Men vs Women

Here is the idea. Let's make the hypothesis that the unknown distributions of talent (potential) for men and women look like this. That is, in a universe where equal numbers of men and women play and train and there are no social factors, the distribution of skill for men and women are shifted by half a standard deviation, about 50 points. This is a combined result perhaps from differences in strength, focus, coordination...whatever.

We don't have these distributions. But we do have information that might relate to the shapes of the tails of these distributions, the circled region. If our hypothesis is right and the top men and women are sampling from the tails of these distributions, then we should notice the fraction of women falling as we go from 2 to 2.5 to 3 to 3.5 here because we hyphothesise the women's distribution falls off faster.

That's not what we see. Of the top 100 established ratings 3 are women. Of the top 1000, 43 are women. The ratio stays pretty constant throughout the tail. That's a problem for our hypothesis, and a better hypothesis is the players are selected from distributions that are not shifted.

View attachment 728108
Is a normal distribution an accurate representation? I would figure a Chi-squared type thing with a far left hand lean in the curve. If 500 is the median, I would suspect far more 400's than 600's, and a gargantuan number of 300's vs. 700's.

Out of curiosity, this is theprobability density function of males and females in my 2 APA leagues combined (total n=100 and removing 1 version of myself as a duplicate).

Selection ratio: (men:women) 3.76:1

SL-2: 5 Women, 0 Men
SL-3: 8 Women, 15 Men
SL-4: 4 Women, 21 Men
SL-5: 4 Women, 26 Men
SL-6: 0 Women, 12 Men
SL-7: 0 Women, 4 Men

Overall Average SL: Men 4.58, Women: 3.33

Interestingly, my Tuesday league plays out of bars and my Wednesday league plays out of a more formal pool environment,

Tuesday Female Average SL: 3.0, Wednesday Female Average SL: 3.64
 
It takes the same amount of power to move the CB the same speed no matter how heavy the cue is (a slower moving heavier cue and a faster moving lighter cue can deliver the same force to the CB).

pj
chgo

No, that is false. It takes more input power (energy) by the user if the cue stick is heavier.

The same amount of energy is transferred to the ball, but more energy is retained by the cue after the collision. Pretty basic conservation of momentum principal.
 
Is a normal distribution an accurate representation? I would figure a Chi-squared type thing with a far left hand lean in the curve. If 500 is the median, I would suspect far more 400's than 600's, and a gargantuan number of 300's vs. 700's.

Out of curiosity, this is theprobability density function of males and females in my 2 APA leagues combined (total n=100 and removing 1 version of myself as a duplicate).

Selection ratio: (men:women) 3.76:1

SL-2: 5 Women, 0 Men
SL-3: 8 Women, 15 Men
SL-4: 4 Women, 21 Men
SL-5: 4 Women, 26 Men
SL-6: 0 Women, 12 Men
SL-7: 0 Women, 4 Men

Overall Average SL: Men 4.58, Women: 3.33

Interestingly, my Tuesday league plays out of bars and my Wednesday league plays out of a more formal pool environment,

Tuesday Female Average SL: 3.0, Wednesday Female Average SL: 3.64
I’ve read that the APA starts women as a 2 and men as a 3. If that is true, you’d want to control for that since it’s based on assumptions.
 
I’ve read that the APA starts women as a 2 and men as a 3. If that is true, you’d want to control for that since it’s based on assumptions.
They’ve changed that a few years back to where everyone starts as a 3 regardless of gender, and you basically don’t get demoted unless you really struggle making balls. As a result SL-3 ends up representing a really broad range of players.

There are a few SL-3’s i know that have Fargo ratings. Their Fargo range is 281-381. However, the 381 should probably be a 4 at this point (a base 4 is a 375).
 
“Females are larger than males in more species of mammals than is generally supposed. This includes many species of bats, shrews, Tasmanian devils, spider monkeys, flying squirrels, grey whales, humpback whales, hyenas, mongoose, Ross seal, tapirs, west Indian manatees, hippopotamus, dikdiks, okapis, and various mice.”
Ok thank you for the correction. I was overly broad and just plain wrong so let me be more succinct. Sorry for the erroneous mammal quote.

God made female humans much smaller and physically weaker than the males. This was not the result of evolution that's how they were created on day one. Doubters and yeh butters can cite all the nonsense they can come up with. I've already heard and considered all of it. Does not change reality one iota.

