dc.description.abstract |
Many studies have reported the frequency and types of injuries in
soccer players. However, a few have assessed the relationship of playing
position, climate, psychological effects and infra structure facilities with
injury. The purpose of the study was to develop a statistical model for
injuries among the soccer players in Jaffna. The observations on the soccer
injury-related variables, age, Body Mass Index (BMI), playing position, years
of experience, training method, equipment and ground facilities, climate and
psychological effect were collected from a simple random sample of 125
soccer players from Jaffna. These nine variables were grouped into 3 factors
using the factor analysis techniques. The first factor (TIF) consists of
training method and infra structure facilities; the second factor (AE) consists
of age and years of experience and the third factor (BMP) consists of BMI
and playing position. It is interesting to note that the three variables in the
first factor are common for a soccer team and the variables in other two
factors are associated with individual players. Significant associations exist
between injuries and standardized BMI groups as well as playing positions.
The odds of getting injury was significantly increased from back to forward
direction in the soccer field. Logistic regression analysis was used to fit a
model for soccer injury for a team by considering the factor TIF and another
logistic regression model was fitted for soccer injury for an individual player
considering other two factors AE and BMP. Further, a sample maximum
likelihood discriminant function (SMLDF) was developed to classify a soccer
player as injured or not. Using the SMLDF and based on an individual soccer
player’s observations on the above nine variables, we will be able to advise
him about the risk of getting injury in future |
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