For those who are interested, these predictions are used as the basis for the CFG Analysis Games Pick 'Em. For more information on that contest, see the original post. Please post your contest entries to comments on that post, NOT this one. Feel free to comment on this post, just don't put your contest entries there.
I won't bore you with too many details before we get to the picks, but here are some key points about the methodology:
- For the most part, the concept is the same as was done last year. For a full run-down, see my methodology post from last year. The basic idea is that we're using the regional results and the Open results from this season in a variety of combinations to simulate what might happen at the Games.
- In general terms, the picks are based 80% on the Regionals, 15% on the Open and 5% on last year's Games.
- The only information used from last year's Games were the athletes' results from the half-marathon row and the Burden Run. The reason for using these two is that there are no regional events of this length, so hopefully these events will give some insight into how the athletes will fare if (when) an event of that length comes up. For athletes that didn't compete last year, they get a random result on that event in each simulation.
- The regional results have been adjusted to reflect the advantage that athletes in later weeks have over athletes in the earlier weeks (whether it be from additional training or better strategy). I've done this the past two years, but this year the impact of each additional week was stronger than in past years. The one region that I made an extra adjustment for was the North East, since that event was held outside. I treated it as if it had been in week 1 rather than week 4.
- No advantage is given to returning Games athletes, even for Rich Froning. Certainly some will disagree with that, but we've seen time and again that athletes come out of nowhere (Garrett Fisher 2013, for instance) and past podium athletes can fall off (Matt Chan 2013, for instance). I'll probably devote a post in the next two weeks to looking at how much (if any) Games experience plays a role in predicting an athlete's success, beyond their performances so far this season.
- There are some athletes who are listed with a 0.0% chance of finishing in certain spots. Obviously every athlete has at least some chance of winning, but this method simply isn't going to account for such true long-shots. Last year, the longest shot on either side to finish in the top 10 based on my picks was Anna Tunnicliffe at 3%.
- As always, these picks aren't a personal judgment about any athlete, and of course, they are just for fun. Much respect for any athlete that even makes it to this level to begin with.
With those items out of the way, let's get on with the picks. These picks are subject to change in the event that athletes drop out prior to the competition (or if they add a late wildcard, for some reason), but otherwise, consider them final. I will make notes in this post of any changes that have occurred.
[UPDATE 7/8: HQ just announced they will be paying out prize money for the top 20 finishers, but anywhere you see the term "money" in this post, it refers to top 10. I have re-posted these charts with the heading changed to say "Top 10", but I will not be re-doing the predictions to give odds for finishing top 20.]
[UPDATE 7/8: HQ just announced they will be paying out prize money for the top 20 finishers, but anywhere you see the term "money" in this post, it refers to top 10. I have re-posted these charts with the heading changed to say "Top 10", but I will not be re-doing the predictions to give odds for finishing top 20.]
Does money mean finishing in the top 10 ?
ReplyDeleteYes. I just made a note in here about that (after your comment). I'll change the labels on my charts, but I'm still going to predict the chances of finishing top 10, not top 20. And the contest will still be based on top 10.
DeleteThanks!
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