Showing posts with label injuries. Show all posts
Showing posts with label injuries. Show all posts

Wednesday, December 25, 2013

Athlete Monitoring 1.0

Athlete Monitoring 1.0



This is the MS Excel 2010+ (Windows) workbook designed for data collection and quick analysis and visualization using Pivot Table. The workbook is already set up for quick start-up with data collection such as athlete attendance, sRPE, Wellness, Injuries and Illness details and lot more. In the video at the bottom of the page you can see all the features and how-to of Athlete Monitoring 1.0.

This workbook is designed for small staff usage and sharing. High-end statistical analysis and data mining is possible by exporting the data to R or SPSS software, while the simple (visual) analysis is possible using Pivot Table and Chart.

To use this workbook successfully, users should have basic knowledge of how Pivot Table works and it would be highly recommended for the users to have at least some background in maintaining simple training database themselves.

For further customizations please contact me on my mail. 


The price for this workbook is $35








NOTE: If you don't receive the file immediately upon payment, please be free to send me the email and I will forward it ASAP. 

Saturday, October 13, 2012

Injuries vs. Team success



I just read one recent study on relationship of injury rate to team standing at the end of the season. You can find the free full text HERE, but here is the abstract anyway.

Eirale C, Tol JL, Farooq A, Smiley F, Chalabi H. Low injury rate strongly correlates with team success in Qatari professional football. Br J Sports Med. 2012 Aug 17.

Abstract
Using a prospective cohort study design, this study captured exposure and injuries in Qatar male elite football for a season. Club performance was measured by total league points, ranking, goal scored, goals conceded and number of matches won, drawn or lost. Lower injury incidence was strongly correlated with team ranking position (r=0.929, p=0.003), more games won (r=0.883, p=0.008), more goals scored (r=0.893, p=0.007), greater goal difference (r=0.821, p=0.003) and total points (r=0.929, p=0.003).

CONCLUSIONS: Lower incidence rate was strongly correlated with team success. Prevention of injuries may contribute to team success.


All studies of this kind are more than welcome. There is couple of them trying to show correlation between injuries[1] and team performance/season outcomes with not so clear relationship like this one.

My argument here is who is first – chicken or the egg? With observational studies we are not able to make any causation claims, even if it is common sense. We need experimental study, but that is very hard or nearly impossible to do in these scenarios.



So, the correlation claim should go two way – teams with lower injuries show better standing and teams with better standing show lower injuries. Thus the causation claim from studies like this should also be two-way: if you want a better success as a team reduce injuries AND if you want reduced injuries you better be a successful team. Without experimental study we don’t know what caused what – that’s the way correlation works. We don’t know what the change in one variable will yield in another. Hence the importance of learning statistics.

Suppose your team is on a winning spree. How do you feel? Awesome. How does this affect your stress levels and ability to sustain loads? Positively.

Suppose your team is on a losing spree. How do you feel? Like s*it. How does this affect your stress levels and ability to sustain loads? Negatively.

Thus the same physical workload in those scenarios will yield different reactions and thus different injury potential (IMHO). Hence my comment that if you want to decrease injuries you better play good :). Yes, the data from the study like this can be used as a proof for this claim.

I would love to do a point biserial correlation between wellness score 3-days after a game and game outcome (win, loss, draw), but I don’t have much data at the moment to make it valid. That might give some insights about the influence of the game outcomes on the perception of wellness and even training loads (if you track sRPE), and also correlate injuries with both of those data (we can also use some psychological tests of personality as moderator and even some screening tests). This is still observational, but it might give some more significant data. Idea for the study anyone?


[1] There are a lot of ways to quantify injuries, from time loss to occurrence, from over-use to contact ones. And each of them has pros and cons.