A Closer Look at the 2013 Games Season Programming

I struggled for the last few days on how to present this analysis. Last year, I wrote two lengthy posts assessing the programming for the 2012 Games season. I titled the posts "Were the Games Well-Programmed." While I thought those posts turned out well, I hesitated to simply follow the same template as last year, for a couple reasons:

• Plenty of people have an opinion on the Games programming, many of whom are much more known in the CrossFit community than me (for instance, I've already read analysis from Rudy Nielsen and Ben Bergeron). Do we need more opinions out there?
• Assigning grades or giving a thumbs-up/thumbs-down to the Games programming gives off the impression that I have it all figured out. I think HQ has made it clear that they work very hard not to be influenced by the outside world in their decision-making. Am I really going to accomplish anything by telling them they were wrong?

However, balancing those concerns was my feeling that I do have something unique to provide to the discussions. And, most importantly, I think the discussion is important. While I respect HQ's stance to do things their own way, I'd like to think that they are always looking for ways to improve the Games. Although I don't work for HQ, I don't feel as though I'm an outsider. Those of us in the community, and especially those who've been following and competing in the sport for years, are all working toward the same goal: to keep this sport progressing in the right direction. I know that HQ is at least marginally aware of this site, considering Tony Budding took the time to comment on my scoring system post last year. Here's to hoping they're still keeping up with me (and I promise I'll leave the scoring system out of the debate for now, Tony).

With that in mind, this post will be broken down in much the same way as last year's discussion. There are five goals I think that should be driving the programming of the Games, in order of importance:

1. Ensure that the fittest athletes win the overall championship
2. Make the competition as fair as possible for all athletes involved
3. Test events across broad time and modal domains (i.e., stay in keeping with CrossFit's general definition of fitness)
4. Balance the time and modal domains so that no elements are weighted too heavily
5. Make the event enjoyable for the spectators

What I'd like to do is assess how well those five goals were accomplished this season. Unlike last year, however, I'm making a couple changes.

• This year, I'm going to take the entire season into account in this post (last year I separated the Games programming specifically from the Games season as a whole). I've already covered the 2013 Open and Regional programming to some degree in previous posts, so I'll be incorporating some of that here. I think it's better to try to view the Games in the context of the whole season.
• I won't be giving grades for each goal this year. Instead, I'll be pointing out suggestions for improvement, because simply identifying the problems only gets us halfway there. Additionally, I'll point out things that I felt worked out particularly well. Every year, HQ does a few things that bug me, but they also do a handful of things that make me say, "Hey, that was a great idea. I wouldn't have thought of that." I think it's worth acknowledging both sides.

So with that as our background, let's get started.

1. Ensure that the fittest athletes win the overall championship

I think it's hard to argue this wasn't accomplished this year. Rich Froning was challenged, but he still came out of the weekend looking pretty unbeatable. Sam Briggs, although she did show a few weaknesses, appeared to be the most-well rounded athlete across the board by the end of the weekend, while many of the women who were expected to be her top competition had major hiccups. Both Froning and Briggs won the Open and finished near or at the top in the cross-Regional comparison.

Additionally, as I pointed out in my last post, the athletes that we expected to be at the top generally finished that way. That doesn't absolutely mean that the Games are a perfect test, but it does provide some validation when the top athletes keep showing up near the top across a variety of tests in successive years.

How We Can Do Better: I don't really have anything here. The right athletes won, so mission accomplished.
Credit Where Credit is Due: The fact that almost all the athletes competed in every event really helped keep things interesting until the end. In the past, we've seen athletes build an early lead and hang on simply because the field gets so small that there aren't enough points to be lost in the late events. Allowing 30 athletes to finish the weekend allowed some big swings at the end, including Lindsey Valenzuela's move from 5th to 2nd in the final two events.

2. Make the competition as fair as possible for all athletes involved

Because I promised Tony Budding I wouldn't bring up the scoring system in general, I won't touch on that here. Let's just say I think the scoring system is fair enough. However, the way the scoring system was applied in Cinco 1 and 2 didn't make a whole lot of sense. Any athlete who didn't finish the handstand walk (Cinco 1) or the lunges (Cinco 2) was locked in a tie, despite the fact that the lunges took 2-4 minutes and the separation was very clear between many athletes who were tied. Because of the massive logjam (21 male athletes tied for 7th, 13 female athletes tied for 4th), the few athletes who did finish didn't get that big of a point spread on many other athletes who were on pace to be several minutes behind.

The other issue here is judging, which does tie in with programming to some extent. I think the judging continues to improve each year. Anyone who's been to a local competition has seen the judges who just don't have the stones to call a no-rep. That simply doesn't happen at the Games. You cannot get away with cheating reps, and that's definitely a good thing for the sport.

I won't dwell on it here, but everyone knows the judging in the Open is still a concern (see 13.2 Josh Golden/Danielle Sidell fiasco this year). Hopefully some careful programming will alleviate that next year.

How We Can Do Better: Improve tiebreakers for movements such as walking lunges, handstand walks, running, or anything where a distance is involved instead of a number of reps. Also, I'd prefer to have Games athletes not perform chin-to-bar pull-ups. They are really tricky to judge and aren't as impressive to spectators. In fact, the whole "2007" event just didn't really work for me; it seemed like basically a pull-up contest for the athletes at this level.

