April 9, 2015

It is the end! After a solid simulation on NHL 15, it oddly enough predicted the St. Louis Blues to win the Stanley Cup. Montreal lost in the first round of the playoffs to Boston! We will see what happens. Thank you for following along with me on this journey! Check back in a few weeks to see if my prediction of Montreal winning comes true. In the mean time, Go Sens Go!

March 20, 2015 (Post 2)

I have now conducted my final statistical analysis where I look at the current (as of March 20, 2015 at 10am) standings and make a decision.
To do so, I will look at the stats for the teams currently and award points (3, 2 or 1) to the top 3 teams. In the end, the team that has the highest overall score will be my predicted winner. 
Please note, this method may or may not be mathematically significant however, I believe that it is notable based on stats that I have read thus far.

Categories

Number of Wins:
Montreal, St. Louis, Anaheim (45) 3 (3 way tie)
New York Rangers (44) 2Nashville Predators (43) 1

Point Percentages:
New York Rangers (0.688) 3
St. Louis (0.676) 2
Anaheim and Montreal (0.674) 1 (2 way tie)

Goals For Per Game:
Tampa Bay (3.21) 3
Dallas (3.06) 2
New York Islanders (2.99) 1

Goals Against Per Game:
Montreal (2.17) 3
Chicago (2.21) 2
New York Rangers (2.23) 1

Goals For Percentage:
Nashville (58.0) 3
New York Rangers (57.3) 2
Tampa Bay (56.5) 1  

Shots For Per Game:
Chicago (34.1) 3
New York Islanders (33.8) 2
Nashville (31.5) 1

Shots Against Per Game:
Los Angeles (26.9) 3
Minnesota  (27.2) 2
Carolina, St. Louis (27.4) 1 (2 way tie)

Shots For Percentage:
New York Islanders (54.4) 3
Tampa Bay and Los Angeles (54.2) 2
St. Louis (53) 1
 
Outshooting Win Percentage:
St. Louis (0.682) 3
Nashville (0.675) 2
Chicago (0.659) 1

Outshot Win Percentage:
  Anaheim (0.641) 3
New York Rangers (0.640) 2
Montreal (0.605) 1

Scoring First Win Percentage:
  Washington (0.842) 3
Montreal (0.829) 2
New York Rangers 1

Corsi For Percentage:
Los Angeles (55) 3
Chicago (53.8) 2
Detroit (53.7) 1

 Fenwick For Percentage:
New York Islanders and Los Angeles (54.5) 3
Tampa Bay (53.6) 2
St. Louis (53.2) 1

Save Percentage:
Montreal (93.9) 3
Nashville (93.48) 2
New Jersey (93.56) 1

  And the winner is...  

 THE MONTREAL CANADIENS
With a close race between:
- Los Angeles Kings
- St. Louis Blues 
- New York Rangers

I will update further with my EA Sports simulation.
Let's see how this season pans out!
 
  

 

March 20, 2015

Good morning, blog! I have spent the last day or two reading through Statistical Analysis documents about the NHL when deciding who will be the Stanley Cup winner. My goal is that today, I will have a "Stanley Cup Winner" chosen. 

Ottawa Hockey Analytics Conference
While searching through the Hockey Analytics conference twitter feed and slideshow presentations, I found many hockey statistics websites which I searched through to gather more data for my Genius Hour. 

Hockey Analysis
 A site I came across while reading the slides from the conference was hockeyanalysis.com. I did a quick sift through this site to s
One acronym that came up frequently was CF (also seen as CF%). I also found there to be a CA. CF and CA stand for Corsi For and Corsi Against respectively. What are these? 
Corsi measures the differences in shot attempts amongst players. A team is awarded a + or - for shots on goals, missed shots and blocked shots. Naturally, shooting, scoring, saves and any percentages relating to these are important for Stanley Cup contenders (I mean, how else will you win games if you don't score and make saves?) so I figured this stat was also important to look into.
Fenwick also came up periodically which represents simply just the shots and missed shots (it does not account for blocked shots).

