You know, I didn't ask. I assumed OFF IQ in the OFF REB equation and vice versa.Posted by hughesjr on 11/26/2012 2:38:00 PM (view original):Which IQ, DEF, OFF, or Both?Posted by Trentonjoe on 11/26/2012 2:28:00 PM (view original):About rebounding, I asked a while ago in a developed chat (last summer maybe?) specifically what goes into the REBOUNDING Equation and admin said ATH, REB and IQ.Posted by hughesjr on 11/26/2012 2:04:00 PM (view original):

Rebounding: REB 63%, ATH 32%, SPD 5%

Def: DEF 50%, ATH 20%, SPD 5%, BLK 10%, DEF_IQ 15%

Ball Handing: ATH 10%, SPD 10%, BH 40%, PASS 40%

in this one, i am definitely in the camp that thinks, rating values change significantly based on the ratings of the player, his role, his team, and his opponents. but i think you are going a bit overboard in your division of slashers. ath outweights spd by too much in all of them, and in no scenario does a scorer value ath anywhere near 12x lp and per. your bh is too high for all of them, too, IMO.Posted by hughesjr on 11/26/2012 1:58:00 PM (view original):

Offensive TypesATHSPDLPPEBHIQTotalLP 0.30 0.05 0.45 0.05 0.05 0.10 1.00 Balanced 0.20 0.10 0.20 0.20 0.20 0.10 1.00 PE 0.12 0.10 0.05 0.43 0.20 0.10 1.00 SlasherPE 0.30 0.08 0.05 0.17 0.30 0.10 1.00 SlasherLP 0.30 0.06 0.18 0.06 0.30 0.10 1.00 SlasherATH 0.38 0.08 0.03 0.03 0.38 0.10 1.00

just in general, i think you value speed too little. its incredibly valuable on the perimeter. and for any offense type, you should never have these 10:0 lp/per disparities. for your most post oriented center, lp might be 3-4x per, and for your most 3 point oriented scorer, per might be 3-4x lp. but thats as far as i can see it going.

good assumptionPosted by Trentonjoe on 11/26/2012 2:53:00 PM (view original):You know, I didn't ask. I assumed OFF IQ in the OFF REB equation and vice versa.Posted by hughesjr on 11/26/2012 2:38:00 PM (view original):Which IQ, DEF, OFF, or Both?Posted by Trentonjoe on 11/26/2012 2:28:00 PM (view original):About rebounding, I asked a while ago in a developed chat (last summer maybe?) specifically what goes into the REBOUNDING Equation and admin said ATH, REB and IQ.Posted by hughesjr on 11/26/2012 2:04:00 PM (view original):

Rebounding: REB 63%, ATH 32%, SPD 5%

Def: DEF 50%, ATH 20%, SPD 5%, BLK 10%, DEF_IQ 15%

Ball Handing: ATH 10%, SPD 10%, BH 40%, PASS 40%

In this case, I basically run all 6 scenario's against each player ... the maximum overall rating of the 6 is what I say is the player's overall offensive rating.Posted by coach_billyg on 11/26/2012 2:55:00 PM (view original):in this one, i am definitely in the camp that thinks, rating values change significantly based on the ratings of the player, his role, his team, and his opponents. but i think you are going a bit overboard in your division of slashers. ath outweights spd by too much in all of them, and in no scenario does a scorer value ath anywhere near 12x lp and per. your bh is too high for all of them, too, IMO.Posted by hughesjr on 11/26/2012 1:58:00 PM (view original):

Offensive TypesATHSPDLPPEBHIQTotalLP 0.30 0.05 0.45 0.05 0.05 0.10 1.00 Balanced 0.20 0.10 0.20 0.20 0.20 0.10 1.00 PE 0.12 0.10 0.05 0.43 0.20 0.10 1.00 SlasherPE 0.30 0.08 0.05 0.17 0.30 0.10 1.00 SlasherLP 0.30 0.06 0.18 0.06 0.30 0.10 1.00 SlasherATH 0.38 0.08 0.03 0.03 0.38 0.10 1.00

just in general, i think you value speed too little. its incredibly valuable on the perimeter. and for any offense type, you should never have these 10:0 lp/per disparities. for your most post oriented center, lp might be 3-4x per, and for your most 3 point oriented scorer, per might be 3-4x lp. but thats as far as i can see it going.

