# To compare the change in number of goals scored home and away by Premiership teams in two seasons. I will use the 2000-2001 and 2001-2002 seasons.

GOAL

Aim

To compare the change in number of goals scored home and away by Premiership teams in two seasons. I will use the 2000-2001 and 2001-2002 seasons.

## Hypothesis (part 1)

I predict that the teams will score more goals at its home stadium than at the opposition’s stadium. This is because the players will be used to training and playing at their home stadium. They will not be as familiar with the opposition stadium. Also there will be more supporters for a home side at a home stadium so the players’ morale is boosted. These conditions also apply to the opposition. This means a team should score more at home than away.

I also predict that the teams, which tend to score more goals at home, will also score more goals away than the teams which score less at home. This is because these teams have a lot of good players who can adapt easier in foreign stadiums.

## Investigation

I have created a table to show the number of goals scored by each team home and away in the 2000-2001season.

It can be seen from the table that more goals are scored at home than away by the teams, 529 home goals as opposed to 405 away goals. Almost every team scored more goals at home than away. The only exceptions are Middlesborough and Coventry City.

## Comparing Means

The mean of goals scored at home is 587 ÷ 20 = 29.35

The mean of goals scored away is 405 ÷ 20 = 20.25

This shows that the average team scores 9 (nearest whole number) more goals at home than it does away.

Using this mean the standard deviation can be found.

## Standard deviation

As well as having an idea of the ‘average’ of the data, it is useful to know how the data are distributed around the average. The standard deviation is known as a measure of dispersion as they say something about how the data are dispersed around the average (mean).

A distribution in which the values are widely spread will produce a high value for the standard deviation, and a distribution in which the values are closely grouped will produce a low value for the standard deviation.

The standard deviation is a useful way to compare the spread of values in two or more distributions.

Here is the standard deviation of the goals scored at home.

1672 ÷ 20 = 83.6

83.6 = 9.1

This value shows that the deviation of the number of goals scored at home is 9.1.

The standard deviation of the goals scored away can be calculated in much the same way.

690.42 ÷ 20 = 34.5

34.5 = 5.9

Home Goals   Mean = 29.35    Standard Deviation = 9.1

Away Goals    Mean = 20.25    Standard Deviation = 5.9

From these calculations the goal distributions can be compared. It can be concluded that the clubs tend to score more goals at home than away, but the number of away goals is more tightly grouped. This is expected as all the clubs commonly share the unfamiliarity of playing at an away pitch. As some teams are better than others, they will tend to score more at home than ...