Credit Where Credit is Due: Chip timing helped identify the winners really nicely in some of the shorter events. Also, judging keeps improving each year.

3. Test events across broad time and modal domains (i.e., stay in keeping with CrossFit's general definition of fitness)

Right off the bat, let's look at a list of all the movements used this season, along with the movement subcategory I've placed each one into. I realize the subcategories are subjective, and an argument could be made to shift a few movements around or create a new subcategory. In general, I think this is a decent organizational scheme (and I've used it in the past), but I'm open to suggestions.

It's pretty clear that the CrossFit Games season is testing a very wide variety of movements, and the majority of those were used in the Games. Even some that were left out of the Games, like ordinary burpees* and unweighted pistols, were used in other forms (wall burpees*, weighted pistol). No major movements that we've seen in the past were left out of this entire season, with the exception of back squats. I've seen some suggestions online about testing a max back or front squat in the future, as opposed to the Olympic lifts that we have been seeing a lot.

Another key goal is to hit a wide variety of time domains and weight loads. Below are charts showing the distribution of the times and the relative weight loads (for men) this season. The explanation behind the relative weight loads can be found in my post "What to Expect From the 2013 Open and Beyond." Two notes: 1) some of the Regional and Games movements had to be estimated because I don't have any data on them (such as weighted overhead lunge and pig flips); 2) the time domains for workouts that weren't AMRAP were rough estimates of the average finishing times.

Although most of the times were under 30 minutes, we did see a couple beyond that, including one over an hour (the half-marathon row). As for the weight loads, we saw quite a range as well. The two heaviest loads were from the max effort lifts (3RM OHS and the C&J Ladder), but there were also some very heavy lifts used in metcons, mainly in the Games (405-lb. deadlifts for crying out loud). Still, lighter loads were tested frequently in early stages of competition (Jackie, 13.2, 13.3).

How We Can Do Better: I like the idea of testing a max effort on something other than an Olympic lift.

Credit Where Credit is Due: Nice distribution of time domains, and no areas of fitness were left neglected entirely. CrossFit haters can't point to many things and say 'But I bet those guys can't do X.' Yeah, they probably can.

4. Balance the time and modal domains so that no elements are weighted too heavily

Based on the subcategories of movements I've defined above, let's look at a the breakdown of movements in each segment of the 2013 Games Season. These percentages are based on the weight each movement was given in each workout, not simply the number of times the movement occurred (for example, the chest-to-bar pull-ups were worth 0.50 events in Open 13.5, but they were worth only 0.25 events in Regional Event 4).

One thing that surprised me was how little focus there was at the Games on basic gymnastics (pull-ups, push-ups, toes-to-bar, etc.). However, there was quite a bit of bodyweight emphasis (high-skill gymnastics like muscle-ups and HSPU), as well as some twists on other bodyweight movements (wall burpee, weighted GHD sit-up). Overall, bodyweight movements (including rowing) were worth 60% of the points and lifts were worth 40%.

Another surprising thing was how much emphasis there was on the pure conditioning movements like rowing and running. Now, one of the "running" events was the zig-zag sprint, which wasn't actually about conditioning but rather explosive speed and agility. Still, the burden run and the two rowing events really put a big focus on metabolic engine and stamina. I have no problem with this, but what I would like to see is these areas tested more early on. Running in the Open is almost impossible, but at the Regional level, it would make sense to test some sort of middle- or long-distance runs so that athletes who struggle there would have those weaknesses exposed.

As far as loading is concerned, what seems to be happening at the Games in recent years is that things are either super-heavy or super-light. Only two of 12 events tested what I would consider medium loads (somewhere around a 1.0 relative weight for men, like 135-lb. cleans or 95-lb. thrusters), and none tested light loads. Also, as noted above, the bodyweight movements that were required were generally extremely challenging. I personally wouldn't mind seeing some more "classic" CrossFit workouts involved, like we saw with "The Girls" at the end of last year's Games.

Whereas last year's Games seemed to be lacking in the moderately long time frame (12:00-25:00), I think they did a better job of spreading things out this season. In the Games, we had 1 event over 40:00, 3 between 12:00 and 40:00, 4 between 1:00 and 15:00 and 2 that were essentially 0 time.

One other way to see if we're not weighting one area too much is to look at the rank correlations between the events. If the rankings for two separate events are highly correlated, it indicates that we may be over-emphasizing one particular area. For this analysis, I focused only on the Games, because it's not really such a bad thing if we test the same thing in two different competitions since the scoring resets each time, but within the same competition, it's more of a problem. 

I looked at the 10 Games events in which all athletes competed, which gave me a total of 45 unique combinations for men and 45 combinations for women. Of those combinations, only 8 had correlations greater than 50% and only 3 had correlations greater than 70%. Not surprisingly, the 2K row and the half-marathon row were highly correlated for both men and women (54% for men and 81% for women). Also, the Sprint Chipper and the C&J Ladder were strongly correlated (70% for men and 54% for women), likely because they both had a major emphasis on heavy Olympic lifting. One surprise was that the burden run and the 2K row were 79% correlated for women, but I think that may have been somewhat of a fluke, considering the correlation was just 31% for men.

In the end, most events appeared to test pretty distinct aspects of fitness, which is a good sign.