What I am trying to capture is the fact that high ATH and low PE/LP guys can score too ... but most of the time, it is LP, Balanced, or PE that is the higher score. There are some players where the SlasherATH may be the higher number, but not many.

I will look at SPD a bit more on the Perimeter.

Well, it is a computer game that works only with numbers ... how else would you come up with a rating for a player other than to weight what you think makes up 100% of the number the computer will use?Posted by dahsdebater on 11/26/2012 3:22:00 PM (view original):

At the end of the day I think you can only do a mediocre job, at best, trying to encapsulate offensive or defensive value in any formula that just adds ratings together.

By doing it this way, all your overall scores in any area will be in the range of 0-100 when comparing them to each other.

what you are describing is effectively, adding the ratings together. you are normalizing to a scale but thats not really the point.Posted by hughesjr on 11/26/2012 3:33:00 PM (view original):

BTW, it is not just adding numbers together ... it is taking 100%, splitting that up into component parts, multiplying that percentage against the attribute, and adding those corrected values together.

By doing it this way, all your overall scores in any area will be in the range of 0-100 when comparing them to each other.

to come up with the "right" formulas, dahs is right, adding definitely does not do the job. i wrote myself a program, similar to yatzr's but trimmed down, so i could rank recruits by custom formulas and recruit off it - although it was more about being able to play with the formulas, than actually recruiting (and i never really used it to recruit, but i played with formulas a **** ton). you minimally need cross products. for example, as we've been discussing, if you have good ath, lp is more valuable. if you have good spd, per is more valuable. so, to really capture the detail - you need an offense equation that would be something like-

3 point shooting = a*ATH + b*SPD + c*PER + d*BH + e*SPD*PER + f*BH*PER

ok ... whatever you say :)Posted by dahsdebater on 11/26/2012 3:36:00 PM (view original):

Well, back when I ran the big regression I did on defense a few years ago, I wanted to simplify it to the smallest possible number of variables that would still provide any meaningful information. I got much better power out of the equation FG% = Const - k*(ATH^a)*(SPD^b)*(DEF^c)*(BLK^d) than FG% = Const - k*[a*ATH + b*SPD + c*DEF + d*BLK], which suggests to me that multiplying ratings is probably far more meaningful an exercise than adding them. It seems to me that things work somewhat similarly on offense, although added terms might be a little more important on offense than on d, where adding all possible terms only increased the regression power fairly marginally over only the quartic term.

Billy ... what is factor 'e' and factor 'f'Posted by coach_billyg on 11/26/2012 4:05:00 PM (view original):what you are describing is effectively, adding the ratings together. you are normalizing to a scale but thats not really the point.Posted by hughesjr on 11/26/2012 3:33:00 PM (view original):

BTW, it is not just adding numbers together ... it is taking 100%, splitting that up into component parts, multiplying that percentage against the attribute, and adding those corrected values together.

By doing it this way, all your overall scores in any area will be in the range of 0-100 when comparing them to each other.

to come up with the "right" formulas, dahs is right, adding definitely does not do the job. i wrote myself a program, similar to yatzr's but trimmed down, so i could rank recruits by custom formulas and recruit off it - although it was more about being able to play with the formulas, than actually recruiting (and i never really used it to recruit, but i played with formulas a **** ton). you minimally need cross products. for example, as we've been discussing, if you have good ath, lp is more valuable. if you have good spd, per is more valuable. so, to really capture the detail - you need an offense equation that would be something like-

3 point shooting = a*ATH + b*SPD + c*PER + d*BH + e*SPD*PER + f*BH*PER

I am doing the a*ATH+b*SPD+c*PER+d*BH

Now if you effectively define (the way you are describing) a, b, c, d ... and if none of the other attributes matter, you would add those up and they would equal 100.

