okay. Some of you have heard my theories about how to game Avon FanLit before. Some of you even saw them being tested, when we first posited them. But here’s the truth:

As constituted in the game we played, the rankings in Avon FanLit were susceptible to gaming. I’m not talking about cheats or zero-bandits or skippers or any of that. I’m just talking about regular old gaming that resulted from the game mechanics. A lot of what I’m going to say here is conjecture, but it’s conjecture that’s supported by observation, evidence, and FanLit’s own comments.

Things we know. First, your score is determined by two things: the votes you get, and the number of eyeballs you can grab from the crowd.

Important conjecture number one: The database stores one score for each voter. It either store a number (e.g. 4.5) or a skip. If a person skips a story, but then has it come up in the pool again and reads it, their previous skip is replaced with the score they give. Holly verified that, although it’s possible to skip a story more than once, it would only record one skip per person. I conjecture that it stores only one score–otherwise a person could skip a number of stories and then give them zeroes, which gives them double-ding power. Believe it or not, this hidden mechanic is vastly important.

Important conjecture number two: The database tries to get every entry to have a certain “minimum” number of scores (inclusive of skips). That minimum number is determined, to some extent, by the total number of votes relative to the number of stories. It won’t be even, but let’s say that any story should have at least half the average number of votes available in the pool.
Important conjecture number three: The number of reads you get is inclusive of invites.

Important conjecture number four: Not all positions in rotation are equal. Your position in the rotation is determined by two things: (1) whether you need more scores so as to fit criteria 2; and (2) your last N scores, where N is probably 3 or 4. If your last three or four scores are not very good, even if you are technically “in” rotation, you’ll probably be near the bottom of the pack. If your last N scores are decent, you’ll be near the top of the rotation.

This second bit is partially supported by claims by FanLit, who claimed that if your story isn’t getting skipped, you’ll fall out of rotation faster, but it’s more supported by observation. There’s a reason why getting a 5 from an invite was more likely to be obliterated by a low-score within minutes after you’d been sitting on a 2.0 for three hours: The 5 pushed you towards the top of rotation, and so you were more likely to be pushed in front of eyeballs, and thus get a bad score.
In Rounds 3 and 4, I tracked score timing and data, and while I didn’t have enough information to say definitively, it seems to me that this was a very plausible theory.
Okay. That’s the sum of my guesses about the inner workings of FanLit. Now you add in some observations about the FanLit reader’s habits, also garnered by paying a great deal of attention.
People were less likely to skip stories when the pool was thin (few entries available). People were less likely to skip stories late at night. They were less likely to skip stories that were presented to them when the database was serving up batches of 10 or so near the end of the voting period.

People were more likely to skip stories in that first rush on Monday.

So what do you do about this? Easy: you use your invites to game the system so that you’re only getting read when the pool is favorable. You submit your story on Saturday afternoon. You don’t use any of your invites. It’ll get reads up through Sunday mid-morning, where (chances are) you’ll get a few bad scores in a row. You lay low all through Sunday. Sunday night, you send out three invites to people you know respond quickly; you’re tossed back into the voting pool, and you pick up more high scores. At this point, you’re getting more scores from non-invites, because the database will push you to the top of the rotation to try and even you out. You should have something like 30 votes at this point, and 22 invites in your pocket.

Then you blast your 22 invites all at once. Boom. You’ll have 50-something votes; way more than anyone else, and you’ll be so far out of priority on Monday, compared to the stories that were submitted, that you won’t surface until the database starts batching at the end, when people are unlikely to skip.

That’s how you use your invites to minimize skips. Is this indicative of anything other than an ability to game the system? No. Will this help if your story isn’t any good? No. Must you do this to final? No. But it probably helps. And it shows that the main problem with the Avon FanLit calculus is that skips are weighted far, far too heavily. They’re the easiest thing in the world to game, and so their effect needs to be minimized.

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