How We Can Do Better: Fans love the heavy movements, but I'd suggest supplementing those with some more moderate weights as well. CrossFitters can relate to someone crushing a workout even if the weight it not enormous (those Open WOD demos weren't bad to watch, were they?) Also, let's test running earlier in the season.

Credit Where Credit is Due: We saw events where even Rich Froning and Sam Briggs found themselves near the bottom, which tells me we are really testing a wide range of skills. And actually, I liked limiting the Games to 12 events (instead of 15 last year), because in my opinion that was sufficient and we didn't wind up double-counting too many areas.

5. Make the event enjoyable for the spectators

Unfortunately I don't have any data to back this up, but in my opinion, this is the area that I think has improved the most in recent years. I think a nice touch at the Games is that in multi-round workouts, each round is performed at a different point on the stage. This really helps the audience follow the action and builds the drama as you see athletes progress through the workout.

Making all the events watchable was also nice after Pendleton 1, Pendleton 2 and the Obstacle Course were unavailable last season. The burden run had many of the same qualities as an off-road event, but it was all done on site and finished up in the soccer stadium.

However, as nice as it is to use the soccer stadium to allow more spectators, the vibe at those events is considerably more subdued. Perhaps HQ will be able to find a way to improve this in the future, but it seems that this sport isn't quite as conducive to viewing from such a distance. By contrast, the intensity in the night events in the tennis stadium is fantastic.

How We Can Do Better: Figure out a way to make things a bit more exciting in the stadium. It won't be easy, but there's no denying that things weren't quite as intense when the workouts were held there.

Credit Where Credit is Due: The Games are truly becoming more of a spectator sport. Even the uninitiated can see the action unfold and understand and appreciate what's going on. And although I mentioned it above, the improvements in judging have helped the spectator experience.


*I decided to break up "wall burpees" into burpees and wall climb-overs. Each were worth 1/6 of the value of that workout (snatch was 1/3 and weighted GHD sit-up was 1/3). This was updated on 8/22/2013.

Which Have Been the "Best" Events This Season?

If you've been reading my blog for any length of time, you know that one of the ways I like to evaluate the effectiveness* of a CrossFit event is by looking at how well the results from that event correlate to results from a variety of other events. I laid out the theory behind this in my post from last year titled "Are certain events 'better' than others?", but I'll recap it here:

• In a competition setting, what we are trying to do is learn as much about each athlete's overall fitness level as possible.
• We only have a limited number of events to do this, particularly in the Open and at Regionals. Therefore, we need to maximize the information we get from each event.
• If athletes who score well on a particular event tend to score well across the board, then that event is probably a good indicator of overall fitness. Conversely, if the results from that event don't correlate at all with results in other events, then maybe that particular event did not really tell us much.

Overall, this year's regionals and Open were set up well for me to do this type of analysis. I did this same analysis after last year's regionals, but due to the cuts after regional event 5, I was left with only about 250-300 athletes of each gender who completed all the Open and Regional workouts, and this limited the analysis to only the very elite athletes. I also did this analysis after the Open this year, which gave me a huge sample of athletes, but with only 5 events, I didn't really have a "wide variety" of events to evaluate. 

This year, because we did not have any cuts at Regionals, I was left with 673 men and 512 women who have completed all 12 events this season. Although these are all still very solid athletes, I got a lot more of the borderline regional competitors in the mix than I did last year. Remember, a "good" event for the Games might not make a "good" event for a competition within your own box. So keep in mind with this analysis that we are evaluating these events based on how well they predict overall fitness for Regional competitors.

The methodology for performing this analysis this year was the following:

• For athletes who completed all events this year, compile their results (not just their ranking) for each of those events. The Regionals results I used are those that have been adjusted to account for the week in which week each athlete competed. See my previous post for more info on those adjustments.
• Rerank the entire field in each of those events.
• For each event, calculate the sum of each athlete's ranks in all other events.
• Calculate the Pearson correlation (referred to from here on out as simply "correlation") between the ranks in each event and the sum of ranks in all other events. Higher correlations indicate "better" events.

Below are the results for both men and women.

The pattern that emerges is one I've noticed pretty much across the board since I've been doing this type of analysis: events with more movements tend to be better tests of fitness. This makes sense intuitively, since they test more things, by definition. That doesn't mean we shouldn't have single-modality events in competition, it just means they probably should be used sparingly and only for movements that are deemed very important.

You may notice that Open Event 2, which had three movements, is bucking this trend by falling quite close to the bottom. The concerns with this event were pretty well documented during the Open: judging was very difficult, the weights were extremely light for top competitors, and the option of step-ups was utilized by a lot more athletes than was probably expected. So simply because you have 3 or 4 movements in an event doesn't make it a great one.

To get a visual interpretation of the concept I'm getting at here, below are scatter plots for some of the best and worst events from this year. On each graph, the x-axis represents each athlete's rank on that event and the y-axis represents each athlete's combined rank on all other events.

It should be fairly clear that for the first two graphs, there is a clear relationship between the x- and y-axis. Athletes who did well on these events generally did well across the board. On the third graph, the points are much more scattered, indicating that there were plenty of athletes who did well on Open Event 2 who didn't fare well across the board, and vice versa.

Although I consider the results using the entire Regional field to be the most useful, I also tested performed this analysis on three other subsets of the regional field:

1. Games athletes only
2. Top 292 men and top 258 women (same number as I had in my analysis last year)
3. Random sample of 20% of the entire regional field

What I was interested in was how volatile my results were. For instance, is Regional Event 1 really better than Regional Event 4 for women (76% vs. 74%)? Would that hold up if I changed the group of athletes a bit?

