Do teams with lower state tax rates get significant discounts?

[Craig Button]

I live in Austin, and while state income taxes are low, property taxes are ridiculous. We have one of the highest in the nation, and it isn't getting any better anytime soon. The rent on my apartment that was just under 800 square feet was jumping from around 700 to 1,000 dollars. And I believe it has gotten higher since I moved out 4 years ago. Our rent increases here are among the highest in Texas. I hope you have a pretty good job, like 25 dollars an hour - because that's roughly how much it'll cost to live in Austin for a two bedroom apartment/house.

I charge $2000 for a 1 bedroom condo in Toronto.
Last time I saw anyone charging around $1,000 was maybe 25 years ago

 

[Voight]

Bob was probably getting 10 million/year regardless of where he signed, it helped that FLA was the team in most need of a #1 goalie.

While the lack of state income tax probably made it easier for Kuch to sign for 9.5/year, I am sure a team discount factored in as well. He wanted the team to have flexibility, look at Stamkos he took 8.5/year when he could have easily signed for 12 on the open market. Likewise with Hedman when he re-signed.

Vinik and Yzerman re-built the organization and made it very player friendly, guys want to play there and are willing to make a little less $$ to make that happen.

 

[4thline]

OP, kudos on taking a stab at this and on coming up with a way to track the relative change, but outside of a 1st year stats project this gets torn apart pretty quickly. That there is a much correlation as there is is pretty telling

 

[FerrisRox]

It is. Clearly you're forgetting LTIR contracts.

Your thoughts of a hard cap are false because from the get smart GMs found a way around it.

What is "smart" about having LTIR contracts? What makes you think it requires "smarts" to acquire them?

You're confused here.

 

[Legionnaire]

What is "smart" about having LTIR contracts? What makes you think it requires "smarts" to acquire them?

You're confused here.

With all sue respect you are wrong

 

[Legion34]

I'm not sure how this can really be debated. Taxes do influence contracts. It's a simple, obvious fact.

I think the bigger question is: Is the benefit worth changing rules over? I see a team like Tampa and it looks like they have an advantage, but I also wonder how much is culture/region. It's hard to really say without players coming out and disclosing this info.

multiple players. Coaches. Agents. GMs. Media and even tax specialists have come out and said it is an advantage

I linked multiple articles and quotes in a previous thread. The poster just ignored this. Created a new thread and pretended it didn’t exist

 

[Legion34]

Bob was probably getting 10 million/year regardless of where he signed, it helped that FLA was the team in most need of a #1 goalie.

While the lack of state income tax probably made it easier for Kuch to sign for 9.5/year, I am sure a team discount factored in as well. He wanted the team to have flexibility, look at Stamkos he took 8.5/year when he could have easily signed for 12 on the open market. Likewise with Hedman when he re-signed.

Vinik and Yzerman re-built the organization and made it very player friendly, guys want to play there and are willing to make a little less $$ to make that happen.

Bob even still took a 2.5%AAV discount in comparison to price.

 

[Legion34]

Bob was probably getting 10 million/year regardless of where he signed, it helped that FLA was the team in most need of a #1 goalie.

While the lack of state income tax probably made it easier for Kuch to sign for 9.5/year, I am sure a team discount factored in as well. He wanted the team to have flexibility, look at Stamkos he took 8.5/year when he could have easily signed for 12 on the open market. Likewise with Hedman when he re-signed.

Vinik and Yzerman re-built the organization and made it very player friendly, guys want to play there and are willing to make a little less $$ to make that happen.

The point is with tax advantages. They didn’t take nearly as much of a discount as it looks like.

 

[God King Fudge]

I wonder if all these folks that see their BP shoot through the roof "CUZ UNFAIR!" are going to blame HF when they have a heart attack from one of these threads.

 

[x Tame Impala]

I struggle to see how the posters in this thread that have been crying about different income tax rates for months now, still can’t just acknowledge that a higher tax rate is simply the opportunity cost for being able to offer a world class city for your players to play and live in.

Yes you are taxed more in Toronto than in Tampa or Dallas or Glendale. But there are huge differences and benefits to living in Toronto over those other places. Some players may value those benefits differently than others, but that’s up to the players to decide when they’re choosing which team to play for.

“Yeah that sucks I’ll get taxed more, but I’ll get to live in Toronto!”

It’s absolutely asinine to make changes to the cap based on income and it’s really only Canadian posters who I see do it.

 

[x Tame Impala]

Double post

 

[thestonedkoala]

I charge $2000 for a 1 bedroom condo in Toronto.
Last time I saw anyone charging around $1,000 was maybe 25 years ago

How many square feet? Where is it located?

