#1 – Lindenwood University (17-0-0)
Last Week: 1
#2 - University of Missouri-St. Louis (14-2-0)
Last Week: 3
#3 - University of California, Irvine (17-1-1)
Last Week: 4
#4 - Michigan State University (18-2-0)
Last Week: 6
#5 - SUNY Stony Brook (16-2-1)
Last Week: 2
#6 – SUNY Buffalo (20-3-0)
Last Week: 5
#7 - The Ohio State University (18-2-0)
Last Week: 7
#8 - University of Michigan (15-5-0)
Last Week: 10
#9– University of Florida (13-3-2)
Last Week: 9
#10 - Eastern Michigan University (15-7-3)
Last Week: 11
#11 - Long Beach State (14-2-2)
Last Week: 8
#12 - California Polytechnic State University, SLO (10-5-3)
Last Week: 13
#13 - University of Rhode Island (13-4-4)
Last Week: 14
#14 - University of North Texas (16-2-1)
Last Week: 12
#15 –Colorado State University (15-3-1)
Last Week: 15
Monday, February 18, 2008
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The Rankings Explained
Since the conclusion of the season both founders set out to find the best solution to answer the age old question, “Who’s #1?” After much search, the answer was to use a mathematical formula to calculate the answer. Removing the human element from the voting would likely result in less biased rankings towards individual teams and regions.
The solution would be found in the ELO chess rating system. They system was created to rank chess players by another means that wins, losses and draws. The system uses a mathematical formula to reward each person for impressive feats and punish them for lesser impressive feats. Because chess and inline hockey are two different animals, the general equation had to be changed to allow for more hockeys related factors into the equation.
Using the FIFA Women’s World Rankings as a guideline (Elo Based), we managed to change the rankings to suit the nature of our sport. The rankings include the importance of the game, the outcome of the game, the expected result of the game, and the goal differential of the game when calculating a result. To better explain the way the rankings work I give you the following examples (all team start with a ranking of 1500):
Lindenwood University (1500) vs. UMSL (1500): If Lindenwood won the regular season game 4-3; they would be awarded 15 points for the victory and UMSL would be docked 15 points. However, if the game was won 12-2, Lindenwood would earn 39.38 points for the victory and UMSL would be docked 39.38 points. Additionally, the importance of the game could change, using the national title game as the example, with both teams having equal ratings Lindenwood would be awarded 52.5 points for a 6-3 win.
However, as you could assume, two teams having the same rating would be rare. Each teams point total carries over from one week to the next and from one season to the next. The following is a example of two teams with different point values and the different results it can produce.
Lindenwood University (1746.38) vs. Illinois State (1360.88): There are a few things that you can determine because of the vast difference in each teams rating (385.5). The first is that Lindenwood is expected to win the game. The second is that Illinois State winning the game would be a much bigger accomplishment that Lindenwood winning the game. The maximum points Lindenwood can earn from this game is 7.72, which would mean they won by at least 10 goals. However, on the flip side, if Illinois State was to win the game by at least 10 goals they could earn as many as 71.03 points. This is based on the projection that Lindenwood would win the match-up 90% of the time.
As the two examples show, there are a bunch of positives when using this system. For starters, once a team has achieved a high rating, it becomes difficult for them to increase it without playing a higher level of competition. This rewards regions that have more competitive teams. It also rewards teams who travel out of the region and win games against other higher rated teams. For example, last season, Towson and Army both played James Madison who would have had a higher rating that both visiting teams. In the games, Army and Towson both won handily and would have increased their ratings while negatively hurting James Madison. But, the hidden bonus is they now can bring those rating points back into their region. Those points then become spread out over the entire region as the season progresses and teams win and lose.
