POWERPLAY 雜誌

A few weeks back ago I decided to examine hockey games to look for a few factors that might lead to success.  I had planned to release the article a few weeks ago, but, a funny thing happened.  Dino Barnabé had a similar idea.  He released an article in French titled "Revisit Our Classics (Part 1)" that also examined factors leading to wins in hockey.  With Dino's permission, I translated his article to English and plan to provide you my article as a companion article.  So after giving you a week to digest "Revisit Our Classics (Part 1)", I present my article "Factors that Lead to Wins in Hockey".

My goal in PPM sports is to ONE DAY have a JUGGERNAUT hockey team.  A team that is virtually unbeatable (at least in USA).  However, so far in my PPM career, I'm far from a JUGGERNAUT.  I do continue to grow, day-by-day, season-by-season.  With my current team, I can expect wins against many teams, unfortunately for me, I am still destined to humiliating losses when playing hockey elite teams such as the Psychos, Razorback Thugs and other power houses.  For today's article, I will examine factors that could effect a team's odds at winning.  I plan to examine the effect of team strength, overall team rating (OTR), game importance settings, and home ice advantage.  Anyone who has played PPM for even a few weeks ponders questions relating to success.  Can I expect to be competitive with teams who have higher team strength that mine?  Does home ice advantage help me win?  Is my high OTR why I am winning?  Hopefully, I can provide some statistics to consider about these questions.

For the study, I examined the 180 games played in USA on Day 1 of season 20.  For each game I collected the following information:  1) team strength difference (the Total Strength found on each team's profile page the day after the game was played), 2) Overall Team Rating (OTR) total difference (also found on team's profile page), 3) difference in game importance settings (average level difference per period - scores range from 4 to -4... scores of 4 would be playing at very high and opponent playing at very low), 4) did the winning team play on their home ice, and 5) what was the margin of victory.

Data used led to the following results:

1)    Team Strength Difference

a.    88% of all games played were won by the team with the higher strength rating.  
(That means only 12% of teams with a lower strength rating won).

b.    The largest negative strength difference to obtain a win was -71.

c.    Odds of Winning Based on Strength (# of games used for calculation)

i.    100% for teams with a positive strength difference of over 150 (9)

ii.    100% for teams with a positive strength difference of 101 t0 150 (13)

iii.    96% for teams with a positive strength difference of 51 to 100 (49)

iv.    88% for teams with a positive strength difference of 26 to 50 (32)

v.    89% for teams with a positive strength difference of 11 to 25 (28)

vi.    71% for teams with a positive strength difference of 1 to 10 (34)

vii.    62% for teams with a positive strength difference of 1 to 5 (26)

viii.    38% for teams with a negative strength difference of -1 to -5 (26)

ix.    29% for teams with a negative strength difference of -1 to -10 (34)

x.    11% for teams with a negative strength difference of -11 to -25 (28)

xi.    12% for teams with a negative strength difference of -26 to -50 (32)

xii.    4% for teams with a negative strength difference of -51 to -100 (49)

 xiii.    0% for teams with a negative strength difference of over 100 (22)

* For These Calculations:  Strength Difference = Teams Overall Strength - Opponents Overall Strength

2)    Overall Team Rating (OTR) Difference

  a.    80% of all games played were won by the team with the higher OTR

  b.    The largest negative OTR difference to successfully win was -81.

  c.    8% was the odds of winning if the teams OTR was over 50 lower than their opponent.

3)    Game Importance Settings

  a.    Only 39% of the teams using the higher game importance settings obtained a win.  (Likely influenced by high strength teams using very low settings for cupcake matchups).

  b.    For games with a strength difference of +/- 25 the following was found.  71% of those games played were between teams with neutral game importance settings.  Of the remaining games, 59% (17% of total) of the winning teams used a higher game importance setting than their opponent and 41% (13% of total) used lower game importance settings but still managed to win.

4)    Home Ice

  a.    65% of all games played were won by the home team.

  b.    51% of games played between teams with a difference of +/- 25 were won by the home team.

5)    Margin of Victory

  a.    10 goals was the average margin of victory for the 180 games examined.

  b.    Examining margin of victory versus team strength differences provided a more valuable picture.

i.    22 goal average for difference of 150 strength

      ii.    13 goal average for difference of 100 t0 150 strength

     iii.    14 goal average for difference of  50 to 100 strength

     iv.    8 goal average for difference of 25 to 50 strength

      v.    6 goal average for difference of 0 to 25 strength

      vi.    3 goal average for difference of -25 to -1 strength

      vii.    2 goal average for difference of less than -25

When reviewing the above data, I believe it leads to these factors. 

Factor 1:  Team strength has a strong impact on a team's potential to win.  If you have a lower strength rating than your opponent it is going to be significantly tougher to win.

Factor 2:  Team OTR has an impact on team play, but, to a lesser degree than team strength.

Factor 3:  The game importance setting can sometimes be important.  But, based on the data presented, game importance was not significantly important unless the games were between fairly closely matched opponents.

Factor 4:  Home ice does provide and advantage.  However, that advantage is hardly noticeable when playing teams of equal strength.

Factor 5:  Not only does team strength effect winning percentage, it also has a serious impact on margin of victory.

The data presented has plenty of room for improvement.  I based everything on only 180 games.  Numbers should still be fairly reliable.  Future studies could more precisely determine the numbers, but, using current data can lead managers to wiser decisions for upcoming matches.

Last comments, how does my data compare with Dino's article?  Well, they compare similar aspects, but, from different perspectives.  It's really hard to compare based on the directions ease article addressed the game.  I think each article has its place and value.  Dino's data was collected from a far larger group of games and I definitely look forward to his ongoing project.  ... anxiously awaiting part 2 of "Revisit Our Classics".  Here's wishing each of us, warmth and higher team STRENGTH.