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Subject: Econometrics Model for Sokker
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there is a clear seasonal behavior in prices so the exercise to explain prices with skills only doesn't make sense to me
a more reasonable thing to do is to regress wages on skills of fresh youthpulls
a more reasonable thing to do is to regress wages on skills of fresh youthpulls
there is a clear seasonal behavior in prices so the exercise to explain prices with skills only doesn't make sense to me
exactly, if the exercise is to explain/predict prices, i.e., achieve high R squared or minimize forecasting error.
But if he's interested in the elasticity of price with respect to skill, then it doesn't matter if the R^2 is low, as long as the omitted variables are not correlated with skills (for example, if you tend to sell weak players in the middle of the season and strong players at the end, you would have a problem).
a more reasonable thing to do is to regress wages on skills of fresh youthpulls
How would that help you to understand the sokker market? :P
(edited)
exactly, if the exercise is to explain/predict prices, i.e., achieve high R squared or minimize forecasting error.
But if he's interested in the elasticity of price with respect to skill, then it doesn't matter if the R^2 is low, as long as the omitted variables are not correlated with skills (for example, if you tend to sell weak players in the middle of the season and strong players at the end, you would have a problem).
a more reasonable thing to do is to regress wages on skills of fresh youthpulls
How would that help you to understand the sokker market? :P
(edited)
it wouldn't at all! but it will help to spead some light to players skill sublevels
Yes I just want to regress prices on skills. Well, I am talking to BlueZero, I will be posting here anyway
Mean estimation Number of obs = 94394
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 2848193 14172.76 2820414 2875971
--------------------------------------------------------------
. mean precobr if weekday==1
Mean estimation Number of obs = 153351
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 2862240 11288.47 2840115 2884365
--------------------------------------------------------------
. mean precobr if weekday==2
Mean estimation Number of obs = 134576
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 2768012 11897.42 2744693 2791330
--------------------------------------------------------------
. mean precobr if weekday==3
Mean estimation Number of obs = 100319
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 2904617 14463.56 2876269 2932965
--------------------------------------------------------------
.
. mean precobr if weekday==4
Mean estimation Number of obs = 95526
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 2577661 14281.52 2549669 2605652
--------------------------------------------------------------
. mean precobr if weekday==5
Mean estimation Number of obs = 126264
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 3192797 13727.81 3165890 3219703
--------------------------------------------------------------
. mean precobr if weekday==6
Mean estimation Number of obs = 119052
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 3446477 14024.36 3418990 3473965
--------------------------------------------------------------
The Mean for the prices of Sunday is the biggest one on the week
:)
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 2848193 14172.76 2820414 2875971
--------------------------------------------------------------
. mean precobr if weekday==1
Mean estimation Number of obs = 153351
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 2862240 11288.47 2840115 2884365
--------------------------------------------------------------
. mean precobr if weekday==2
Mean estimation Number of obs = 134576
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 2768012 11897.42 2744693 2791330
--------------------------------------------------------------
. mean precobr if weekday==3
Mean estimation Number of obs = 100319
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 2904617 14463.56 2876269 2932965
--------------------------------------------------------------
.
. mean precobr if weekday==4
Mean estimation Number of obs = 95526
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 2577661 14281.52 2549669 2605652
--------------------------------------------------------------
. mean precobr if weekday==5
Mean estimation Number of obs = 126264
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 3192797 13727.81 3165890 3219703
--------------------------------------------------------------
. mean precobr if weekday==6
Mean estimation Number of obs = 119052
--------------------------------------------------------------
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
precobr | 3446477 14024.36 3418990 3473965
--------------------------------------------------------------
The Mean for the prices of Sunday is the biggest one on the week
:)
only for the senior players, which is logical because users buy 'last minute' players to use them in league games
thats a good theory
i could check it just on prices over R$ 4.000.000 for example and it would say that it is just for senior players
what do you think ?
(edited)
i could check it just on prices over R$ 4.000.000 for example and it would say that it is just for senior players
what do you think ?
(edited)
Or you could directly run this for players above and below a certain age :P
I could swear he was talking about the senior users
HUAUHAHUAUHAUHAUH
(edited)
HUAUHAHUAUHAUHAUH
(edited)
The results are still significant for Sunday
I used age under 24
(edited)
I used age under 24
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I believe that you will see if you study prices for saturday that they are high for seniors, but low for juniors.... :)
I am 100% sure about that without a Econometrics Model for Sokker ;)
Tthat is our lots of experience on TL Model ;)
Tthat is our lots of experience on TL Model ;)
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