In general, the events near the very top and the very bottom stayed in that vicinity, with a couple of exceptions. Here are the main takeaways:

• For men, Regional Event 4 was in the top 3 across all the samples and Open Event 1 was in the top 5 across all the samples. For women, Regional Event 4 was in the top 4 across all the samples, Regional Event 1 was in the top 5 across all the samples, Open Event 1 was in the top 5 across all the samples and Open Event 4 was also in the top 6 across all the samples.
• Considering HQ is programming the same events for both men and women, I would conclude that Regional Event 4 ("The 100s") and Open Event 1 (AMRAP 17 of burpees and snatch) were the best events this season. In one of my 2013 Open recap posts, I noted that 13.4 was generally the best event of the Open. I still feel that it was a very good event for the entire Open field, but it wasn't quite as strong when we look at just these stronger athletes. 
• Across both men and women, Open Event 2, Regional Event 5 and Regional Event 3 were each in the bottom 4 in all but one sample. I would conclude that these were generally the three weakest events this season. 
• I mentioned some issues with Open Event 2 above.
• For Regional Event 5, I think the issue is that we saw a lot of athletes near the bottom of the field do well on this simply because they could deadlift a house. If you could handle the deadlifts easily, you could generally do well even if you weren't particularly great at box jumps or had sub-par aerobic capacity.
• For Regional Event 3, I think the issue was that the burpees did not really factor into this much, making it basically just a muscle-up test. As far as single-modalities go, this wasn't too bad of an event. But personally, I think this event and the overhead squat ladder (a true single-modality) should have been worth only 50% of the other events.  
• Two of the events featuring box jumps turned out to be relatively modest tests of fitness. Throw in all the complaints about achilles problems we've seen popping up recently, and I think HQ may want to look into adjusting how they program box jumps. I think box jumps are a good test of fitness in general, but I'd personally love to see us go to box jump-overs (onto and over the box with an option to jump straight over) in the future.
• With the exception of Open Event 2 and Regional Event 5, I think the rest of the events were generally solid. As I mentioned above, I might consider adjusting the point value for a couple of the other ones.

I also did one final analysis, primarily out of curiosity. Using the entire Regional field, I looked at the correlation between each pair of events. Some of the interesting findings:

• In general, the most highly correlated pair was Regional Event 4/Regional Event 1 (71% for women and 67% for men). This is somewhat surprising given how the time domains were completely different, but both involved pull-ups and a light thruster-type movement (bar thrusters or wall-balls).
• The two muscle-up workouts (Regional Event 3 and Open Event 3) were highly correlated (68% for women and 55% for men).
• Regional Event 5 and Regional Event 7 were highly correlated (56% for women and 68% for men). Both were extremely heavy.
• The least-correlated pair was Regional Event 3/Regional Event 5 (17% for women and 19% for men). Shouldn't be a surprise considering one was bodyweight only and one involved extremely heavy deadlifts. The pair of Regional Event 2/Regional Event 3 were also not very correlated (38% for women and 22% for men). Remember those occurred within 2 minutes of each other.

That's about it for today. This is always one of my favorite analyses to work on, but with the Games fast approaching, I suppose it's about time to start tackling the tough questions and making some predictions. Will Froning three-peat? (Probably) Who will emerge on the women's side with Annie out? (It's wide-open) Will the first event of the Games take more or less than 4 hours? (God, I hope so) What bizarre contraption will Rogue unveil this year? (Potentially a flying bicycle, similar to the one in E.T.) Who will wear the shortest shorts this season? (Stacie Tovar still the champ until proven otherwise)

Anyway, until next time, good luck with your training!

*I am referring to the effectiveness of this event as it relates to competition. In other words, is this event a good test of fitness. This does not necessarily mean the event is good or bad for training purposes. For instance, I feel that 13.2 was not a good workout for testing (due to a lot of factors, like how difficult it was to judge and how light it was for the top competitors), but in training, I think it would be a good workout for building aerobic capacity (and it definitely left me hurting).

A Fairer Regional Comparison: 2013 Edition

Today's post will mark an anniversary of sorts for my blog. Roughly a year ago, I put up my first post, in which I produced adjusted worldwide Regional rankings, accounting for the advantage gained by athletes in the later weeks. The post went up with little fanfare, and I imagine many people who started coming to this site via Rudy Nielsen's Outlaw Way blog may not have even read this original post. In hindsight, it was probably overly technical, but give me a break: it was my first post.

Well, today I'll be doing essentially the same thing for this year's regionals. But first, let me clarify what I believe these rankings really mean. They are not my predictions for the Games, and they are not a ranking of the best CrossFitters in the world. Rather, what they are is an attempt to understand who would win if the exact same Regional events played themselves out at the Games. If all the Games qualifiers competed together, at the same time, using the Games scoring system, who do we believe would win? Certainly this gives us a good starting point to discuss who may win the Games (hint: Rich Froning has a shot!), but it's not a prediction for the Games.

