About the Free Throw Shooting Influence on End Result & the Weighted Standard Deviation
and Basketball Actuality News Video in our Thursday's Basketball Statistics Referred Concepts
Basketball Statistics Referred Concepts:
About the Free Throw Shooting Influence on End Result
"... In what manner free throw shooting have an influence on the end result of games ? ..."
Let's take to be true, for example, that both teams had converted all of their free throws, or the losing team convert all of its free throws and the winning team convert the same number of free throws.
How all these data is performed statistically to the end ?
Here are some numbers from the archives of the eBA Basketball Statistics Creative Analysis System:
1.- The average number of free throws attempted in a game is about 25 per game.
2.- The shooting average is about 75% efficiency.
3.- That implies as a possibility that a 1% upward would make an actual deviation in FTM once every 4 games (see 1.-: teams shoot 25 FTA per game), translated in only one point every four games.
4.- Teams win by one point 5% of the total of games played.
5.- That 1% upward in FT% would tell us that 25% of these 1-point wins would instead go to overtime.
6.- And finally, to go on with discussion, that 1% FT% upward give us a win on 5% * 25% * 50% = 0.6% of the team's games, or 0.5 current games: that's means one additional win every two seasons.
What about the free throws analysis and the weighted standard deviation ?
Performing this calculation we must not mistake precision with accuracy. Nonparametric elements like percentiles make no hypothesis that is taken for granted about the shape of the distribution: they are more cautious measures and much less likely to return errors at the the highest degrees.
If you're searching leaders in a category, basketball free throws for example, I recommend you to always use nonparametric measures with a common plan with parametric measure, merely to be sure there are no outliers into your results.
The weighted standard deviation doesn't succeed in seizing the unfairness between two players with the same rates at free throws percentage ( as in all the other categories ) in different quantities of playing time.
Same rate is as if: that rate and no more. What it would succeed in catching is a significant change between the width of the distributions, having an effect upon the standard scores. The differences between player rates would be involved, but not if they have the same rate.
When analyzing free throws numbers ( or any other range ) with measures that aren't well fully apprehended, I give preference to study at the numbers from multiple angles. In this case which you propose at your question, I would perform the computations using
2. Standard deviation
3. Weighted Standard deviation by minutes
4. Weighted Standard deviation by square root (minutes per game)
and examine and note the similarities or differences of them. There shouldn't be much significant change, but it would be holding the attention if there was.
in the current Basketball Statistics eBA Clinics.
Read More at eBA CLINICS ONLINE, search "basketball statistics" in this blog and consult the Chapter eBA Basketball Possessions Analysis.
This topic is resumed in the eBA Basketball Statistics Creative Analysis System and at the eBA Encyclopedia.
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