 

[MikeyMike01]

I live in Austin, and while state income taxes are low, property taxes are ridiculous. We have one of the highest in the nation, and it isn't getting any better anytime soon. The rent on my apartment that was just under 800 square feet was jumping from around 700 to 1,000 dollars. And I believe it has gotten higher since I moved out 4 years ago. Our rent increases here are among the highest in Texas. I hope you have a pretty good job, like 25 dollars an hour - because that's roughly how much it'll cost to live in Austin for a two bedroom apartment/house.

I’m aware of the property tax problem. I’d be renting anyway so that’s fine.

$1000 rent for 800 square feet sounds like a dream!

 

[TomasHertlsRooster]

I literally did it in the exact way that you did (adding together all of the cap hits) and included the teams you wanted. Now you see the results and suddenly it's useless? Even I would have expected more from you.

2019:

All teams between 40-45% taxes: 100.4%
All teams between 49-53% taxes: 105.2%

2018:

All teams between 40-45% taxes: 101.7%
All teams between 49-53% taxes: 109.3%

There is still a significant differences between low tax and high tax areas.

- Doesn't understand why testing for correlation is infinitely better than binning continuous variables.
- Tells other posters "I would have expected more from you".

Goodness gracious.

 

[Dekes For Days]

- Doesn't understand why testing for correlation is infinitely better than binning continuous variables.
- Tells other posters "I would have expected more from you".

Once again, I did it in the exact same way you did it, and included the teams that you said you wanted to create a bigger sample, and then when it didn't show what you expected/wanted, you tossed it aside as completely worthless.

2019:

All teams between 40-45% taxes: 100.4%
All teams between 49-53% taxes: 105.2%

2018:

All teams between 40-45% taxes: 101.7%
All teams between 49-53% taxes: 109.3%

There is still a significant differences between low tax and high tax areas.

 

[Craig Button]

How many square feet? Where is it located?

Just less than 700.
Around the Don Mills area

 

[TomasHertlsRooster]

Once again, I did it in the exact same way you did it, and included the teams that you said you wanted to create a bigger sample, and then when it didn't show what you expected/wanted, you tossed it aside as completely worthless.

2019:

All teams between 40-45% taxes: 100.4%
All teams between 49-53% taxes: 105.2%

2018:

All teams between 40-45% taxes: 101.7%
All teams between 49-53% taxes: 109.3%

There is still a significant differences between low tax and high tax areas.

No, that is not remotely what happened.

I said that doing things this way would be BETTER than just averaging averages as you initially did. However, it is still not the best way to go about this, because you are dichotomizing two continuous variables. Do you not understand what that means? Do you not understand why that is a bad idea? Let me explain.

Let's create a hypothetical scenario in which teams in the 40% range spend 105%, teams in the 45% range spend 95%, teams in the 47% range spend 120%, teams in the 49% range spend 110%, and teams in the 53% spend 100%. Here is what that would look like on a chart:

You actually get a (minuscule) negative correlation with those numbers. However, if you repeat the same exercise that you just performed with these hypothetical numbers, you would get:

Teams in the 40-45% range: 100%
Teams in the 49-53% range: 105%

The actual correlation between the numbers would be slightly negative, and essentially non-existent. But you would come to the same exact conclusion as you did; that there is a significant difference between low tax and high tax areas.

The reason that you would come to this conclusion in this hypothetical scenario is due to a few factors. For one, you are assigning the same significance to a 40% tax rate as a 45% tax rate, and the same significance to a 49% tax rate as a 53% tax rate; both of which are fundamental errors, for obvious reasons. Second, you would be completely excluding all data in the 47% range, which is also a fundamental error for obvious reasons.

This is very similar to the issue that is present with this study regarding concussion rate and altitude. Look at the actual data, plotted on a chart:



The correlation is slightly negative between their x and y variable. However, by separating the variables into two bins that were selected by a completely arbitrary method, they were able to come to a conclusion that was completely out of line with the actual correlation between the two variables. And unlike your analysis, they did not completely exclude some variables. What you are doing is slightly worse than what they did in this flawed study.

Now, the conclusion that is drawn from your methodology is not as far from the truth as the conclusion drawn from your methodology in my hypothetical scenario. In fact, the conclusion that you came to is pretty close to the conclusion that is drawn from the two R^2 values in the correlation; which is to say that there probably is a correlation, but it is not extreme, or severe.

But does this not show you the clear flaw with your methodology?

 

[Dekes For Days]

However, if you repeat the same exercise that you just performed with these hypothetical numbers, you would get:

Teams in the 40-45% range: 100%
Teams in the 49-53% range: 105%

First off, you're averaging averages, which is the exact thing you complained about me doing.

Second, there are clear groups of tax levels, and under the first sample I did that you complained about, this lack of correlation would be clearly visible.

No-tax areas: 105%
High-tax areas: 100%

But that's not what we saw in our real life scenario. We saw a positive correlation with the high-tax areas paying significantly more than low-tax areas, and it stayed consistent when we looked at the second sample.

