I believe that success should be rewarded and failure should have its consequences. On the other hand, we don't want to see one team get so far ahead that it's impossible to catch them ever again, nor do we want to see a team fall so far behind that they become the St. Louis Browns of the league.
I decided to focus on the media revenue in my proposal for two reasons: (a) It's the bulk of the money a team has in its budget and (b) its not under a team's control (unlike gate revenue which, to a degree, is under a team's control).
My thought was that teams should be rewarded for winning. As such, I figured we could set the media revenue to a base number for the league (I used the current league median in the example below) and then increase or decrease that amount based on the team's performance the previous year, with the proviso that no team (no matter how well you do) can go above 20% over that base figure and no team (no matter how poorly they do) can go below 20% under the base figure.
The current league median for media revenue is 95,833,332, so the highest anyone's media revenue could reach (with that figure) would be about $115m and the lowest it could get to would be $76m. The figure for each team would be adjusted based on the number of wins the team has. So, the more games you win, the higher your media revenue will be the next year and the fewer games you win, the less your revenue will be (subject to the +/- 20% league median maximum and minimum).
Another thing I wanted to make sure of was that a team's previous successes weren't wiped out because of one bad year (or that a team is unduly rewarded for one good year). So, if a team won 98 games one year and then, due to injuries or other bad luck dropped to 60 the next year, I didn't want to see their revenue simply plummet to the floor. To counter this, I calculated a team's performance as a weighted average of the previous three seasons (weighted 50/33.33/16.66).
I also figured that if a team has a .600 winning percentage, that would be considered a "fully successful season" and a .400 winning percentage would be a "fully unsuccessful season." A .600 winning percentage is about 97 wins and a .400 winning percentage is about 65 wins. So, no team would receive extra revenue for anything over 97 wins, nor would a team be penalized for anything under 65 wins. This would also put a brake on runaway success or failure affecting the revenues. A team with 81 wins (a .500 record) should, by definition, be neither rewarded nor penalized - their revenue should stay the same.
By dividing the revenue range by the range of wins where performance matters, we come to a total of about $580k per win. So, for every win between 81 and 97 in the weighted average, the team would gain an additional $580k in revenue. For each loss between 65 and 81, they would lose the same amount (again, subject to the minimum and maximum).
Have I completely confused you yet? I thought so. Let me give you an example.
Take a look at the spreadsheet linked here and go to the 2028 tab.
The median revenue for last year was about $95.8m (cell E2). The amount per win is about $580k (cell C10).
Brooklyn, for example, had 69 wins last year, 85 the year before and 82 the year before that. When weighted, that gives an average of 77 wins. Since that's four games below .500, their revenue would decrease by 4*$580k, giving them a revenue for the next year of about $93.5.
Highland's average is only 57 wins, but since we're not penalizing below 65, they are treated as if they had 65 wins, which is 16 games below .500. Likewise, Seattle is at 115 victories, which is 34 games over .500. However, they are treated as if they had 97, which is the maximum amount, so they gain 16*$580k (about $13m).
The new revenue totals are carried forward to the next year and recalculated based on the median value for that year. And so on. I created tabs with made up win totals for the next few years, just to illustrate how this works.
Also, take a look at the 2031 tab. For that season, I created a collapse for Seattle, where they only won 67 games. Because we're using a weighted average, Seattle's revenue is not going to suddenly plummet. They still have the strength of the previous two seasons to keep them at the maximum revenue. However, if they were to have another bad season (see 2032), then they would start to see their revenue drop.
Likewise, I created a spike for Highland in 2032, going from 60 wins to 99. This brought their weighted average up to 79 (from only 57 the year before). As a result, their situation improves, but they don't end up suddenly end up flush with cash, because they still need another good season to bring their average up over the .500 mark.
To summarize:
- At the beginning of each year, the median media revenue is calculated and, based on that, a ceiling and floor of 20% in each direction are created.
- Team records for the three previous seasons are weighted to get a win total and revenue is added or subtracted based on that win total (with a floor of 65 wins and a ceiling of 97 wins).
- If a team's revenue would fall below the floor or above the ceiling, then the totals are adjusted for those teams.
Any questions? I don't want to make this a formal vote, just a session for getting input. I'll also make my Excel spreadsheet available to anyone who wants it (just email me) so that you can play with the numbers yourself.
Zev
I like it, it looks good. Related question:
ReplyDeleteDoes anyone have any insight on the optimum ticket price? I like to be the kind of owner who gives my fans a good product for a decent ticket price. But I also don't feel like I can leave any money on the table. My success on the field has increased every year, but I don't feel I'm seeing an attendance increase. Are my prices too high? Or does it take more years of more success to get the fans to come out? Or is gate revenue such a small piece of the pie I shouldn't worry?
Zev, thanks for all your hard work on this. I like this approach and think it would be an improvement over the current system. I will generally defer to you and others as to whether any tweaks are necessary.
ReplyDeleteBill, under the current version of the game I don't think the rest of us can see your ticket price (at least, I haven't been able to figure out how to find it). My experience on this issue is mainly from earlier versions of the game, and I'm not sure how much the new versions have changed the analysis. Generally, however, I have found that the primary drivers of fan attendance are Market Size, Fan Loyalty, and Fan Interest ratings. If those ratings are good then your attendance should follow; however, I do think that attendance will decrease if you set the ticket price too high. For what it's worth, my ticket prices are $12.95.
This looks good, Zev. I wouldn't have a problem with this. Would this be in addition to adjusting the baseline budgets?
ReplyDeleteI'm generally happy with this proposal in principle, as it seems a fair way to deal with the issue. I separately emailed Zev because I'm not sure the formulas accurately accomplished the desired goal, but that's something easily resolved.
ReplyDeleteMy only conceptual concern is that this process will keep league revenues flat over time. In contrast, the game normally slowly ratchets league revenue upwards, through increases to media revenues. I think our model should account for that, perhaps by slowly increasing the median revenue by a certain percentage each year. I'm not sure what that percentage increase should be (5% maybe?), but I do think we want to incorporate that concept into our revised media revenue model.
Mack,
ReplyDeleteI saw your email and will look into the individual items shortly. As for the issue of media revenue growth, it does grow, but very slowly.
I happened to run a test league for 100 years a few weeks ago and still have the data. The average media revenue for the league ran like this:
2014 52,458,333.33
2024 53,562,500.00
2034 54,000,000.00
2044 53,187,500.00
2054 57,453,125.00
2064 57,819,444.44
2074 59,861,111.11
2084 61,750,000.00
2094 59,400,000.00
2104 58,421,052.63
Over the course of a century, it did bump up, but we're not running centuries at a time. We run about 2-3 seasons every year. As such, the growth is very little from season to season.
If there has been growth in our league's history, it's probably a result of changes in real world baseball's finances affecting OOTP as they put out new versions. When we started in 2002 with OOTP4, the financial landscape of the real-life MLB (in terms of salaries, media revenue and whatnot) was much different than it is today and today's version of OOTP would treat them much differently than OOTP4 did.
I'm not opposed to bumping up the numbers, but, from season to season, the growth should probably be small.
Zev
Thanks Zev. That's very interesting. In that case, it probably doesn't make sense to build growth into the model.
ReplyDeleteThat data also makes me rethink some of my contract negotiation ideas. (grin)