For the ratings system to work, each game has to have a certain amount of value attached to it. In the system we will be using five different levels to rate the importance of any give game. The first level is the lowest level of importance; it contains all pre-season exhibition games. The second level includes all regular-season regional games, as well as cross-divisional exhibition games. Level three includes all cross-regional games and invitational based tournaments, like WinterFest. The fourth level includes all regional playoff games and the fifth and final level includes all national playoff games.
The solution would be found in the ELO chess rating system. They system was created to rank chess players by another means that wins, losses and draws. The system uses a mathematical formula to reward each person for impressive feats and punish them for lesser impressive feats. Because chess and inline hockey are two different animals, the general equation had to be changed to allow for more hockeys related factors into the equation.
Using the FIFA Women’s World Rankings as a guideline (Elo Based), we managed to change the rankings to suit the nature of our sport. The rankings include the importance of the game, the outcome of the game, the expected result of the game, and the goal differential of the game when calculating a result. To better explain the way the rankings work I give you the following examples (all team start with a ranking of 1500):
Lindenwood University (1500) vs. UMSL (1500): If Lindenwood won the regular season game 4-3; they would be awarded 15 points for the victory and UMSL would be docked 15 points. However, if the game was won 12-2, Lindenwood would earn 39.38 points for the victory and UMSL would be docked 39.38 points. Additionally, the importance of the game could change, using the national title game as the example, with both teams having equal ratings Lindenwood would be awarded 52.5 points for a 6-3 win.
However, as you could assume, two teams having the same rating would be rare. Each teams point total carries over from one week to the next and from one season to the next. The following is a example of two teams with different point values and the different results it can produce.
Lindenwood University (1746.38) vs. Illinois State (1360.88): There are a few things that you can determine because of the vast difference in each teams rating (385.5). The first is that Lindenwood is expected to win the game. The second is that Illinois State winning the game would be a much bigger accomplishment that Lindenwood winning the game. The maximum points Lindenwood can earn from this game is 7.72, which would mean they won by at least 10 goals. However, on the flip side, if Illinois State was to win the game by at least 10 goals they could earn as many as 71.03 points. This is based on the projection that Lindenwood would win the match-up 90% of the time.
As the two examples show, there are a bunch of positives when using this system. For starters, once a team has achieved a high rating, it becomes difficult for them to increase it without playing a higher level of competition. This rewards regions that have more competitive teams. It also rewards teams who travel out of the region and win games against other higher rated teams. For example, last season, Towson and Army both played James Madison who would have had a higher rating that both visiting teams. In the games, Army and Towson both won handily and would have increased their ratings while negatively hurting James Madison. But, the hidden bonus is they now can bring those rating points back into their region. Those points then become spread out over the entire region as the season progresses and teams win and lose.
For the ratings system to work, each game has to have a certain amount of value attached to it. In the system we will be using five different levels to rate the importance of any give game. The first level is the lowest level of importance; it contains all pre-season exhibition games. The second level includes all regular-season regional games, as well as cross-divisional exhibition games. Level three includes all cross-regional games and invitational based tournaments, like WinterFest. The fourth level includes all regional playoff games and the fifth and final level includes all national playoff games.
6 comments:
Long Beach is actuall 14-2-2 not 13-3-2
Long Beach State wins their final 5 games including beating Davis who beat undefeated UC Irvine and they drop in the rankings?
It's a subjective poll man, you have three people who move someone ahead of you, you tend to fall...
I don't understand the love for Cal Poly SLO. UNLV is 8-2-0 in their last 10, have a better record than SLO, and beat SLO 9-3 last meeting.
I would think SLO would be below UNLV, and also below UC Davis, who is 8-1-3 in their last 12, and beat SLO last meeting too.
PS- UC Irvine is 17-1-0, not 17-1-1
BTW, SLO is 5-3-2 last 10.
I think UC Irvine tied San Diego State...
They are 17-1-1.
Thanks you.
The record for UC Irvine is correct. Every game a team plays in counted towards their overall record. Exhibition games or not, what they did in those games are reflected in our rankings.
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