Newbie on basketball statistics

[josecarlos]

Hi!!!

I've got another question, this time about pace factor. I know how to calculate the pace factor for a team, but I don't know how can I do it for a player.

I have read that too much times people gives the pace factor of a team to every player of that team and this is not correct. So, how can I calculate pace factor for only one player?

Thanks in advance.

José Carlos

Anybody?

[Crow]

I provided an answer but it is hiding for some reason. Administrator notified. Owner to be notified. Friday 13th. Hope the issues are minor, not malicious and don't escalate.

[Crow]

If you want to do for a major league just find a site that gives total possessions on court and divide by minutes then multiply by 48. If doing for your Spanish women's league you may have to write code to count possessions from play by play data or count them manually. You could estimate possession from the total boxscore activity (counting the things that end possessions including team turnovers and minus offensive rebounds) that occurred while they are on court but you'd lose a bit of accuracy.

Check the definition of possession. It is different than a "play". An offensive rebounded ends a play but the possession is continued. Timeouts don't create new possessions. There is some extra details for "minor possessions" that you might find

[Crow]

recovered comment from josecarlos:

Right now I'm estimating possessions from total boxscore. I don't have access to play by play after the game has finished.

Thanks for your comment.

[josecarlos]

Thank you Crow for your help and patience with me!!!

[Crow]

You are welcome. Forum hasn't been that active in recent times.

[josecarlos]

Hi to everyone!!!

I've got any questions about stats, why not?

This first question is possible due to my lack of english, but I want to be sure that I'm understanding correctly the meaning of "Pace". When you say "The pace of a team" what you are saying is "The number of possessions of a tem"? So Pace = Number of Possessions?

Second question it's about win predictions. The formula is easy and there is no problem to understand it, but I want to know why a value is applicated to that formula and the value is "41". Is "41" because the regular season are 82 games?

And my third question is about PIE. In the form there are terms who makes reference to the "Game", like GmPts (Game Points), GmFGM (Game Field Goals Made), GmFTM (Game Free Throws Made), etc. I understand that when the form say Game Points, for example, are the sum of the points of the two teams, or when they say Game Field Goals Made, are the sum of the Game Fields Goals Made by the two teams, am I right? If I'm not right, please tell me what the meaning of GmPts, GmFGM, etc. If I'm right ... If I want to know the PIE of a player why I use data of the two teams?

And that's all!!! I hope to have been explained correctly all my doubts!!!

[josecarlos]

Excuse me, but I have another question about wins predictions.

The formula to calculate win predictions are: 2.54*(ORTG-DRTG)+41 ... And my question is ... when two or more teams has the same victory predictions, Is there any way to say which is first and which is second? Any other formula? Thanks in advance!!!

[Mike G]

(TmPts)^14/(TmPts^14 + OppPts^14) is also used to project Win%
Different exponents have been used, from 12 to 16.5
Pts can be total, per game, or per x possessions.
then
Win% * G = Wins

Pace is possessions per 48 minutes.
For a team, this is really the average of the team's inherent pace and their opponents' inherent pace(s).

I'm not aware of PIE, but it makes sense to scale a player's productions to the team and opponent.
In the 1960s, there were more than 100 rebounds per game. Now it's closer to 80. And there still are big variations from team to team. So 10 rebounds might be equivalent to 8 in another milieu.

[josecarlos]

(TmPts)^14/(TmPts^14 + OppPts^14) is also used to project Win%
Different exponents have been used, from 12 to 16.5
Pts can be total, per game, or per x possessions.
then
Win% * G = Wins

Pace is possessions per 48 minutes.
For a team, this is really the average of the team's inherent pace and their opponents' inherent pace(s).

I'm not aware of PIE, but it makes sense to scale a player's productions to the team and opponent.
In the 1960s, there were more than 100 rebounds per game. Now it's closer to 80. And there still are big variations from team to team. So 10 rebounds might be equivalent to 8 in another milieu.

