Leftos wrote:UPDATE: Okay, so here's what I've got so far. Tell me what you think.
FG%: At least 4 FGM, normalizing factor FG% .548
3P%: At least 2 3PM, normalizing factor 3P% .398
FT%: At least 4 FTM, normalizing factor FT% .868
OREB: Normalizing factor 2.894
DREB: Normalizing factor 6.348
REB: Normalizing factor 9
AST: Normalizing factor 6.359
STL: Normalizing factor 1.673
BLK: Normalizing factor 1.731
PTS: Normalizing factor 20.104
Ok, I was thinking more of along the lines of PER, as I have never seen the equation for game score until now.NovU wrote:He's planning to use the Game Score metric to choose the best players for each game. I don't think 5 minutes player would become the player of the game that often.
Nick wrote:What happens if no players reach these numbers?
Pdub wrote:Ok, I was thinking more of along the lines of PER, as I have never seen the equation for game score until now.NovU wrote:He's planning to use the Game Score metric to choose the best players for each game. I don't think 5 minutes player would become the player of the game that often.
Game Score; the formula is PTS + 0.4 * FG - 0.7 * FGA - 0.4*(FTA - FT) + 0.7 * ORB + 0.3 * DRB + STL + 0.7 * AST + 0.7 * BLK - 0.4 * PF - TOV. Game Score was created by John Hollinger to give a rough measure of a player's productivity for a single game. The scale is similar to that of points scored, i.e., 40 is an outstanding performance, 10 is an average performance, etc.
Pdub wrote:Nick wrote:What happens if no players reach these numbers?
I don't think the normalizing factor is a baseline minimum. Or maybe the normalizing factor is for choosing the different statistics to display.
So with -
STL: Normalizing factor 1.673
BLK: Normalizing factor 1.731
and the top performer of the game has 2 blocks and 2 steals but the program can only choose one of those categories, I guess the steals would show up because the normalizing factor is lower.
Pdub wrote:Is the normalizing factor your scaling system so a player with 5 minutes ,10 points, 3 assists, and 2 steals doesn't end up the player of the game after putting up an amazing game score?
I am also interested to know what metric will be used for the multiple games.
if made at least | Guards | Forwards | Centers | |
FG% | 4 | 0.487 | 0.528 | 0.529 |
3P% | 2 | 0.393 | 0.380 | 0.230 |
FT% | 4 | 0.862 | 0.826 | 0.753 |
OREB | 1.242 | 2.671 | 2.328 | |
REB | 4.153 | 8.145 | 7.431 | |
AST | 6.324 | 3.037 | 1.688 | |
STL | 1.619 | 1.209 | 0.680 | |
BLK | 0.424 | 1.240 | 1.536 | |
PTS | 17.160 | 17.731 | 11.616 |
NovU wrote:Pace as in significance/insignificance of the plays or defensive role or plus minus ratings.
I don't think it's a bad metric but there are some flaws there as opposed to John Hollinger's claim.
NovU wrote:My recommendation would be something like WAR. It's a new metric
Great job on your part going distance to get the datas from B-R. It was not an easy task to do so I believe.
Leftos wrote:I based my analysis on BasketballReference's box score page (here's a sample), which as you can see, has no efficiency metrics.
so if the user doesn't keep track of all teams and players correctly and fully, PER will surely be off.
The final step is to standardize aPER. First, calculate league average aPER (lg_aPER) using player minutes played as the weights.
And about needing only the teams for the PER calculation, how about this part of the Calculating PER guide?
Is there an easier way to do this?
benji wrote:Great job on your part going distance to get the datas from B-R. It was not an easy task to do so I believe.
Can you copy-paste? Because that's all you need to get data off B-R.
Parsing is faster but if you don't know how to do it, copy-paste is faster. 82games.com is the hard one to get data off of for me because of that.
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