Hey all
I just posted an article on Raps HQ with my annual statistical projection for the Raptors, plus projections for every team in the league. Feel free to go read it in full for a more detailed explanation of the process, but I'll put all the necessary info here anyway.
https://www.raptorshq.com/2017/8/1/1...ns-projections
The process is much the same as most years I do this, with a couple of tweaks. The goal, as ever, is to build this up with as little manual modification as possible - so none of my own opinion on rotations, minutes, roster construction comes into play at all. Player usage on each team is completely controlled by their minutes last year. And no assumptions are made on my part in terms of age decline, or young players getting better. Everyone is assumed to be the same player as last year, with the same usage, with only their minutes increased or decreased based on the team around them adding or removing high minutes players from last year.
1) Pull 2016-17 data for every player in league: total minutes played, WS/48, BPM, RPM
2) Compile team rosters (as of July 26th in this case) and check team minutes total against 19,800 (5x48x82).
3) Pro-rate player minutes to get correct minutes total for each team. Individual player cap at 3000 MP.
4) Multiply MP x WS/48 then divide by 48 to get total WS for each player.
5) Sum player WS's for each team to get team WS total.
6) Multiply BPM by MP for each player, divide by team MP, sum all player values for team average BPM.
7) Same for RPM.
8) Use pythagorean wins calculation using BPMx5 (and RPMx5) as point differential.
9) Calculate average win total for the entire league, adjust all teams up or down to ensure 41 win average.
10) Profit!
This results in 3 win predictions for each team. I'll present the Raptors in detail, and for league standings will use an average win total for each team with the three results equally weighted.
So, here is the individual player data for the Raptors.
Those numbers result in win predictions of 56 wins (by WS), 52 wins (by BPM), and 49 wins (by RPM).
As for the league as a whole:
Some of that seems right, other bits are somewhat whacky. I've got explanations for some outliers (Cavs in particular) in the piece, if you are interested. Or we can just discuss them here.
My big takeaways - if the Cavs do implode because of Kyrie, the Raptors seem as poised as anyone in the East to jump in to fill the void. And the East is awful - with 12 of the 15 West teams projected to finish with a better record than the 8th seed Knicks - and the Kings are soooo close to making it 13 of 15.
I just posted an article on Raps HQ with my annual statistical projection for the Raptors, plus projections for every team in the league. Feel free to go read it in full for a more detailed explanation of the process, but I'll put all the necessary info here anyway.
https://www.raptorshq.com/2017/8/1/1...ns-projections
The process is much the same as most years I do this, with a couple of tweaks. The goal, as ever, is to build this up with as little manual modification as possible - so none of my own opinion on rotations, minutes, roster construction comes into play at all. Player usage on each team is completely controlled by their minutes last year. And no assumptions are made on my part in terms of age decline, or young players getting better. Everyone is assumed to be the same player as last year, with the same usage, with only their minutes increased or decreased based on the team around them adding or removing high minutes players from last year.
1) Pull 2016-17 data for every player in league: total minutes played, WS/48, BPM, RPM
2) Compile team rosters (as of July 26th in this case) and check team minutes total against 19,800 (5x48x82).
3) Pro-rate player minutes to get correct minutes total for each team. Individual player cap at 3000 MP.
4) Multiply MP x WS/48 then divide by 48 to get total WS for each player.
5) Sum player WS's for each team to get team WS total.
6) Multiply BPM by MP for each player, divide by team MP, sum all player values for team average BPM.
7) Same for RPM.
8) Use pythagorean wins calculation using BPMx5 (and RPMx5) as point differential.
9) Calculate average win total for the entire league, adjust all teams up or down to ensure 41 win average.
10) Profit!
This results in 3 win predictions for each team. I'll present the Raptors in detail, and for league standings will use an average win total for each team with the three results equally weighted.
So, here is the individual player data for the Raptors.
Those numbers result in win predictions of 56 wins (by WS), 52 wins (by BPM), and 49 wins (by RPM).
As for the league as a whole:
Some of that seems right, other bits are somewhat whacky. I've got explanations for some outliers (Cavs in particular) in the piece, if you are interested. Or we can just discuss them here.
My big takeaways - if the Cavs do implode because of Kyrie, the Raptors seem as poised as anyone in the East to jump in to fill the void. And the East is awful - with 12 of the 15 West teams projected to finish with a better record than the 8th seed Knicks - and the Kings are soooo close to making it 13 of 15.
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