedures
R1 = Round 1
R2 = Round 2
R3 = Round 3
