Submission wait times are an oft-discussed topic among writers and much rejectomancy is applied to how long a story is pending with a publisher. I’ve covered it before, some four years ago in this post: Submission Protocol: The Waiting Game. When a story is held longer than usual by a publisher, authors begin to prognosticate. Signs are read, the stars are consulted, and the bones cast in an attempt to divine what this delay could possibly mean. The great theory is this: the longer a publication holds your story, the more likely they are to accept it. Along with that theory is the idea that rejections generally arrive faster than acceptances. But is all that true? Let’s dive into the numbers and see if we can’t shed some light on this.
The last time I tackled this issue, I had far less submission data to work with. Now I have lots more, so we’re gonna approach things from a more data-driven angle. I currently have 449 submissions tracked on Duotrope. When we subtract pending subs and those I’ve withdrawn, we’re left with 423 submissions. Unfortunately, I need more info than many of these subs provide. I need to know the average return time (how long it actually takes) for the publisher AND the estimated return time (how long the publisher says it will take). When I sort for subs that meet both criteria I’m left with an even 200. Of those 200 submissions, 182 resulted in a rejection and 18 resulted in an acceptance.
That’s a sample size, but a pretty good one, so let’s look deeper at the numbers.
If the great theory holds, then all my acceptances should exceed the average return time and probably the publisher’s estimated return time. But did they?
Out of the 18 acceptances, only 5 were held longer than the average return time and only 3 were held longer than the publisher estimated return time. Now, take these numbers with a grain of salt, as this is a pretty small sampling of acceptances. The markets that held stories past average and/or estimated return times are pro markets, where that might be more expected. So, no conclusive evidence here, but let’s see if the rejections and their much larger sample size tell us something different.
Again, the theory states that rejections should come quicker than acceptances and be within or under the average and estimated response times. So let’s look at the 182 rejections I have and see what we see.
Of the 182 rejections, 130 of them arrived before the average return time and a whopping 166 arrived before the estimated return time. That’s 71% and 91% respectively. So, it looks like responses to rejections do typically arrive faster. But what about the rejections that took longer than the average and estimated return times? Anything special about them? Well, sort of. The percentage of personal rejections, further considerations, and shortlists was definitely higher, about 31%, as opposed to about 15% in the rejections that arrived quicker. So it does seem like you’re more likely to get a “better” rejection when your story is held longer, but it’s important to understand that a lot of top-tier markets only send form rejections, even if your story is held quite a while.
Does the great theory–that a story held longer is more likely to be accepted–hold water? I wish I had more conclusive evidence that it does, but I don’t. That likely has a lot to do with the markets that accepted my pieces that also had all the data I needed. So I’d say the jury is out. As for rejections, I think I have enough of those to state it does seem like a story held longer is more likely to receive a “good” rejection, a personal note, a further consideration, etc. I had a much larger group of submissions and publisher there, so it’s possible those results do support the idea that acceptances take longer too.
Of course, all this is classic rejectomancy and should be viewed as such. In other words, don’t get too hung up on how long your story is being held. It might mean something, and it might not, but you can definitely increase your anxiety level by obsessing over it. (This is absolutely a “do as I say and not as I do” moment.)
Thoughts on this? Evidence of your own? I’d love to hear about it in the comments.
“If the great theory holds, then all my acceptances should exceed the average return time and probably the publisher’s estimated return time.”
Since different publishers have different response times, in order to test this theory, wouldn’t we need to convert that number from “#Days” to “length of time as a percentage of average return?”
If Publisher A generally responds within 30 days, and Publisher B generally responds within 60, then my 25 days at A is more meaningful than 25 days at B
So now I need you to go back to your spreadsheet and add a column:
#DaysTilResponse / #DaysAvgResponse
And then recalc all this against that…. 😉