Thank you Mike G for your answer!!!

I understand that the correct formula to predict the number of wins is Wins = Win% * G. What's the meaning of G? Total games played? Total games of the regular season, for example? Further, you say that exponents used are from 12 to 16.5. Which is the reason to select 14 or any other number from 12 to 16.5?

Thanks in advance!!!

[Mike G]

https://www.basketball-reference.com/about/

Pythagorean Wins; the formula is G * (Tm PTS14 / (Tm PTS14 + Opp PTS14)). The formula was obtained by fitting a logistic regression model with log(Tm PTS / Opp PTS) as the explanatory variable. Using this formula for all BAA, NBA, and ABA seasons, the root mean-square error (rmse) is 3.14 wins. Using an exponent of 16.5 (a common choice), the rmse is 3.48 wins. (Note: An exponent of 10 is used for the WNBA.)

A smaller exponent is used for a game with fewer possessions.
More poss. ==> more likely that the better team will win.

[josecarlos]

https://www.basketball-reference.com/about/

Pythagorean Wins; the formula is G * (Tm PTS14 / (Tm PTS14 + Opp PTS14)). The formula was obtained by fitting a logistic regression model with log(Tm PTS / Opp PTS) as the explanatory variable. Using this formula for all BAA, NBA, and ABA seasons, the root mean-square error (rmse) is 3.14 wins. Using an exponent of 16.5 (a common choice), the rmse is 3.48 wins. (Note: An exponent of 10 is used for the WNBA.)

A smaller exponent is used for a game with fewer possessions.
More poss. ==> more likely that the better team will win.

Thank you Mike G. I read that explanation last night. And I'm trying to make calculus based on the data that I've got and I don't get good results. I'm going to explain better. Right now, I only have the data of 5 games played of each team, I don't have an historic of games of each team preaviously loaded in my database. So, I'm trying to predict the total of wins of each team based on the data I have in my database, remeber, just only 5 games of each team. Am I wrong? Which data you use to make the victory predictions of the NBA regular season, for example? Do you use data from pre-season?

[josecarlos]

https://www.basketball-reference.com/about/

Pythagorean Wins; the formula is G * (Tm PTS14 / (Tm PTS14 + Opp PTS14)). The formula was obtained by fitting a logistic regression model with log(Tm PTS / Opp PTS) as the explanatory variable. Using this formula for all BAA, NBA, and ABA seasons, the root mean-square error (rmse) is 3.14 wins. Using an exponent of 16.5 (a common choice), the rmse is 3.48 wins. (Note: An exponent of 10 is used for the WNBA.)

A smaller exponent is used for a game with fewer possessions.
More poss. ==> more likely that the better team will win.

Thank you Mike G. I read that explanation last night. And I'm trying to make calculus based on the data that I've got and I don't get good results. I'm going to explain better. Right now, I only have the data of 5 games played of each team, I don't have an historic of games of each team preaviously loaded in my database. So, I'm trying to predict the total of wins of each team based on the data I have in my database, remeber, just only 5 games of each team. Am I wrong? Which data you use to make the victory predictions of the NBA regular season, for example? Do you use data from pre-season?

Anyone?

[josecarlos]

Hi all!!!

- ¿Which advanced stats do you consider that are better to know what are the best teams and players in attack and defense?
- If you want to compare two or more players to decide which one is better. ¿which stats do you will use?

Thanks in advance!!!

[Crow]

If you can compute the overall offensive and defensive efficiencies, that is a start. If you can compute the "4 factors" (efg%, oR%, turnover%, ftm/fga for offense and "allowed" by defense), that gives you more information. You can compare offensive factor to defensive factor and say where the advantages and disadvantages may be in the matchup on both sides of the court..

With players you can compare all the separate statistics you have and / or compare the roll-up (PER, winshares per 48 or whatever you are using).

Stats have different levels of importance, so pay attention to the importance of the stat (size of scoreboard impact, direct or indirect) as well as the size of any differences on that stat.