Sporting Charts
 Sporting Charts (www.sportingcharts.com) is another site that I found which presents real-time data for current and past seasons, teams and players and allows  you to compare and contrast different stats, teams and standings. I am looking forward to using this site for my analysis.

My Takeaway Points from Researching
From gathering information from these two sites as well as the conference site slides, I have decided to also focus on:
- Goals For percentage
- Shots For percentage
- Fenwick For percentage
- Corsi
- Corsi For percentage
- Shooting Percentag
- Save Percentage
- Goals per Game
- Shots per Game
- Home and Away Winning Percentages

References
 HockeyAnalysis.com. (2013). HockeyAnalysis.com: Advancing Our Knowledge of Hockey Through Statistical Analysis. [Website]. Retrieved from: www.hockeyanalysis.com.

Ottawa Hockey Analysis at Carleton. (2015). Statistical Sports Consulting. [Website]. Retrieved from: www.statsportsconsulting.com/ottanalytics.

SportingCharts.com (2014). SportingCharts.com. [Website]. Retrieved from www.sportingcharts.com.


 

 

February 12, 2015

I was intrigued by a recent Ottawa Hockey Analytic conference at Carleton University On February 7, 2015. Not only is it in my favourite North American city but it is also the city where my favourite NHL team is from! I wish I was there!  They had prestigious hockey analytics from across North America to present their findings.
Therefore, for my next genius hour post and for the next few weeks, I think I am going to focus on their findings once a summary is posted.
In the mean time, I am going to embed a TwitterChat started at the conference (#OTTanalytics) in my blog which I will research and look into at a further date. 
My current goal: By  February 28, 2015: I will have my statistical analysis complete and a prediction will be made.

February 4, 2015

Demands at school have been higher than anticipated so I have not currently reached my goal for this week in Genius Hour completion. Having said that, I will be sure to make up the time lost in coming weeks but for today's analysis, I will discuss briefly some of the current standings in the 2014-15 season. In weeks to come, I will be analyzing the data from other seasons (currently, the data is inputted for 2008 - 2014).

Toronto Maple Leafs
Oh, the Canadian 'favorites' (well...depending where you are from I guess). They started off so well; playoff contenders at that. After firing head coach, Randy Carlyle (even as a non-leafs fan, I miss you!), it seemed like the dust was clearing and Toronto was back on track. Now however under their current interim coach and former assistant coach, Peter Horachek, they have just suffered their 10th straight loss. 
All Leafs jokes aside,  each year Toronto has potential (I may even cringe as I say that) statistically. They have been known to win games despite being out-shot--something I found to resonate well with standings--and have some fresh new blood (Hello Nylander). Maybe next year, boys.


Ottawa Senators
I love the Senators (Go Sens Go!) Despite their current standings (roughly 12 points back from a playoff spot), they have good games and they have bad games. After firing their head coach, Paul MacLean (tear, tear), people were hesitant about their assistant coach, Dave Cameron, taking over. Although his winning streak is not nearly consistent, he is good at line juggling when appropriate! This young and vibrant group, under new captain, Erik Karlsson, has potential...they just need to find it!

Nashville Predators
Statistically, they are the best team in the league right now (72 points). Fresh off of a sweep against Toronto and winning 6 of their last 10 games, Nashville has been consistent both offensively and defensively. What is interesting to note is their goals for differential compared to their goals against is currently the second highest in the league (+35; only behind Chicago with +37). I now am curious as to whether or not this influences success.

St. Louis Blues
Currently St. Louis has the best record. Sitting pretty with 70 points, on a 6 game winning streak in regulation and winning 9 of their last 10 games, the fire is light underneath St. Louis! Throughout the entire season however, I have noticed their consistency. If I had to make any bets right now on who would win (statistically aside), they would be my go-to choice.

Until next time... 
 

 

January 27, 2015

Good morning!

