11-01-2019, 10:41 AM
(This post was last modified: 11-11-2019, 03:34 PM by Fordhammer.)
I don't intend to infringe upon the territory of resident Power Rankings maker @`Jackets28`, but I check his list each week he posts it and lately couldn't help but find myself disagreeing with a few rankings. I think what he's doing is interesting because it looks more at the process, like yardage for and against, rather than purely at results. But I couldn't help but feel looking purely at results would be an interesting approach. So I decided to do it.
I wanted to be as scientific about this as I could be, and I remembered that Bill James - who is mostly famous for baseball data analysis - has a formula he uses to make NFL power rankings. I won't even bother trying to walk through it because Bill does so quite a bit more effectively than I could anyway. The only significant changes I made were 1) making home field advantage worth 4.5 points (based on some other math I did) and 2) what I describe in the following paragraph. Anyway, here's the link breaking down the methodology: https://www.billjamesonline.com/article808/
I ran the loop for this a bunch of times but was noticing that the more I ran it, the lower every single team's rating moved. In fact, when I ran it 1000 times, every team wound up below their initial rating of 100. This may be in part because of our small league size. Or maybe I fucked up the code. But I looked at it enough to feel like it's not the latter. In any event, the changes became pretty minor from iteration to iteration after 50+ loops. I set it to run 100 times, but then made one small change from the link above. I kept the raw ratings, but I also wanted everything to expressed as a number above or below an average. So I divided all numbers by the league average rating and multiplied by 100 to get a "Rating+".
The two sets of rankings are displayed below. The raw ratings represent a better comparison if you're looking at two teams. As an example, Baltimore has a rating of 107.3 and Philadelphia has a rating of 102. So if you wanted to compare those teams you'd basically say Baltimore is 5.3 points better than Philadelphia. If you're looking at the scaled ratings, Baltimore sits at 102.7 versus Philadelphia's 97.7. In this case Baltimore is about 2.7% better than league average whereas Philadelphia is about 2.3% worse than league average. The differences between teams are fairly close to the raw system, but the scaled system is much cleaner in my opinion. But enough blabbing. The power rankings, thru week 10. It's Yellowknife's world and we're all just living in it.
Raw Ratings
Ranking - Team - Rating
1. Yellowknife Wraiths - 116.4
2. Orange County Otters - 109.5
3. Arizona Outlaws - 107.4
4. Baltimore Hawks - 107.3
5. Austin Copperheads - 105.0
6. Chicago Butchers - 103.1
7. Philadelphia Liberty - 102.0
8. New Orleans Second Line - 102.0
9. Colorado Yeti - 99.4
10. San Jose Sabercats - 92.5
Scaled Ratings
Ranking - Team - Rating
1. Yellowknife Wraiths - 111.4
2. Orange County Otters - 104.8
3. Arizona Outlaws - 102.8
4. Baltimore Hawks - 102.7
5. Austin Copperheads - 100.5
6. Chicago Butchers - 98.7
7. Philadelphia Liberty - 97.7
8. New Orleans Second Line - 97.6
9. Colorado Yeti - 95.2
10. San Jose Sabercats - 88.5
Predicting Week 11 Spreads
I thought it would be fun to try to guesstimate these as I have an approximation for how many points better any team given team is than another, as well as a rough number for home field advantage. All lines are expressed through the home team and are just calculated based on the difference in raw rating with an adjustment for HFA, rounded to the nearest "half-integer". For any unfamiliar with what these mean, a -19 means the team is favored by 19, a +6 means the team is a six point underdog.
@ : Wraiths -19
@ : Yeti +1
@ : Outlaws -4.5
@ : Sabercats +6
@ : Second Line +3
I wanted to be as scientific about this as I could be, and I remembered that Bill James - who is mostly famous for baseball data analysis - has a formula he uses to make NFL power rankings. I won't even bother trying to walk through it because Bill does so quite a bit more effectively than I could anyway. The only significant changes I made were 1) making home field advantage worth 4.5 points (based on some other math I did) and 2) what I describe in the following paragraph. Anyway, here's the link breaking down the methodology: https://www.billjamesonline.com/article808/
I ran the loop for this a bunch of times but was noticing that the more I ran it, the lower every single team's rating moved. In fact, when I ran it 1000 times, every team wound up below their initial rating of 100. This may be in part because of our small league size. Or maybe I fucked up the code. But I looked at it enough to feel like it's not the latter. In any event, the changes became pretty minor from iteration to iteration after 50+ loops. I set it to run 100 times, but then made one small change from the link above. I kept the raw ratings, but I also wanted everything to expressed as a number above or below an average. So I divided all numbers by the league average rating and multiplied by 100 to get a "Rating+".
The two sets of rankings are displayed below. The raw ratings represent a better comparison if you're looking at two teams. As an example, Baltimore has a rating of 107.3 and Philadelphia has a rating of 102. So if you wanted to compare those teams you'd basically say Baltimore is 5.3 points better than Philadelphia. If you're looking at the scaled ratings, Baltimore sits at 102.7 versus Philadelphia's 97.7. In this case Baltimore is about 2.7% better than league average whereas Philadelphia is about 2.3% worse than league average. The differences between teams are fairly close to the raw system, but the scaled system is much cleaner in my opinion. But enough blabbing. The power rankings, thru week 10. It's Yellowknife's world and we're all just living in it.
Raw Ratings
Ranking - Team - Rating
1. Yellowknife Wraiths - 116.4
2. Orange County Otters - 109.5
3. Arizona Outlaws - 107.4
4. Baltimore Hawks - 107.3
5. Austin Copperheads - 105.0
6. Chicago Butchers - 103.1
7. Philadelphia Liberty - 102.0
8. New Orleans Second Line - 102.0
9. Colorado Yeti - 99.4
10. San Jose Sabercats - 92.5
Scaled Ratings
Ranking - Team - Rating
1. Yellowknife Wraiths - 111.4
2. Orange County Otters - 104.8
3. Arizona Outlaws - 102.8
4. Baltimore Hawks - 102.7
5. Austin Copperheads - 100.5
6. Chicago Butchers - 98.7
7. Philadelphia Liberty - 97.7
8. New Orleans Second Line - 97.6
9. Colorado Yeti - 95.2
10. San Jose Sabercats - 88.5
Predicting Week 11 Spreads
I thought it would be fun to try to guesstimate these as I have an approximation for how many points better any team given team is than another, as well as a rough number for home field advantage. All lines are expressed through the home team and are just calculated based on the difference in raw rating with an adjustment for HFA, rounded to the nearest "half-integer". For any unfamiliar with what these mean, a -19 means the team is favored by 19, a +6 means the team is a six point underdog.
@ : Wraiths -19
@ : Yeti +1
@ : Outlaws -4.5
@ : Sabercats +6
@ : Second Line +3