Einstein

Been there, done that. haha.

There are several ways people deal with adversity. Some people fight back. Some people disengage. And some people cope with it by rationalizing. "Yeah, they're charging a lot of money. But that's the business. The NFL has changed. We must understand. etc" Rationalization is a defense mechanism in which controversial situations are justified and explained in a seemingly rational or logical manner to avoid the true explanation, and thereby make them appear less threatening. Some people will rationalize the PSL's which double dip on taxpayers by attributing them to broader, understandable business practices and changes within the NFL, suggesting that such changes are inevitable and should be accepted. There is a bit of stockholm syndrome mixed in. I haven't seen anyone in this thread who is shocked, stunned or surprise. Everyone knew it was coming. Some are pointing out the inequity in it. Thats not a sign of being surprised - its a sign of evaluating the situation for what it is.

His cryptic comments meant nothing though. This is all coincidence.

This whole thread could be submitted to Cold Takes Exposed. @Beck Water and @H2o with early nominees. That reporter nailed everything. From the team, to the literal pick we landed.

The general attitude I see in this thread is “We all knew it was coming, it’s what is common in the NFL, therefore it is okay.” I, like you, don’t understand those feelings. But everyone is different and its a coping strategy on their part and people have to do what they have to do to get on. Let them buy them first, and then scoop them up for pennys on the dollar in a few years.

Diggs must have forgotten the last half of last season, where Allen played without a #1 WR because Diggs was stinking up the joint.

This morning… ———- RG3: Is Diggs essential to Josh Allen’s success? Random tweeter responds to RG3: Diggs helped, but he is not essential to Allen’s success. Diggs response: You sure? ———- And yet fans still think Diggs wasn’t giving cryptic messages 🤦🏻‍♂️

Very weak comp. The Bills wanted him gone.

#1 - Yes, it would be zero. #2 - I ran the math on this earlier. PSL value will be approximately 1/4 of what owners paid within 5 years of ownership. This could potentially change if the team wins a SB the year before you sell your tickets, but you would need that luck to cause a temporary spike.

There it is! That was my entire point with my predictive model. Kirby and Wot were disputing the facts of what you just admitted it. It is simply maths. As for your point that lower PSL’s will encourage more buying - we’ll, I’ve already written several posts on why I don’t see that happening, so I don’t want to spam the forum with information on elasticity. The idea was never that the stadium wouldn’t be full. The Bills will MAKE SURE it’s full.

Funny part is that even with this trade, people won’t believe that his cryptic tweets were messages. They simply won’t get it.

@GunnerBill - I told you that where there is smoke, there is fire.

It’s not. But I do want to commend you for posting. It’s nice to see your name pop up next to a post, rather than just reacting to others thoughts. I’m sure you have a lot to offer the forum so I encourage you to post more often. If your argument is that there is data that is not included in a model, then yes, i’d agree. But for the data we have, the margin of error and confidence level provide measures of how much the sample results can vary from the true population parameter. In our calculations, even when accounting for a 95% confidence level, the sample size of 420 account holders exceeded the necessary size to achieve a margin of error of 5%. This means the estimate of 75% buying under the new pricing, even with variability in PSL costs and sections, is statistically reliable within the predefined margin of error. Another problem is that you, like Kirby, assume a higher sales rate with lower priced tickets. I wouldn’t assume that. As I mentioned prior, price sensitivity and elasticity of demand. Lower income fans that often make up the less pricier areas of the stadium are generally more price-sensitive, meaning their demand for tickets is more elastic. This elasticity is due to their inability (and sometimes unwillingness) to purchase tickets with even a small increase in price, as the cost represents a larger portion of their discretionary spending. You’re comparing unlike items here. Predictive values are just that. Predictive of future failure at the same clip. But that has nothing to do with whether that 25% end up purchasing elsewhere in the stadium. Apples and oranges. The model predicts a future sales rate of 75%. That’s all. Nothing more, nothing less. If a portion of the 25% from another tier end up purchasing at a later time in a cheaper tier, that doesn’t change the idea that approximately 25% of the current season ticket holders in that tier are choosing not to purchase. For what it’s worth, I think the argument that a portion of the 25% purchase elsewhere is a good hypothesis to make. There is no evidence to back it up at this point - it’s pure conjecture - but it is reasonable. That being said, it has nothing to do with predictive values. It’s an outside factor completely unrelated to the model. If you are concerned that i’m arguing that the stadium will not be full, fear not. That is not my argument at all. That’s ridiculous. Now if you want a more interesting hypothesis with also absolutely no evidence - It’s very possible that the Bills are inflating the renewal number to 75% with corporate tickets. What piqued my interest is the Bills usage of “account holders” for renewal rates, rather than seats or tickets. That is a term I would use if I wanted to obfuscate data. But that’s an entirely different topic.