What would the e*SPD*PER do that you could not do with b*SPD and c*PER ?

Also think I may be doing the same thing by having 5 different "offensive types" ... in one type LP and ATH are very important and in the other type, PER and SPEED are more important. Which ever number is higher (between those types) would be how that player is rated ... I'll post an example

i really don't know what you did, to be honest, but as ive mentioned, i wholeheartedly disagree with many of the conclusions you drew from your regression analysis. i talked to a guy who knows statistics better than me, who did some regressions, and what he explained he was doing, it gave me a warmer feeling than when you explained it to me a year or two ago or whatever. i asked him specifically about the shot blocking and value of ratings on defense stuff, and he reached TOTALLY different conclusions than you, ones than sounded A LOT more accurate to me. so, im really not sure what you did, ive never really followed why you are doing a regression of ATH^a * SPD^b ...., i don't think that is a model that WIS uses, and thus, I don't see the value in the coefficients you derive from the regression. also, for what its worth, the guy i was talking to who knows the details of statistics way better than me, generally agreed with the reason i had for why those coefficients weren't very useful, and he went further, providing even more reasons. it was pretty interesting, it restored my faith in the ability of statistical models to reach somewhat useful conclusions regarding the value of HD ratings, while also confirming and extending my beliefs that you cannot view those coefficients as perfect representations of the values of ratings.Posted by dahsdebater on 11/26/2012 3:36:00 PM (view original):

Well, back when I ran the big regression I did on defense a few years ago, I wanted to simplify it to the smallest possible number of variables that would still provide any meaningful information. I got much better power out of the equation FG% = Const - k*(ATH^a)*(SPD^b)*(DEF^c)*(BLK^d) than FG% = Const - k*[a*ATH + b*SPD + c*DEF + d*BLK], which suggests to me that multiplying ratings is probably far more meaningful an exercise than adding them. It seems to me that things work somewhat similarly on offense, although added terms might be a little more important on offense than on d, where adding all possible terms only increased the regression power fairly marginally over only the quartic term.

anyway, just wanted to pass that along, i was very surprising by your BLK conclusions, and was happy to hear another person reached a different conclusion on a similar attempt. but it made me think that you might be making a mistake, or else, had something different going into your model that was causing your problem.

Offensive Ratings |
Defensive Ratings |
||||||||||||||||||||||||||||||||||||||

Pos |
Yr. |
Starters |
GS |
ATH |
SPD |
REB |
DE |
BLK |
LP |
PE |
BH |
P |
ST |
FG% |
FG3% |
FT% |
MIN |
PTS |
REB |
AST |
BLK |
STL |
TO |
PF |
R |
BH |
O |
D |
LP |
Balanced |
PE |
SlasherPE |
SlasherLP |
SlasherATH |
LP |
PE |
Balanced |
||

PG1 | Sr. | David Vanover | 9 | 61 | 73 | 18 | 56 | 13 | 61 | 74 | 69 | 66 | 76 | 47.0% | 34.3% | 67.4% | 26.0 | 13.4 | 2.4 | 3.6 | 0.1 | 1.2 | 1.8 | 2.1 | 37 | 69 | 72 | 65 | 66 | 70 | 72 | 70 | 68 | 68 | 56 | 65 | 60 | ||

SG1 | So. | Jim Teuteberg | 9 | 62 | 62 | 1 | 69 | 2 | 2 | 73 | 57 | 63 | 69 | 40.5% | 41.9% | 52.9% | 23.3 | 6.2 | 0.4 | 2.7 | 0.0 | 1.1 | 1.7 | 1.9 | 26 | 62 | 65 | 68 | 37 | 53 | 65 | 61 | 52 | 61 | 59 | 68 | 63 | ||