Many of you have probably seen a version of these rankings at http://crossfitregionalshowdown.com/leaderboard/men and http://crossfitregionalshowdown.com/leaderboard/women. These are certainly informative, and in fact I grabbed all the original results from this site, so I really appreciate the work they've done. But my feeling has always been that the athletes in the later weeks have an advantage that isn't captured in these rankings. It stands to reason that having additional weeks to prepare, watch other competitions and game plan the events has to give athletes some advantage.

To get an idea of the advantage across the entire field, I ranked all athletes that finished all 7 Regional events based on their worldwide Open rank. Then I ranked them by their worldwide Regional rank (from the sites listed above). For each region, I looked at the average change from Open rank to Regional rank, then plotted them along with the week in which each region competed. This is shown in the chart below, with lower numbers representing improvements from the Open to Regionals.

You can see that while there is variation, the latter weeks clearly tended to have better scores from athletes, relative to their Open performance. This isn't a perfect metric: for one, some elite athletes don't take the Open as seriously as others, but also, it gets skewed at the each end because the top athletes in the Open can only get worse and the worst athletes in the Open can only get better. Still, this tells us that something is probably going on. For women, the same effect is there, but it's not quite as pronounced.

To attempt to account for this, I performed a series of two-variable linear regressions. For each event, I used the event result (the actual result*, not the ranking) as the dependent variable, and for one of the independent variables, I used the week of the athlete's region. For the other independent variable, I used either the athlete's 2012 Regional ranking (if he/she competed individually in 2012) or the athlete's 2013 Open ranking (if he/she did not compete individually at Regionals in 2012). Then I looked at the coefficient for the week of competition - this would give an indication of the impact of the week of competition, after controlling for the athlete's ability.

I then divided the coefficient by the average result on that event for all athletes to get the percentage impact of the week of competition. Depending on some of the summary statistics and using a bit of judgement, I arrived at a final adjustment factor for each event (some were 0 if the results didn't appear significant enough). If the adjustment factor for event 1 was -1.0%, then for every week beyond the midpoint (week = 2.5), I adjusted the athlete's score up by 1.0%. If the athlete competed in week 4 and his score was 6:00, then his adjusted score becomes (6:00 / (1 - 1.5%)) = 6:05. If the athlete competed in week 1, his adjusted score becomes (6:00 / (1 + 1.5%)) = 5:55.

Below are the adjustment factors I used for each event for men and women:

• Event 1: -0.6% (men), -0.5% (women)
• Event 2: +0.7% (men), +0.8% (women)
• Event 3: -0.7% (men), none (women)
• Event 4: -0.2% (men), none (women)
• Event 5: none (men), none (women)
• Event 6: -1.5% (men), none (women)
• Event 7: -1.8% (men), -2.2% (women)

As you can see, these are not particularly aggressive adjustments. I think with the first wave of athletes having several weeks to prepare, the advantage is not dramatic each week beyond that. And for women, certain movements like muscle-ups and handstand push-ups are simply so troubling for many athletes that no amount of game-planning in a few weeks can make a significant difference.

For those who care, a couple notes on differences from my modeling last year, as well as some limitations:

• This year, I used all Regional athletes. Last year I only used those who completed all made the cut to the final event, but since there were no cuts this year, I used everyone.
• This year, I performed the regression across the individual athletes. Last year, I summarized up to the region level first before performing the regression. I think this year's method is preferable; last year I summed up first because I didn't have access to everyone's Open results, so I just counted up the number of athletes in each region in the top 180 worldwide as a proxy for region strength.
• This year, I included Asia, Africa and Latin America in running the regressions. Last year, I excluded them.
• I made no adjustments for the weather conditions at the outdoor regions. I realize that the elements may have made things more difficult, but with only a couple regions competing outdoors, it is difficult to assess just how much impact this had.
• I used no tiebreakers. If two athletes tied, they just stayed tied. Sue me.

OK, let's cut the chit-chat and get to the results. The tables below show my adjusted worldwide Regional rankings, along with the rankings if I had not made any adjustments for the week of competition and the rankings if I had not made any adjustments and used Regional scoring.

My adjustments were generally smaller on the women's side, so there wasn't a ton of shifting on that side of the leaderboard. For the men, we definitely saw some big jumps. Among the biggest winners with my adjustments were:

• Josh Bridges (7th to 4th)
• Lacee Kovacs (28th to 18th)
• Travis Mayer (32nd to 23rd)
• ZA Anderson (34th to 24th)
• Mikko Salo (30th to 22nd)
• Daniel Tyminski (18th to 14th)
• Marcus Filly (26th to 20th)
• Valerie Voboril (20th to 17th)
• Kristan Clever (31st to 28th)
• Katrin Tanja Davidsdottir (35th to 32nd)
• Talayna Fortunato (14th to 12th)

That's all for now, folks. Next week, I plan to look into all 12 events we've seen so far this season and see which ones were "better" than others. Until then, good luck with your training.


*For events 3, 4, 6 and 7, I added additional time for each rep still left at the time cap, since the 1 second per rep they have listed is not realistic. For events 3 and 7, I added 15 seconds/rep. For event 6, I added 10 seconds/rep. For event 4, I added 5 seconds/rep.

Quick Hits: Regional Reaction and Upcoming Schedule

It's been quite a ride the last four weeks of regionals, and to be sure, there is plenty of analysis to be done before we get to the Games in a few weeks. But for now, I just want to get some general thoughts together about the Regionals and my experience watching the Central East. I'll also look briefly at how my projections turned out, as well as what I plan to post over the coming weeks.

