Miller (2014). Validity of using functional threshold power and intermittent power to predict cross-country mountain bike race outcome.
Journal of Science and Cycling, 3(1): 16-20
muscle fibers (Coyle et al., 1992). This suggests that
IP performance is at least in part based on the
parameters surrounding an athlete’s FTP. Moreover,
interval training can improve aerobic-dependent time-
trial performance (Stepto et al., 1999; Lindsay et al.,
1996; Padilla et al., 1999). While the training of the
participants in this study was not recorded, it can be
postulated that the strong relationship between these
two tests is at least in part due to the combination of
training benefits of off-road cycling and the upper limit
of intermittent exercise capacity as constrained by
The main finding of this study is that when using
relative power output to predict XCO-MTB, IP has a
stronger correlation than FTP. This agrees with the
finding of Inoue et al. (2012) where a 5 x 30-s Wingate
(at 50% Wingate load) could predict XCO-MTB
performance. Interestingly, when Prins et al., (2007)
had athletes perform a time trial on the same course as
race performances were recorded, a similar correlation
was found as that in this study when comparing IP with
race time. In the same study, variable intensity and 1-
km time trials were performed and compared with the
same XCO-MTB performance. While these trials were
completed with a high degree of control in the
laboratory, the results shown here suggest IP field test
can better predict race performance. This supports the
IP field test as it suggests that performance can be
predicted at least as well as any other previously used
model and independent of weather conditions and
expensive laboratory equipment.
The error associated with the regression models used in
this study indicates that IP can predict XCO-MTB
performance with less error than FTP. This is
important given that finish rankings were often
determined by smaller time margins than the error
associated with both tests, and could mean the
difference between finishing first and third or getting
pulled from UCI races where the 80% rule is in effect.
Two potential criticisms of the IP test from a laboratory
practitioner could be lack of control for the workload
and the selection of the work:rest ratios. However, we
feel that given the relationship of IP and race
performance, the ease of execution of the IP field test,
and the suggestion that the IP field test is at least as
good at predicting XCO-MTB performance as other,
more difficult field and laboratory measures, future
research can potentially point towards fine-tuning a
similar test to the one used in this study. This area
needs more research.
This is the first study to relate power-based field tests
of FTP and IP to XCO-MTB performance. While
the FTP test can explain much of the variation in
performance, a field-based IP test is a better
predictor of XCO-MTB race time than FTP. The
astute coach should use this test as a criterion when
determining the ability and preparedness of an
athlete for competition.
The authors would like to thank Saris Cycling Group,
USA for supplying PowerTap power meters, Joule 2.0
head units and Supermagneto Pro stationary trainers for
all test sessions.
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