Forecasting IFPA Tournament Growth: Is There a Fee Effect?

Can you explain this a little more? Not sure I follow.

Whatever negative effect SCS day has on the # of tournaments, it is offset by a huge amount of tournaments that would not otherwise have occurred on that day. These effects are baked into the model, and you can see in the first figure that it tracks rather well on what actually happens on SCS day.

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Mmmmm data trends. Cool analysis thread

“Histogram” was the term I meant to use. Basically, group the number of participants of each individual event into “bins” of five so you can make a chart like the one below (excuse the random histogram picture I stole from Google). I’d assume we have some kind of long right-tail (lots of events with 10-30 people) followed up fewer and fewer events with 50, 60, 80, 100, ++ all the way until you hit 800 for Pinburgh.

I got that, I’m confused more about the “as a way to supplement the information about averages” part of the comment. What is the goal, to determine whether there has been a shift in the distribution of tournament sizes over the years?

Phil, also, for this analysis of tourney size (if you pursue it), I’m assuming that the data set is large enough that Average (Mean) is deemed an appropriate metric to use instead of Median? Pinburgh’s ~800 players would certainly skew a small data set, but having some 4,000+ events per year probably makes Mean equally useful. Correct?

Yes, that is what I think would be interesting to see to supplement the Average number. What shifted the average down between 2016 and 2017? Are we seeing fewer bigger events? More frequent smaller events? And as 2018 rolls on, what are we seeing in terms of per-event numbers if directors are choosing the “hybrid” method of allowing people to declare if they will pay to be included in submission.

There are more layers to this question than you probably intended. It is true that as the number of samples increases, the less of an issue outliers are. However, because we are plotting changes over years, and the overall number of samples are changing, it can affect our interpretation of the mean. For example, I’m not sure that the drop in mean tournament size over years mentioned before is really all that meaningful, and is probably just an artifact. In early years, there are fewer tournaments, so the mean is skewed by high attendance tournaments. Then as the number of overall tournaments increase, particularly with more low player tournaments, the mean gets dragged down. This will happen even if you use the median, btw. Does that make sense? See the last figure below, too

for @coreyhulse, here are your histograms…

It’s sort of hard to see what’s going on at this scale, but at the very least, you can see that the vast vast majority of tournaments are small in size (under 50 players).

Here is growth by tournament size

As you can see, there was growth in practically all tournament sizes. There was a drop off in the 100-200 bin though, that might account for some of the drop in the 2016-2017 mean tournament size. However, that was really only a loss of 12 tournaments… WARNING: I allowed the y axis scales to vary in this figure because if I didn’t, you wouldn’t be able to even see the 100-200, and 200+ bins because there are so few of them.

Below is a plot of the proportion of tournaments that fall into different bin sizes over the years.

Here, you can see that with increased growth, the overall number of low attendance tournaments continue grow relative to the high attendance ones. This is the effect I was speaking of at the beginning of this post – the influence the high attendance tournaments becomes less and less pronounced over the years, which can affect how you interpret year-to-year changes in the mean.

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Thought I’d give a quick update on this post. The predictions I posted at the beginning of year have been remarkably accurate. There doesn’t really seem to have been much of a fee effect. The annual growth remains unabated.

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As always: good analysis. Nice predictive model!

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  1. How does the model ‘see’ suppressed players like myself? I have played approximately the same number of events this year, only without submitting results for points.

  2. just looking at the graphs without raw numbers, Jan & Feb 2018 seem to be outliers and then there is a pretty consistent number above 10000( 7different months, so far.) That is pretty damned positive from an overall health of the ‘sport of pinball’ perspective.

  3. What is the expected payoff, or “increase of interest” generated from the $1 fee? If the current growth trend was predictive without the fee being a factor, will 2019 tell the story?

Suppressed players should still be submitted in the results to make sure they are impacting the value of the tournament appropriately.

We of course can’t track any events where that data wasn’t submitted to us.

unless the TD offers an opt-out option, correct?

Opt out option isn’t just a suppressed players thing. That’s available for anyone at the discretion of the TD.

  1. Well, the technical answer is that the model doesn’t handle them at all. The model simply tries to predict the overall number of players. That said, if players were dropping at a greater rate in 2018 than in prior years, then we would see that the predictions would have been consistently higher than what was observed. That didn’t happen.
  2. I wouldn’t call jan and feb outliers. There is always a lull in the winter months. It seems there is a seasonal effect every year. Spring/Fall are the most active seasons, and Winter/Summer are the least active seasons.
  3. So, the hypothesis is that adding money to the SCS will improve overall interest. Since the payouts don’t happen until 2019, I think it’s safe to say any benefits of the fee won’t appear until 2019. If growth outstrips predictions, then you could say that it was a success.
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Yeah, i think there’s some confusion about what a suppressed player is. @JNX I don’t think you are suppressed, because your IFPA profile is still active. What we’ve been doing is just letting you opt out of submissions altogether.

yeah, i never really delved into details. 1. I still got to play and 2. I didn’t pay the fee.

Ultimately, I didn’t want my stance against the fee to affect others, including the TD. I am now going to start playing as a rated player again, rejoining the herd.

I would challenge that the measure of success would be accelerating growth to the same percentage that the fee comprises local prize money. If entry fee is $5, then taking a dollar from that would make the growth over normal projections need to be 20%. If it is $10, then the uptick in growth would need to be 10% over the regular projections.

Admittedly an aggressive target, but there needs to be a bang for everyone’s literal buck.

Do you feel that there is still a need for the 5 played event rule for new players, now that the $1 fee has been established? On the flip side, should a TD have to pay a $1 fee for a player that essentially doesn’t count towards the value of the tournament. Figured I would stir the pot…

Yes

Yes

Let me settle that pot down for you :slight_smile:

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9 posts were split to a new topic: Five game “experience” requirement for IFPA rating (split from Fee Effect thread)