03-04-2020, 07:59 PM
(This post was last modified: 03-04-2020, 08:00 PM by speculadora.)
Hello, I noticed some particularly... "interesting" season predictions out there and thought maybe I could help you put some numbers behind your decisions. Welcome to my hacky little article that will predict probably nothing.
So, all I did was copy all the players from the TPE Tracker to get this data. You can toggle columns and it copy pastes into Excel quite nicely. For this first bit though I'll just be looking at the Team Stats tab.
Season Predictions: Total TPE Method
NSFC
1. (12,253)
2. (11,563)
3. (10,983)
---
4. (10,733)
5. (8,930)
ASFC
1. (13,946)
2. (11,865)
3. (11,025)
---
4. (9,185)
5. (7,955)
Overall
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Season Predictions: Average TPE Method
NSFC
1. (644)
2. (642)
3. (596)
---
4. (549)
5. (496)
ASFC
1. (697)
2. (593)
3. (551)
---
4. (459)
5. (418)
Overall
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Now for the part where I do a bunch of arbitrary stuff. As we know, most of us at least, not all positions are created equal in DDSPF. Having very good players at some will influence your outcomes far more than others. Some of these weren't exactly easy to put numbers on so don't hammer away at your keyboards debating with me. Obviously MLB and SLB aren't equal, but I'm not trying to go into a whole huge thing here, so I considered them both for one position and that brought the weight I applied to LB's down.
Here's a breakdown of the weights I applied to each position. Again these are generalized and somewhat opinion based. Please don't fight me. Scale goes from 1 (each additional TPE less impactful) to 5 (each additional TPE more impactful)
QB: 5
RB: 2
WR: 4
TE: 3
OL: 1
DT: 3
DE: 2
LB: 2
CB: 5
S: 3
K/P: 1
So anyway. Every team's average TPE for that position was multiplied by the weight, then divided by the sum of the weights.
Season Predictions: Weighted TPE Method
NSFC
1. (751.9)
2. (704.2)
3. (669.2)
---
4. (546.7)
5. (533.6)
ASFC
1. (696.1)
2. (692.9)
3. (665.2)
---
4. (533.6)
5. (490.5)
Overall
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
So there you have it. I found a way to predict OCO will win the conference.
But to discuss a more relevant point: basically what you see is that although the Wraiths trail the Yeti in other metrics, Yellowknife have their TPE very very well distributed across the different positions. Like weirdly well. Hopefully this last bit has confused you enough to ignore me.
So, all I did was copy all the players from the TPE Tracker to get this data. You can toggle columns and it copy pastes into Excel quite nicely. For this first bit though I'll just be looking at the Team Stats tab.
Season Predictions: Total TPE Method
NSFC
1. (12,253)
2. (11,563)
3. (10,983)
---
4. (10,733)
5. (8,930)
ASFC
1. (13,946)
2. (11,865)
3. (11,025)
---
4. (9,185)
5. (7,955)
Overall
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Season Predictions: Average TPE Method
NSFC
1. (644)
2. (642)
3. (596)
---
4. (549)
5. (496)
ASFC
1. (697)
2. (593)
3. (551)
---
4. (459)
5. (418)
Overall
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Now for the part where I do a bunch of arbitrary stuff. As we know, most of us at least, not all positions are created equal in DDSPF. Having very good players at some will influence your outcomes far more than others. Some of these weren't exactly easy to put numbers on so don't hammer away at your keyboards debating with me. Obviously MLB and SLB aren't equal, but I'm not trying to go into a whole huge thing here, so I considered them both for one position and that brought the weight I applied to LB's down.
Here's a breakdown of the weights I applied to each position. Again these are generalized and somewhat opinion based. Please don't fight me. Scale goes from 1 (each additional TPE less impactful) to 5 (each additional TPE more impactful)
QB: 5
RB: 2
WR: 4
TE: 3
OL: 1
DT: 3
DE: 2
LB: 2
CB: 5
S: 3
K/P: 1
So anyway. Every team's average TPE for that position was multiplied by the weight, then divided by the sum of the weights.
Season Predictions: Weighted TPE Method
NSFC
1. (751.9)
2. (704.2)
3. (669.2)
---
4. (546.7)
5. (533.6)
ASFC
1. (696.1)
2. (692.9)
3. (665.2)
---
4. (533.6)
5. (490.5)
Overall
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
So there you have it. I found a way to predict OCO will win the conference.
But to discuss a more relevant point: basically what you see is that although the Wraiths trail the Yeti in other metrics, Yellowknife have their TPE very very well distributed across the different positions. Like weirdly well. Hopefully this last bit has confused you enough to ignore me.