Let's get started:

• Watching the Central East regionals this past weekend solidified in my mind that CrossFit as a sport has staying power. The stands were legitimately packed all weekend, and some of the roars from the crowd were unlike anything I've heard at a CrossFit event before. In particular, one moment that stands out was the end of men's event 6 with Rich Froning chasing down Dan Bailey on the lunges. When Dan put the bar down halfway through, the crowd just sensed that Rich had a shot, took their energy to another level, and of course, Rich delivered, gutting out the entire 90 feet to take the event. Few other sports let the spectators really see that type of will and determination to endure pain, and on a regular and repeated basis. It's one of the reasons I've always enjoyed watching track and field, but I think the variety of CrossFit pushes the athletes to places they have never been to before. I think any fan of sport can appreciate seeing that.
• There's no question that the Central East men's region was hands-down the most competitive region. What is up for debate is whether HQ should do anything to remedy the situation. I think inviting athletes solely based on a worldwide regional ranking is not a smart idea - not unless the Regionals are all held on the same weekend and under identical conditions. That means no more outdoor events, and it probably means we all get to watch less of the action. But perhaps some sort of last-chance qualifier might be worthwhile for those in the top 10 of their region? Seeing athletes like Nick Fory and Gerald Sasser miss out on the Games despite putting up scores that would win several other regions is frustrating (see http://crossfitregionalshowdown.com/leaderboard/men).
• After making some adjustments based on the actual results that came in for the overhead squat workout, I recalculated the average relative weight and the load-based emphasis on lifting (LBEL) for this year's regionals. For both men and women, the average relative weight was higher than both 2011 and 2012, but the LBEL was lower. The way I interpret that is that the minimum strength required to be competitive at regionals was very high this year (high relative weight), but for those that could handle the required weights, the competition generally favored the smaller athletes (low LBEL).
• I'd still like to see running more involved in the regional competition. I know there are logistical issues, but it seems silly that in selecting the fittest athletes in the world, no one is required to run more than 800 feet (and even that 800 feet of running, in event 7, is little more than a light jog to recover). How about at least some shuttle sprints? Or a longer run on Friday when fewer people are able to attend anyway?
• On the men's side, it's going to be almost impossible to pick against Rich Froning for the Games. The guy is an absolute machine with virtually no weaknesses. Unless every event is under 4:00 or over an hour, I don't see a lot of scenarios where he doesn't win.
• For women, things are wide open. If Annie comes back, she's got a great shot (after the inevitable backlash against HQ for inviting her). Either way, Sam Briggs and Camille Leblanc-Bazinet look awfully solid all-around, and some of the stronger athletes like Elizabeth Akinwale and Linsday Valenzuela have become more well-rounded in the past year. There are others in the mix as well (Talayna Fortunato, Amanda Goodman, Kara Webb, Rebecca Voigt, etc.).

As for my predictions last week, things turned out fairly well. I totally whiffed on two athletes who made the Games (Lindy Wall and Jordan Troyan). For Wall, at least I have an excuse: last year, she was Lindy Barber, so I did not account for the fact that she was 6th at regionals a year ago. Had I known that, she would have been given a 16% chance instead of the 6% I originally gave her (I didn't even list her among top contenders on the site). With Troyan, although he was 10th at Regionals last year, he didn't have a great Open performance this year (20th in his region), so I just didn't see that one coming.

If I give myself a pass on that, then I ended up with a mean square error of 0.044 across the final two weeks (I predicted a total of 8 regionals). This was significantly better than any of the "default" estimates I mentioned last week. The best of those estimates would have been giving my top 3 athletes in each region a 100% shot, which would have produced a MSE of 0.052. There's always room to improve this modeling, but I think it was a decent start in my first year attempting to predict the regionals.

OK, finally, here's a quick listing of topics I plan to touch on between now and the start of the Games:

• A look at all the events thus far to see which are most correlated with success across a wide variety of events (i.e. which events are "better"). I did a very similar analysis last year and did a shortened version of it after this year's open.
• Adjusted worldwide regional rankings to account for the advantage gained by competing in a later region (and possibly other factors). This will be very similar to my inaugural post on this site approximately a year ago.
• Games predictions. I'll definitely do some sort of stochastic prediction to give each athlete odds of winning the Games (and potentially the odds of finishing second, third, etc.). I may separately do a best estimate of who will finish in the top 5 or 10.
• Perhaps a scientific wild-ass guess (SWAG) about some of the events we could see at the Games. This seemed to be pretty popular during the Open, and of course it requires little-to-no hard work on my part.
• Maybe a bit more analysis on the Open now that I've got a more complete dataset (thanks again to Michael Girdley at girdley.com for hooking me up with that data). This could wait until after the Games, depending on time.

If you've got other ideas, by all means let me know. Looking forward to the Games in just six short weeks. I've got my gold ticket, and I hope you all do, too!

Week 4 Predictions: Let the Big Dogs Eat

OK, so I may be a little biased living in Indianapolis, but I think I'm justified in saying that the Central East men's competition is really the crown jewel of the Regional season. I'll be headed down to Columbus, OH to watch Saturday and Sunday in person, and I have to say I'm pretty pumped. The numbers for this region are staggering:

• The winner of the last three CrossFit Games has come from the Central East (Graham Holmberg 2010, Rich Froning 2011-12). Both men are competing this weekend.
• The Central East produced five men in the top 10 of the 2012 CrossFit Games. All five are competing this weekend.
• Two other men competing this weekend qualified for the Games in 2011: Nick Urankar and Joseph Weigel. Urankar was 6th at the regional last year.
• Four of the top 20 Open finishers worldwide and six of the top 43 are competing in this region this weekend.

