It is often said that the more you do something, the better you get at it. Soccer has always been a big part of my life so I found myself thinking whether or not the saying actually made sense when applying it to sports. Some coaches and sports experts argue that the more games a player has under his belt, the more likely he is to score more goals. Others have suggested that the amount of games played does not contribute to how many goals a player will score in a season. For my project, I thought it would be rationale to find out if more games had a correlation with the amount of goals scored. My hypothesis is that we’re will a relevant increase in goals scored in correlation with the number of games player. Moreover, I think the more games a player has, the more likely he will be to score more goals. In addition, I would like to look at games played and goals scored and see which group of players as team scores the most goals for the team. I would form my secondary hypothesis: that the total goals will have a correlation with the groups who have played more games. This would evidently support the idea that experience does contribute to success if my hypothesis were to be true on a team level. I decided that the United States Men’s National Team would be a good test group to research with. They offered players will all similar levels of skill. They all were of close in age and years of experience played. I examined and researched the player’s career stats on the team’s official website for the current 2015/16 season. First I wanted to look at performances at an individual level. I focused on looking at individual players without breaking them up into separate groups. After I looked at my research, there seemed to be a slight correlation between games played and goals scored. The United States Men’s Soccer Team’s top goal scorer had also played in the most games. He scored 18 goals in 18 games. But this could just be an exceptional player so looking at how the team preformed as an average and group would provide additional support to my hypothesis. The scatter chart below shows a steady increase in games played and goals played.

Moving on to my second hypothesis, I then decided to break the team up into four groups based on the amount of games they played. These groups went up by variables of 5 each time ranging. After looking into such research, I found some interesting results. Those who fell in the range of 1-5 games had 43 goals total and were put into group 1. Those who fell into the range of 6-10 games had 68 goals and were put into group 2. Group 3 was composed of those who fell in the range of 11-15 games played had 14 goals total. Group four fell in the range 16-20 games played had 28 goals total. When first looking at these statistics were scored within group one (1-5 games played). I thought it important to then display how many players made up the group as I thought this was important to see in addition to the four groups’ total goals. The two pie charts below displays the researched context. As you can see, group 2 (playing in 6-11) games scored over half of the team’s total goals. This makes sense because they had the most players in their group in comparison. It also showed that the majority of the team’s goals are scored by those who play in group 2. Moreover group two is the highest populated and accumulates the most total goals for the team despite their lesser experience as the group 4 and 5. This data shows that my secondary hypothesis was incorrect. The less experience players as a group scored more goals than the more experienced players. However this does not mean they are the most talented players. To research that question, I took the information and plugged it in again with a different objective in mind.
To convert this data into something more applicable to my hypothesis for individual performances and number of games played. I calculated the groups’ average goal to player ration. These results below show that the players that had played the most games had the highest player to goal ratio. This table proves that I made a successful hypothesis when considering individual performances. The players who played in the most games (group 4) had the highest average goal to player ratio: 7 goals to each player. This supports my original hypothesis that the more games a player has the more goals he will be likely to score. Groups | Games Played | Goals Scored | Players in the Group | Average Goal to Player Ratio | Group 1 | 0 to 5 | 43 | 22 | 2.0 | Group 2 | 6 to 10 | 68 | 17 | 4.0 | Group 3 | 11 to 15 | 14 | 6 | 2.3 | Grop 4 | 16 to 20 | 28 | 4 | 7.0 |

Recommendations/Improvements for Future Studies
There are some external factors that could cause the data to be errored to a degree. Like many sports, each game is a new challenge. The difficulty of opponents can certainly contribute to a player’s ability to score. For example, if the some games are much harder and a starter plays in them but is rested for an easier team, he might get the same amount of “easier opportunity” to score as the substitute playing. My only suggestion as to fix this problem in a future study would to be examine the history of two teams playing together and see how the score fluctuates each year.