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Many people claim that the home team holds an advantage in athletic events. Specifically referring to the NFL, playing on one’s home field is a game-changer. The advantages of playing on one’s home field include the added energy of the crowd, the ability to follow the team’s regular routine, and the benefit of not having to travel. In fact, these benefits are so significant to some people that a three-point advantage has been associated with the home field. Essentially, the home team in a football match has a field goal’s worth of an advantage. NFL fans are more than aware that a field goal may be the make or break for a match. This paper will examine the statistics from the 2016 NFL season to determine whether the data supports the hypothesis that the home team holds an advantage.
The Excel NFL 2016 Datasheet will be used to examine this question. The specific variables of interest are, “Winner At,” “Points Won,” and “Points Lost.” This analysis first requires that we determine the home team’s point margin. For a win, the team’s margin will be a positive value, while in the case of a loss, the team’s margin will be a negative value. Figure 1 shows the frequency of each point margin in the 2016 season. The generation of descriptive statistics for the point margin yields a mean of 3.1176, a median of 3, and a mode of 3. All three statistics are remarkably reflective of this alleged three-point advantage. Additionally, the standard deviation calculated from this dataset is 14.1942.
To determine how this data can reflect all NFL games, rather than strictly during the 2016 season, a confidence interval for the population proportion must be used. This data will be treated as a sample of 255 NFL games. The data shows that the home team won 153 out of 255 total games. The following formula will be used:
In this case, p=153/225, which equals 0.6, or 60%. Meaning, in this sample, the home team won 60% of the time. This can be used to estimate the true proportion of home team wins in the entirety of the NFL. For a 95% confidence interval, the critical value used is 1.96. Using the given data, the formula yields an interval of (.5399, .6601) or (53.99%, 66.01%.) This means that we are 95% confident that this interval includes the true population proportion.
This data can also be used to test the hypothesis of whether the mean advantage for the home team is in fact worth a field goal for all NFL games. The null hypothesis for this test will be μ=3. Since the standard deviation of all NFL games is unknown, the t test must be performed. The formula for the t statistic within the t test is as follows:
The value for μ was determined by the null hypothesis. The remaining values to complete the formula are provided from the descriptive statistic analysis completed on Excel.
Sample Standard Deviation
The solution to this formula using the data is t=0.1323. This test will also be conducted using a 95% confidence interval. In the t distribution table, it is recognized that as the number of items in a sample increases, t approaches z. Since the NFL sample contains 255 games, the t critical value of this test is equivalent to the z value (1.96.) To determine if the null is rejected, the t statistic must be compared to the critical value. The rule for whether to reject the null hypothesis is that the null is rejected if the magnitude of the t statistic is greater than the critical value. In this case, the t statistic is much smaller than the critical value; therefore, the null hypothesis is not rejected. There is sufficient evidence to conclude that the average home team point margin is equal to 3.
Although some people may claim that the home field advantage is just a myth; there is evidence that supports this claim. The data from the 2016 NFL season shows a win percentage of 60% for the home team, as well as an average point margin of 3.11. After running tests on this sample, it can also be proven that this claim is accurate for all NFL games. If one is to bet on an underdog, it would be best to do so when they are the home team.
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