The reason that you would come to this conclusion in this hypothetical scenario is due to a few factors. For one, you are assigning the same significance to a 40% tax rate as a 45% tax rate, and the same significance to a 49% tax rate as a 53% tax rate; both of which are fundamental errors, for obvious reasons.

Are you freaking kidding me?

I literally started out with just the no-tax and high-tax areas that had very little difference between the percentages, and you complained, said the sample was too small, and told me to add in the 44-45% teams and the 49% teams. So I add in all of the teams up to 45%, and all of the teams above 49%, creating a bigger sample, still showing a significant difference between high-tax and low-tax areas, and then you complain that I grouped together the teams that you told me to.

You are using the most extreme example that you know doesn't even apply here to try and discredit my work. You know the correlation. My results match perfectly with the trends we see in the graph. I showed you two different samples, and they both suggest the same thing.

You post the most flawed analysis I've ever seen on here and then you nitpick everybody else's work. There is a significant difference between low-tax and high-tax areas, as everybody can clearly see, no matter which method you use.

 

[TomasHertlsRooster]

First off, you're averaging averages, which is the exact thing you complained about me doing.

Second, there are clear groups of tax levels, and under the first sample I did that you complained about, this lack of correlation would be clearly visible.

No-tax areas: 105%
High-tax areas: 100%

But that's not what we saw in our real life scenario. We saw a positive correlation with the high-tax areas paying significantly more than low-tax areas, and it stayed consistent when we looked at the second sample.


Are you freaking kidding me?

I literally started out with just the no-tax and high-tax areas that had very little difference between the percentages, and you complained, said the sample was too small, and told me to add in the 44-45% teams and the 49% teams. So I add in all of the teams up to 45%, and all of the teams above 49%, creating a bigger sample, still showing a significant difference between high-tax and low-tax areas, and then you complain that I grouped together the teams that you told me to.

You are using the most extreme example that you know doesn't even apply here to try and discredit my work. You know the correlation. My results match perfectly with the trends we see in the graph. I showed you two different samples, and they both suggest the same thing.

You post the most flawed analysis I've ever seen on here and then you nitpick everybody else's work. There is a significant difference between low-tax and high-tax areas, as everybody can clearly see, no matter which method you use.

You dichotomized two continuous variables, and then you took the average of averages among these variables. And now you’re telling me that my analysis is the most flawed analysis you’ve ever seen.

That is f***ing rich.

 

[Dekes For Days]

you took the average of averages among these variables.

No, I did it in the exact way that you did, adding up all of the individual cap hits, and used the teams that you wanted, and you still complain that it's not good enough, while you post incredibly flawed methods yourself and draw conclusions with insufficient information that your data doesn't even support.

 

[TomasHertlsRooster]

No, I did it in the exact way that you did, adding up all of the individual cap hits, and used the teams that you wanted, and you still complain that it's not good enough, while you post incredibly flawed methods yourself and draw conclusions with insufficient information that your data doesn't even support.

I’m talking about what you initially did, which was dismissing the results of correlation in favor of dichotomizing two continuous variables and then averaging the averages of them. That immediately made it very clear that you are out of your depth here and probably aren’t in a position to criticize the methods which I used. From that point on, you firmly entrenched yourself in a glass house and you’ve been throwing stones out of it ever since. Just stop.

 

[Harvey Birdman]

when anyone on this board actually moves due to lower taxes let me know

I’ll be doing it after I retired. From PA live in So-Cal. Taxes here are crazy, so is the cost of living. I’ll be heading some where like Tennessee or Florida when I retire.

 

[Harvey Birdman]

I’m aware of the property tax problem. I’d be renting anyway so that’s fine.

$1000 rent for 800 square feet sounds like a dream!

Here is so call it’s around 2500-2800 for 1400 depending on where you live. Can go much much higher in the well to do or downtown area.

 

[MikeyMike01]

Here is so call it’s around 2500-2800 for 1400 depending on where you live. Can go much much higher in the well to do or downtown area.

And the highest income tax in the nation to boot.

 

[Legion34]

I’m talking about what you initially did, which was dismissing the results of correlation in favor of dichotomizing two continuous variables and then averaging the averages of them. That immediately made it very clear that you are out of your depth here and probably aren’t in a position to criticize the methods which I used. From that point on, you firmly entrenched yourself in a glass house and you’ve been throwing stones out of it ever since. Just stop.

you still haven’t answered why you are just ignoring multiple agents coaches. GMs and players who actually say that take home pay and taxes are important in negotiations

You designed a “study”’ with limitations and decide that you can decide that the high tax and no tax markets can be used as a comparables...

When an accountant with 20 NHL clients did an analysis and reported that

From a purely fiscalperspective.... a Canadian team in a high tax market cannot compete with a Low tax market. Specifically based on his analysis of tax disparity.

Why do you think you know more that you can draw conclusions like this. When it contradicts the evidence provided by an actual professional?