Thanks for visiting my homepage! As you can see, the teams in my Power Rankings are sorted by a certain five-digit number. This number is calculated by using a formula of my own design.
I wanted to make a formula that showed which
teams are the best at the moment. Because of the different opponents for the different teams from week to week (making it hard to compare different teams' performance), I decided to make a formula that took all games played during the regular season into account
(so that strong teams overall should generally place higher than weak teams), yet placed less importance on older games than the most recent ones (by weighing games by how recently they've been played). After trying different designs, I decided to stick with
my original plan (though in a stream-lined version), at least until I get the time to significantly expand my spreadsheets. This is how the formula works:
A team can get six different results in any game (not including goals for and against),
a regulation win, an overtime win, a shootout win, a shootout loss, an overtime loss, and a regulation loss. The first three (a 'W' in the standings) give a team 2 points in the standings, the following two (an 'OTL') give a team 1 point, while the final result
(an 'L') yields no points at all. This shouldn't be news for any of you. In my formula, all teams get 2, 1, or 0 points for each game, just as in the normal standings.
HOWEVER, I give each game a multiplier depending on when the game is
played. The first game of the regular season for each team has a multiplier of 1, so that the team will get 2, 1, or 0 WEIGHTED points for that first game. The multiplier for game #2 will be 2 (for a total of 4, 2, or 0 weighted points). The 14th game of the
season will get a multiplier of, you guessed it, 14, giving the team a total of 28, 14, or 0 weighted points.
At any point in the season, I divide the obtained number of weighted points by the maximum possible for that team. Finally, this
number is indexed to 100,000, meaning all teams will have a Power Rating between 0 and 100000. For comparison's sake, I've added the prorated points and prorated ROWs for the season. I also give the teams letter grades ranging from A+ to D- (or A+ to
D with anyone below D getting an F, if you like), based solely on these prorated totals. More on that in a seperate post.
Let's use my favorite team, the Chicago Blackhawks, as an example. Their first 10 regular season games this season
(2013-'14) ended with the following results (in order):
W - OTL - L - W - W - W - OTL - W - W - OTL
These results gave the Blackhawks:
2 + 2 + 0 + 8 + 10 + 12 + 7 + 16 + 18 + 10 (for a total of 85) weighted points.
they had won all of those ten games, they would've had 110 weighted points. Thus, at the time, their "weighted points percentage" was (85 / 110) .773, while their normal points percentage was (6-1-3, 15 points) .750. This means that they were trending upwards,
compared to their overall record, at the time. Had they lost their 10th game in regulation, while losing in OT in the third game, their overall record would be identical at 6-1-3, but their weighted points percentage would've been (78 / 110) .709 instead,
a sign that they were trending downwards.
Imagine if a team went 6-4-0 (.600 points percentage) in their first ten games, but was on a six-game winning streak after their 10th game. Even though they would trail Chicago by three points
after only 10 games, they would have a better Power Rating (.818) than Chicago, courtesy of their current winning streak (0 + 0 + 0 + 0 + 10 + 12 + 14 + 16 + 18 + 20 = 90 weighted points). Had they started their season winning six in a row, then finishing
this 10-game segment with four straight regulation losses, their Power Rating would have been (42 / 110) .382.
So, in short, more recent games are more important to each team's Power Rating than older ones, yet every game played has some
impact on the final rating. I think the term POWER RANKINGS should refer to a combination of overall strength and current form, something I think my formula accomplishes very well. Afraid of giving biased and subjective Power Rankings, I felt that the mathematical
and statistical way was the only way to go. I hope you like it!