Thank goodness for the rule allowing extra spots for former champions, because limiting this region to only three spots would be damn near inhumane. Five doesn't even seem quite enough, frankly. Eight competitors from this region were in the top 31 of the worldwide regional standings last year. There are some other great athletes competing this weekend (Ben Smith, Nate Schrader, Lucas Parker, Christy Phillips, etc.), but you can't deny the strength of the Central East men's region as a whole.

The competitiveness of this region also forced me into making some adjustments to my modeling this week. For background on the process of generating these projections, please see my prior post.

Change one this week was the fact that I decided I could not treat Froning like the other competitors. Realistically, the only way he's not making the Games is due to injury. My solution was to give him an 80% chance of finishing top 10 worldwide and a 20% chance of finishing 11-25 worldwide. This leaves open the chance that he could get beat, but only in a scenario where several other guys put up crazy numbers.

Change two was to adjust all my projections to give more of an advantage to the top competitors. My solution was to do the following:

• For each category, look at last year's results and calculate how often athletes in that category finished in the top 25 worldwide. Last week, I calculated how often they finished top 50.
• Additionally, calculate how often they finished between 26-75 worldwide. Last week, I calculated how often they finished 51-100.

The reason for making this change was that in really competitive regions, too many athletes were getting put into that top 50 range. From there, it was just a crapshoot to see who drew better random numbers and qualified for the Games. Now, it's less common for athletes to get into that top 25 category, so doing so gives you a big advantage. For instance, athletes in the top category (top 15 at Games last year) have an 83% shot at finishing top 50 and a 65% shot at finishing top 25. The next highest category (16-50 at Games last year, top 40 worldwide in Regionals last year) had an 81% chance at finishing top 50 but only a 41% shot at finishing top 25. This gives us more separation for the top athletes.

Still, the Central East has five men who all qualified for my top category. The fact is, it's tough to separate them: who would you pick not to make it from those five? But then again, you also have Nick Urankar, who is really solid (26th worldwide in the Regionals last year), and there are others who could legitimately slip into the top 5. As a result, my projections don't look that great for some men that you'd generally consider to be locks for the Games. I'm not sure that's necessarily wrong.

One final note: I made the assumption that if Froning or Holmberg is in the top four, the region gets four spots. If both are in the top five, the region gets five spots. This means if Froning is 5th and Holmberg is 4th, they both still get in. Technically, this isn't how the rules are laid out, but after HQ invited 4th place Kristan Clever from SoCal, I think it's a safe bet that they'd do the same for these guys.

Before I move onto this week's picks, let's look at how last week's picks turned out. Overall, I think pretty well:

• Of the 12 qualifiers from regions I projected, 4 were given more than a 50% shot at making it. There were also 3 athletes who I gave more than a 50% shot who did not make it.
• According to my picks, the longest shots to qualify were Alex Nettey at 16%, Zach Forrest at 18% and Matt Hathcock at 18%.
• If we look at the mean square error (MSE) for my picks compared to some other naive estimates, they did pretty well. 
• The MSE for my picks was 0.045.
• If you had given everyone in each region an equal shot, your MSE would have been 0.064.
• If you had given a 100% chance to the top 3 in the Open in each region, your MSE would have been 0.078.
• If you had given a 100% chance to my top 3 in each region, your MSE would have been 0.057.

So overall, a decent showing. As mentioned above, I made some adjustments, so we'll have to see how they turn out.

As I did last week, I'm limiting these picks to the four regionals that will be broadcast. In this case, that's the Central East men and women and the Mid Atlantic men and women. Without further ado, here are the athletes with the best shot at qualifying from those regions this weekend:

Enjoy the weekend, everyone!

Week 3 Predictions: #Spealler and Stochastic Modeling

Welcome back for week 3 of the regional season. Looking at this slate of regions (Asia, North Central, North West, South West), it's pretty clear what sticks out: #spealler. What everyone wants to know is whether or not Chris Spealler can qualify for a 7th time, and if so, will he do it in as dramatic fashion as last year?

I'll attempt to answer that question in a couple of ways. One way is just based on experience watching the sport, sizing up the events and going by "feel" to some degree. The other way is to look at Spealler's chances the same way I'll be looking at everyone else's chances: with some stochastic modeling.

Before I get back to Spealler, I'll give an overview of how I did the modeling this week, because it's quite different than my week 1 and 2 predictions. This week, I wanted to look not only at who is most likely to qualify, but how likely they are to qualify. In other words, I wanted to estimate the probability of each athlete qualifying to the Games.

In short, this is done as follows:

• Based on their performance in the 2012 Open, 2011 Games and 2011 Regionals, separate the 2012 Regional competitors into various categories.
• See how frequently athletes in each category posted a very high (top 50 worldwide) or relatively high (50-100 worldwide) regional performance in 2012 (based on the cross-regional rankings last year).
• For each athlete this year, place them in one of the categories based on their performance in the 2013 Open, 2012 Games and 2012 Regionals.
• Depending on their category, randomly generate a worldwide ranking for each athlete this year. The category affects this randomized worldwide ranking, i.e. those who had better results in the past year will generally get a better randomized worldwide ranking this year.
• Re-rank all athletes within a region based on these randomized worldwide rankings.
• Repeat 1,000 times and see how often each athlete qualifies for the 2013 Games.