I contradicted your hypothesis of the existence of two different customer types negating predictive potential. But it appears to have gone over your head. Unless you mean that someone else also corrected you on that point 10 pages ago. If so, you probably should have heeded that posters advice.

We are alike in many ways. It’s likely why we butt heads sometimes 😉.

Exactly right. You should learn about predictive modeling. You don’t have to guess or use a hunch. We have maths to give us the answer on what is predictive. The 1.6% is predictive. At a 95% confidence interval.

Not when i’m correct.

These sponsorship deals exist at the current stadium as well, not to mention every stadium in existence. No, this does not mean the team wants to lose 25% of its season ticket base.

Yes, I agree, there is definitely someone in this thread doing this…

I think you misunderstood. What the formula does is tell you what sample size you need for the sample to be predictive. That's the entire point. We need at least 203 account holders to be offered PSL's at a 90% confidence level, to have the sample be predictive. The Bills have shown over 400. This is just absurd. "Hear me out boss. Let's spend millions of dollars to hire salespeople who sell people on $40k PSL's, all day every day, and get this... we are going to WANT lots of people to say NO and waste our time/money". They want 100% sales. Unless you have information that they are breaking disparate impact by selling the same seats for more money to corporate buyers (which they aren't). They likely dont. Which is why they are selling clubs first. They are using it as a benchmark.

They pass 95% confidence level. How does that not tell us anything?

"Failure" isnt the right way of looking at it. It's just the reality of the numbers. Neither good nor bad. The 60k isnt used in the equation at all so doesnt mattter. I just cut the end of my sentence off. It was meant to say 60,000 tickets at 2.5 ticket per account holder

Right. So let's figure out how many the Bills need to attempt to sell to before we have a predictive value. Meaning, how many people before we know the % of sales is a good predictor of future outcomes. - Let's say we want a confidence level of 90% and a Z-score of 1.65 (technically 1.645). - Let's assume 60,000 season tickets at 2.5 tickets per account holder. - A 5% margin of error. - We know 75% of those shown the new ticket pricing have agreed to buy, so we have p = 0.75 and q= 1 − p (so 0.25) So we have: The answer is 203. With a 90% confidence level and a 5% margin of error, the Bills need to offer PSL's to at least 203 account holders. We know they have presented to 1.6% of account holders. If each account holder averages 2.5 tickets, that means they have presented to 403 account holders. Which is significantly more than they need to see predictive value. in other words, the 75% sale figure is predictive. .

That's not the right maths... It's 1.6% of account holders. NOT seats.

You're conflating the current stadium with the new stadium. There is no debate that the new stadium has high demand. We are talking about the new stadium. Where 1 in 4 customers are giving their tickets up. As stated earlier, I expect a similar outcome with lower priced tickets, due to price elasticity. I believe the Bills expect it as well. They will model prices in the lower seats to percentage wise match club seats to obtain at least 75% buy in. We do know that losing 1 in 4 customers is a very, very bad thing. If John Doe thought he would be poked in the eye, and then did get poked in the eye, it does not make the eye poke a good thing. It only means he accurately forecasted his eye poke.