For today's statistical analysis, I decided to analyze the factors which I looked at in the previous statistical analysis but just for the teams who made the play-offs for the 2013-14 season. These teams were: 

Anaheim Ducks
Boston Bruins
Chicago Blackhawks
Colorado Avalanche
Dallas Stars
Detroit Red Wings
Los Angeles Kings
Minnesota Wild
Montreal Canadiens
New York Rangers
Philadelphia Flyers
Pittsburgh Penguins
San Jose Sharks
St. Louis Blues
Tampa Bay Lightning 
 

Results

1) Pearson Correlation between number of points and number of wins in the regular season:  0.963.
This is a  very strong positive correlation. Naturally this makes sense because the number of wins you have correlates strongly with making the playoffs and earning a high amount of points.

2) Pearson Correlation between the number of points and average number of goals per game in the regular season: 0.695.
This shows that there is no correlation or relationship between the number of points accumulated and the goals per game for the play-off making teams. Oddly enough, there was a strong positive correlation for all of the teams. 
 
3)  Pearson Correlation between number of points and average number of goals against per game in the regular season-0.457.
This is a rather weak negative correlation. Therefore, more goals you let in has a negative effect on your success but it is not a strong relationship.

4)  Pearson Correlation between number of points and average out-shot percentage in the regular season:  0.872.
Once again, the out-shot percentage strongly correlates with success of the playoff teams.

5) Pearson Correlation between number of points and average out-shooting percentage in the regular season:  0.604.
There is still a a weak positive correlation between points and out-shooting opponents.

6) Pearson Correlation between number of points and average win percentage when a team scores first in the regular season:  0.648.
For the play-off making teams, there was no strong correlation with winning games when scoring first and the number of points accumulated in the regular season.
 
Next, I will do a new analysis on simply the play-offs from 2013-14 before moving on into past seasons.

January 20, 2015

Good evening, blog!

I have began part one of my statistical analysis! The main focus for today's analysis was "what correlates with the number of points a team accumulates during the regular season?"

For this analysis, I inputted my data from an Excel spreadsheet on SPSS and computed the Pearson Correlation for twelve tests. For those of you 'non-math' lovers, the Pearson Correlation basically finds the relationship between if one thing happens, does another thing happen. For example, if a team has a high out-shooting percentage during the regular season, does that mean they will end the season with more points?

For the sake of this first analysis, I focused on the regular season only. Also, for the math lovers out there, my alpha significance was 0.01 (for those of you who are confused, that means I computed with a margin of error of less than 1%). 
 

Interesting Results

1) Pearson Correlation between number of points and number of wins in the regular season:  0.982.
This is a  very strong positive correlation. Naturally this makes sense because the number of wins you have correlates strongly with the number of points you recieve.

2) Pearson Correlation between the number of points and average number of goals per game in the regular season: 0.834.
This is a rather strong positive correlation. Therefore, the more goals you score, the better chance you have of winning (makes sense).

3)  Pearson Correlation between number of points and average number of goals against per game in the regular season-0.753.
This is a rather strong negative correlation. Therefore, more goals you let in has a negative effect on your success (obviously).

4)  Pearson Correlation between number of points and average out-shot percentage in the regular season:  0.888.
This was the most interesting statistic I found. What I got from it is that there's a strong correlation between being out-shot and earning points. So I guess teams are more successful with less scoring chances. I want to look into this statistic in particular more to see if it is credible or a fluke.

5) Pearson Correlation between number of points and average out-shooting percentage in the regular season:  0.821.
There is still a positive correlation when out-shooting your opponent; however, it does not seem as strong as when you are out-shot. 

6) Pearson Correlation between number of points and average win percentage when a team scores first in the regular season:  0.854.
This credits the 'first goal wins the game' theory since there is a strong positive correlation with winning and scoring first.

I found weak or no correlations when correlating number of points with face-off win percentages, trailing in the first period winning percentage, shots against average per game and shots per game.

Next Steps

I want to look into my findings further and support them with findings from past seasons as well as find other strong positive correlations which may not be as obvious.  
I will start doing this later this week!