Fightin Choke
Golden Dome Fan
- Joined
- May 10, 2012
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So I wanted to create a composite ranking of teams using computer ranking systems, as 538 does when creating their NCAA Tournament model. They used Sagarin, Massey, LRMC (Bayesian version), and Sonny Moore last season, but as we stats geeks know, Sagarin ratings are no longer available for WCBB. As a less than excellent fill-in, I decided to use RPI. Why? Because I'm not really trying to determine winners (which RPI is not designed for anyway), but rather trying to determine an S-curve for tournament seeding (and so this is my nod to the NCAA Tournament Committee's reliance on RPI). As an aside, if I were trying to determine winners, I would certainly have included Massey's Power Rating, which his model uses to predict games. Instead, I used the regular Massey Rating.)
I didn't want the huge task of collecting all the data for all 300+ teams, or even the top 50 teams, so I only included teams that were top 25 in at least 1 of the 4 systems. If I team were top 25 in at least one system, then I collected their data for the other systems as well. For example, Michigan St. was 25th in LRMC, but was not top 25 in any other systems. Thus I looked up their data is the other three systems anyway, so their data weren't incomplete. Here are the composite rankings, where I averaged the ranks for each team and then ordered them from lowest to highest. By the way, just because Michigan State is the 32nd team on my list does NOT mean that they are the 33rd best team, as there are probably others that weren't top 25 in any system that have composite rankings that are higher than the Spartans.
One last caveat: I didn't look at good wins or bad losses, but the committee will surely do that. Of course you can use this composite to see the average rank of teams to help gauge good wins and bad losses.
So on to the data!
But I wasn't satisfied because Notre Dame still wasn't high enough for me, so I tried another variation. But since I cannot attach more than 1 file in a post, I will cover that in my subsequent post.
I didn't want the huge task of collecting all the data for all 300+ teams, or even the top 50 teams, so I only included teams that were top 25 in at least 1 of the 4 systems. If I team were top 25 in at least one system, then I collected their data for the other systems as well. For example, Michigan St. was 25th in LRMC, but was not top 25 in any other systems. Thus I looked up their data is the other three systems anyway, so their data weren't incomplete. Here are the composite rankings, where I averaged the ranks for each team and then ordered them from lowest to highest. By the way, just because Michigan State is the 32nd team on my list does NOT mean that they are the 33rd best team, as there are probably others that weren't top 25 in any system that have composite rankings that are higher than the Spartans.
One last caveat: I didn't look at good wins or bad losses, but the committee will surely do that. Of course you can use this composite to see the average rank of teams to help gauge good wins and bad losses.
So on to the data!
But I wasn't satisfied because Notre Dame still wasn't high enough for me, so I tried another variation. But since I cannot attach more than 1 file in a post, I will cover that in my subsequent post.