When trying to choose a topic to research I tried to find one that interests me. I decided that I wanted to look at nhl players' statistics in some way

When trying to choose a topic to research I tried to find one that interests me. I decided that I wanted to look at NHL players' statistics in some way. Since I am a goalie myself I choose to look at goalies in particular. From looking at all of the statistics I decided to look at salaries more thoroughly since I believe that professional athletes are severely overpaid. When coming up with a question I decided to look at what factors affect NHL goalies' salaries since I had a lot of statistics that I could use to answer that question. The sampling technique I used was convenience sampling because once I found a website with most of the information I needed I only used those goalies to research further. The goalies I looked at were the top forty-five goalies with the highest salaries. There was possibly some sampling bias in the information I gathered because it is from the 2009/2010 season, which is after the salary cap was implemented, so the salaries aren’t an accurate representation of the years previous to the salary cap.

Based on my knowledge of hockey, I believe that years in the NHL, games played last year and goals against average last year will be the three factors that affect NHL goalies' salaries the most.

The factors that I looked at were; birthplace, current team, age, height, weight, year drafted, round drafted, overall draft pick, games played last year, wins last year, losses last year, shootout losses last year, shutouts last year, goals against last year, save percentage last year, goals against average last year, minutes played last year, years in the NHL, total games played, total save percentage and total goals against average. (For definitions and calculations of the factors looked at refer to glossary at the end).

The first factors I looked at were birthplace and current team, however I did not compare them directly to the average salary, I just looked at the frequency of goalies that came from each country or played for each team that were in the group of goalies with the top 45 average annual salaries.

This graph shows that Canada has by far, the highest frequency of goalies that make it into the NHL and have a salary ranked in the top 45 highest salaries. This does not however mean that Canadian goalies make more money than goalies from different countries, it could just mean that there are more Canadian goalies in the NHL. I was surprised that the United States did not have a very high frequency of goalies with the top 45 highest salaries since hockey is so big in the states.

This graph shows that most teams either have only one or two goalies with high salaries and their third string goalie has a low salary. The teams with only one goalie in the top 45 highest salaries only pay their starting goalie a high salary which makes the most sense since they are the ones playing the majority of the games, however it is beneficial to have a backup goalie who is good enough to pay a large amount to, incase your starter goalie gets hurt, this is why many teams have two goalies with high salaries. However, the two outliers in this graph are the New York Islanders and the Atlanta Thrashers, whose goalies are all paid an amount high enough to be ranked in the top 45 highest salaries.

Next, I choose to examine the physical characteristics of goalies to see which of them had the greatest impact on salary.

The graphs above showing height and weight being the explanatory variables and average salary being the response variable, indicate that as your body size increases, the amount of money you make decreases since both slopes are negative. The slope of the line of least squares for the graph comparing height and average salary indicates that for every inch taller a goalie is, his salary goes down by $329 000. The correlation of -0.30867281 between height and average salary shows that they have a negative, weak correlation, meaning that height has little effect on an NHL goalie’s salary. The slope of the line of least squares on the graph comparing weight and average salary shows that for every pound heavier a goalie is, their salary decreases by $2 150. The correlation of -0.015385332 between these two variables shows that weight has virtually no impact on an NHL goalie’s salary. I found this information interesting because I assumed that bigger goalies would make more money since they would take up more net and probably get less goals scored on them , which would in turn allow them to make more money since they are doing a better job. Since I am a goalie I decided to check what my salary would be according to my height and weight by extrapolating. Using the equation of the line of least squares from the graph comparing height and average salary, I plugged in my own height to fins out what my salary would be. From that equation I found that based on my height I would have a salary of 5.257 million dollars if I was an NHL goalie. Next, I did the same thing for my weight. From that equation I found out that based on my weight I would only make 3.142 million dollars if I was an NHL goalie. I found this information interesting because my salary based on my height was significantly higher than what my salary would be based on my weight.

Below are the graphs showing the relationship between goalies’ save percentages and their average salary. I found that there were outliers in this information as well so I removed them and created new graphs. These outliers were goalies with no saves last year, meaning they didn’t play any games and therefore had no stats to influence their salary for this year. In the graph showing the relationship between total save percentage and average salary there was a weak, positive correlation (0.3135), however after the outliers were removed, the correlation went from weak to moderate (0.4756) meaning that a goalie’s total save percentage does have a fairly significant effect on his salary. The slope of the line of least squares from this graph indicates that a goalie’s salary goes up by 137.2 million dollars for every 1 their save percentage goes up. However, it is impossible for a save percentage to be above 1, so I divided the slope by 100 to find out how much their salary increases for every 0.01 or 1% their save percentage increases. According to the calculation I made, for every 0.01 higher a goalie’s total save percentage is, his salary will go up by $137 200 in the next year. As for the graph showing the relationship between last years save percentage and average salary, the correlation between the two went from 0.3153 to 0.2626 after outliers were removed. This means that last years save percentage only has a weak correlation with a goalie’s average salary and therefore has little effect on his salary. The slope of the line of least squares from this graph indicates that a goalie’s salary goes up by 34.1 million dollars for every 1 their save percentage goes up. However, I had to divide the slop by 100 again since a save percentage cannot be over 1. From this calculation I determined that for every 0.01 higher a goalie’s save percentage from last year, his salary will be $34 100 more the following year. This set of graphs demonstrated that a goalie’s overall save percentage is more important than his save percentage just from last year when it comes to determining their average annual salary.