Men and women were designed for different roles as a species. Making it very tough for women as a whole to be superior in tasks they were not built for over men who were. And vica versa. Of course there are strong and coordinated women and weak and uncoordinated men. This is more prevalent the last little span of human existence since with the use of tools the weaker males have found a way to breed and perpetuate their genetics. We differ very distinctly from most of the other animals in this way.

Men and woman have equal rights to all things but they are not equal in every way. This is garbage.
 
God made female humans much smaller and physically weaker than the males. This was not the result of evolution that's how they were created on day one. Doubters and yeh butters can cite all the nonsense they can come up with. I've already heard and considered all of it. Does not change reality one iota.
Your reality and mine differ.
 
Is a normal distribution an accurate representation? I would figure a Chi-squared type thing with a far left hand lean in the curve. If 500 is the median, I would suspect far more 400's than 600's, and a gargantuan number of 300's vs. 700's.
Ratings of any large group of players seems to be normally (bell curve) distributed. Standard deviation usually around 100 to 110. This photo is from my Facebook profile. I think it was all established players at some point.
 

Attachments

  • IMG_1376.png
    IMG_1376.png
    55.5 KB · Views: 103
I understand the idea. But we have different counts. On the FargoRate app, I see one female in the top 100 of the world.
Siming Chen, han yu, and sha sha Liu are all 793 or higher and amongst the top 100 established ratings.
 
Siming Chen, han yu, and sha sha Liu are all 793 or higher and amongst the top 100 established ratings.
Your app lists Han Yu at 794 in the top 100 world female list, and no one else above 776. The top 100 world list goes down to 781.
 
Your app lists Han Yu at 794 in the top 100 world female list, and no one else above 776. The top 100 world list goes down to 781.

siming is off the list because of not having played much fargorated tournaments since covid. china locked down and then she played heyball. same story with most male chinese players
 
Ratings of any large group of players seems to be normally (bell curve) distributed. Standard deviation usually around 100 to 110. This photo is from my Facebook profile. I think it was all established players at some point.
This is all 121,400 players with 100 or more games in the system. The average is 465 and standard deviation 108. As we get more players into the system, the left side will build up more than the right and the whole curve will seem like it is just sliding to the left and keeping the same shape.
1700327080177.png
 
This is all 121,400 players with 100 or more games in the system. The average is 465 and standard deviation 108. As we get more players into the system, the left side will build up more than the right and the whole curve will seem like it is just sliding to the left and keeping the same shape.View attachment 728253
showing the same curves for male and female players would aid the current discussion. As would knowing their respective counts.
 
Your app lists Han Yu at 794 in the top 100 world female list, and no one else above 776. The top 100 world list goes down to 781.
Amongst established players, the top 100 go down to 789 and includes 3 women. This below is from a list of Chinese players in the APP and includes all 3 women. The world top player lists have restrictions that exclude some of the players.




1700327788818.png
 
siming is off the list because of not having played much fargorated tournaments since covid. china locked down and then she played heyball. same story with most male chinese players
Han Yu was, by any reasonable assessment, the player of the decade in 2010-19, the only player that won three WPA World Championships (Shasha Liu won two and Siming Chen won one). She took some time off for family reasons but returned this year with a vengeance. She played just two events this year and got gold at the China Open and silver at the World 10-ball.

At the majors (All Japan, China Open, World 9-ball), no player since Allison Fisher has enjoyed more success than Han Yu. She's got two All Japan titles, three China Open titles, and three World 9-ball titles. By comparison, Siming Chen has two All Japan titles, two China Open titles, and just one World 9-ball. In the case of Shasha Liu, she has no All Japan titles, one China Open and three World 9-ball titles.

Whether you look at recent play or her entire career, Han Yu is above her two biggest rivals. In my view, she's the only woman that ever played to an 800 Fargo (using the eye test). I'd put Han Yu as the six best 9ball player in the history of the women's game (behind only Jean Balukas, Allison Fisher, Karen Corr, Kelly Fisher and Ga Young Kim).
 
It seems to me that women also play tighter to their respective Fargo. For example, a 600 rated female can play like a 650 on her best day and 550 on her worst. But a 600 rated male can play like a 700 on his best day and 500 on his worst.

Also, does anyone know the Fargo rate difference between the recent transgender vs cis gender women players in that walkout match?
 
Back
Top