SF1 | So. | George Rees | 9 | 63 | 68 | 24 | 75 | 14 | 41 | 44 | 52 | 64 | 70 | 41.7% | 0.0% | 59.1% | 23.7 | 3.7 | 3.1 | 1.7 | 0.3 | 1.1 | 1.4 | 1.6 | 41 | 62 | 60 | 73 | 54 | 56 | 54 | 58 | 57 | 60 | 65 | 73 | 68 | ||

PF1 | Jr. | James Golub | 9 | 68 | 35 | 90 | 64 | 62 | 87 | 8 | 26 | 26 | 67 | 52.4% | 0.0% | 79.4% | 22.8 | 12.8 | 7.0 | 0.4 | 0.6 | 0.3 | 1.3 | 2.0 | 83 | 35 | 72 | 67 | 72 | 50 | 33 | 45 | 55 | 50 | 67 | 61 | 64 | ||

C1 | Jr. | Brian Harvey | 9 | 75 | 19 | 83 | 66 | 83 | 45 | 16 | 17 | 20 | 66 | 53.8% | 0.0% | 72.7% | 22.1 | 6.4 | 6.0 | 0.4 | 1.0 | 0.7 | 1.7 | 1.7 | 81 | 28 | 54 | 72 | 54 | 41 | 32 | 42 | 46 | 47 | 72 | 60 | 66 |

On defense, I now have 3 types, LP, PE, Balanced ... his best defense is PE, rated at 65.

So, basically there are 5 choices for an Offensive rating and 3 choices for a defensive rating.

Right now, I use these percentages for them:

Offensive Types |
ATH |
SPD |
LP |
PE |
BH |
IQ |
Total |

LP | 0.30 | 0.05 | 0.45 | 0.05 | 0.05 | 0.10 | 1.00 |

Balanced | 0.20 | 0.10 | 0.20 | 0.20 | 0.20 | 0.10 | 1.00 |

PE | 0.12 | 0.10 | 0.05 | 0.43 | 0.20 | 0.10 | 1.00 |

SlasherPE | 0.30 | 0.08 | 0.05 | 0.17 | 0.30 | 0.10 | 1.00 |

SlasherLP | 0.30 | 0.06 | 0.18 | 0.06 | 0.30 | 0.10 | 1.00 |

SlasherATH | 0.38 | 0.08 | 0.03 | 0.03 | 0.38 | 0.10 | 1.00 |

Defensive Types |
ATH |
SPD |
DE |
BLK |
IQ |
Total |

LP | 0.17 | 0.02 | 0.50 | 0.16 | 0.15 | 1.00 |

PE | 0.11 | 0.22 | 0.50 | 0.02 | 0.15 | 1.00 |

Balanced | 0.12 | 0.13 | 0.50 | 0.10 | 0.15 | 1.00 |

I am not saying i am a genius or anything ... in fact I am asking others what they think makes up a good PE Defense, LP Defense, maybe a Balanced Defense

In my example, a perimeter defense would be 0.11*ATH + 0.22*SPD + 0.5*DEF + 0.02*BLK + 0.15*DEF_IQ

and a LP defense would be 0.17*ATH + 0.02*SPD + 0.5*DEF + 0.16*BLK + 0.15*DEF_IQ

Again, in the case of Vanover, his perimeter defense is 65 but his LP defense is 56.

Billy, this is exactly what you did when you rated the PGs on the first page and said: 10% ATH, 30% SPD, 25% BH, 35% PASS ... if you took .1*ATH + .3*SPD + .25*BH + .35*PASS then that total would be YOUR rating for PGs. The only difference is, I am creating 5 offense types and 3 defensive types. I am also, like Trentonjoe, asking people what percentages of each attribute they think are important for each Position and also for each type ... am I missing some types, etc.