Below are the graphs showing saves last year and comparing saves last year to average salary. The graph comparing saves last year with average salary has a correlation of 0.5592, meaning that the correlation is moderate and positive. This indicates that the amount of saves a goalie makes each year has a fairly significant impact on their salary in the following year. The equation of the line of least squares line on the graph comparing saves last year and average salary indicates that for each additional save a goalie makes his salary will go up by $1570 from 1.2 million dollars if he made no saves at all. The graph strictly looking at saves last year shows that the average amount of saves a goalie with a salary ranked in the top 45 makes in a year is about 1152. I decided to plug this average into the line of least squares equation to find out much the average goalie would make a year based on the amount of saves he makes. From that equation I determined that if a goalie made the average amount of saves (1152) in a year he would receive a salary of 3.008 million dollars in the following year. Based on how strongly correlated the explanatory variables are correlated to the response variable (average salary), this information shows that the amount of saves a goalie made last year effects their salary more than their save percentage. I believe this is because it is likely that goalies with more saves over the course of the year played more games and were likely their teams starting goalie and generally starting goalies get paid the most. Where as a goalie could play only one game and have a high save percentage and not get paid as much because he is just a back up goalie.

Next I chose to look at each goalie’s record from last season in comparison to their average annual salary to see if the amount of games their teams win or lose has an effect on their salary. All three of the explanatory variables looked at in the graphs below had a positive, moderate correlation with average salary meaning that they probably al have somewhat of an impact on a goalie’s salary. Wins had the strongest correlation (0.5801), next was losses (0.4844) and the variable with weakest correlation out of the graphs below was shootout losses (0.4302). The slope of the line of least squares from the graph comparing wins last year to average salary was 0.0849 and the y-intercept was 1.3. This means that if a goalie didn’t win a single game in his season, his salary the following year would be 1.3 million dollars and his salary would increase by $84 900 for each additional game he won that season. The equation of the line of least squares from the graph comparing losses last year and average salary means that for every extra game a goalie loses in a season he will get $107 000 added to his salary for the next year. The equation of this line also shows that if a goalie didn’t lose any games in a season his salary would only be $1.5 million as shown by the y-intercept. Lastly, The equation of the line of least squares from the graph comparing shootout losses to average salary indicates that for each additional game a goalie loses in a shootout his salary will go up by $264 000 from $ 1.8 million if he doesn’t lose any games in a shootout. The information I gathered from these graphs didn’t really make sense to me since the line of least squares on the graphs showed that goalies make more money from losing more games then winning. The only rational conclusion I could draw from this information was that a goalie’s record actually had very little to do with his salary despite the moderate correlation coefficients. However the more wins, losses and shootout losses a goalie has, the more games he has played in so games played is actually the variable that affects a goalie’s salary. To further explore this prediction I decided to look at games played compared to average salary next.

The five factors that I found to have the most impact on an NHL goalies salary based on the strength of their correlations in order are; total games played (0.63585762), wins last year (0.58015612), games played last year (0.5620546), saves last year (0.55917401) and years in the NHL(0.52985582).I based my conclusion on correlations because I was trying to find out which variables had the most impact on an NHL goalie’s salary and correlations describe how closely related two variables are. All of the factors listed above still only have a moderate correlation, some are just stronger than others, this means that there are very many factors that influence an NHL goalies salary, not just a few really strong influential factors. Before gathering my information and analyzing the graphs, I hypothesized that years in the NHL, games played last year and goals against average last year would have the biggest impact on an NHL goalie’s salary, therefore two of my hypothesized factors were correct. I guessed that years in the NHL would be a big factor because I know that rookies can only make up to a certain amount of money each year and generally the more experienced you are, the more money you make, or if you aren’t good enough to make a lot of money, you probably won’t stay in the NHL for many years. I figured that the amount of games played last year would have a big impact on goalies’ salaries because I know that starting goalies usually make more money and starting goalies would have played the most games on their team. Lastly, I thought that goals against average last year would have an impact because generally coaches want goalies with a low goals against average and goalies who did well in their last season and they’re willing to pay them more. I think the reason why goals against average from the previous year didn’t have as much of an impact as some other factors because if a goalie isn’t on a good team then their goals against average will be lower but that doesn’t mean they should be paid less. I think the top five factors with the largest impact on goalies’ salaries have the most impact because they are all either related to how long the goalie has been playing or if he is the starting goalie or not. In conclusion, goalies who have been playing in the NHL for a longer time are going to have higher salaries than guys just coming into the NHL and starting goalies are going to be paid more than backups. There are many factors that affect an NHL goalie’s salary but they mostly have to do with experience.

“NHL Salary Database.”< http://static.fantasysports.ca/NHLSalaryData/globe/top100avg-G-salary.html> updated September 9^th, 2009.