Now, for those so inclined, here are a few details on this process:

• To get a large enough sample size to build this model, I combined men and women.
• The process for creating the categories of competitors was not straightforward. There was quite a bit of judgment on my part to make sure that each category had sufficient athletes to be credible and that the categories produced results that made sense with each other. For instance, I wanted to separate out the top 2011 games competitors (I chose top 15), but that meant I could not further break those athletes down based on 2011 regional rank, because there just would not be enough athletes there to get a credible sample.
• The process for randomly generating the numbers is as follows:
• Generate a uniform random number between 0 and 1 (=rand() in Excel). If the first is lower than the athlete's chance of finishing in the top 50, assign him or her to the top 50. If not, then if it is lower than the athlete's chances of finishing in the top 100, assign him or her to be between 50-100. Otherwise, the athlete is assigned to be between 100 and 150.
• Once we have assigned the athlete to the a range of ranks, generate another uniform random number between 0 and 1. Multiply this by 50 to get the athlete's exact place within the range. Generally, you'll need to be in the top 50 worldwide to qualify, but depending on how other athletes fare, it's possible to end up in the 50-100 range and still be in the top 3.
• Here is a lifting of the categories I used to break down the athletes:
• Top 15 at prior Games
• Below 15 at prior Games, top 40 worldwide at prior Regionals
• Below 15 at prior Games, below 40 worldwide at prior Regionals
• Did not make prior Games, top 50 worldwide at prior Regionals, top .5% in current Open
• Did not make prior Games, top 50 worldwide at prior Regionals, below .5% in current Open
• Did not make prior Games, 50-100 worldwide at prior Regionals
• Did not make prior Games, below 100 worldwide at prior Regionals, top 1% in current Open
• Did not make prior Games, below 100 worldwide at prior Regionals, below 1% in current Open
• Did not make prior Games, did not compete at prior Regionals, top 0.2% in current Open
• Did not make prior Games, did not compete at prior Regionals, 0.2-1.0% in current Open
• Did not make prior Games, did not compete at prior Regionals, below 1.0% in current Open

OK, before we move onto the model results, I promised some good old-fashioned analysis regarding one Chris Spealler. As I mentioned when the regional events were announced, I thought these events favored smaller athletes much more so than last year. It seems that has been the case so far on the men's side (Spencer Hendel failing to qualify and Josh Bridges dominating his regional are two pieces of evidence for this). I think Spealler will take a big hit on the overhead squat and a slightly smaller hit on the deadlift-box jump, but I see him faring well on everything else. 

There are at least 5 really tough guys in that region, so he'll certainly need to be at the top of his game. I tend to think Hathcock will break through this year, which would mean Spealler would probably need to beat out Patrick Burke in order to qualify (doubt he can beat Matt Chan). You never know with Burke since he really struggled in the Open, but he has been in the Games 4 years running. But all in all, with a gun to my head, I say Spealler makes it. I don't exactly know how, but I say he makes it.

Onto the model results. Because this process was time-consuming, and because it's most definitely in the early stages with a few kinks to get worked out, I only produced predictions for the South West and North Central this week. 

This process tends to give a lot of solid athletes a good chance of qualifying, but will rarely give anyone an extremely high chance of qualifying. Obviously, for someone like Rich Froning, I may be inclined to make some manual adjustments so that his odds go up substantially. But frankly, the Regionals are so tough these days that there are only a handful of athletes that we expect to cruise through to the Games.

This week, I have just produced the results straight up, with no modification. Take them for what they are worth: these models only take into account the performances from the past year, and obviously I have no idea how an athlete is feeling or how they have been training. On a large scale, I feel good about them, but there are certainly instances where certain athletes probably should be assigned a better chance than they are here (Kasperbauer seems like one, as you will see below, but then again, that is a very deep region).

OK, finally, below are the athletes in each region with the best chances of making it to the Games.

Enjoy the weekend everyone!

How is Jackie being won?

Friday afternoon, I saw a quote in the recap of the South Central men's event 1 recap from Mike McGoldrick: "The race is in the thrusters and pull-ups for time, so the row doesn't matter." That's always been my feeling as I approached Jackie, but is that really the case? In particular, is that the case for the athletes at the top of our sport?

To answer this question, I took a similar approach to looking at this workout as I did for Open WODs 2-5 this year (for more detail on the theory behind all this, see my post "WOD Design and Why It (Usually) Pays to be Well-Rounded"). Watching several elite athletes, I timed their splits on each movement. Once I had average times for how long each portion of the workout took, I could look at how much an improvement or decline on each portion of the workout would impact an athlete's final time.

What I did for each of the Open WODs was this:

• Use the average pace for each movement to calculate a baseline score.
• For each movement, reduce the average pace by 20%.
• For the other movements, increase their pace by an amount such that the composite pace is still 1.00. If we have 3 movements, that means increasing the pace of the other two movements by 10% each.
• Re-calculate the time for the workout. The percentage reduction in the overall score from our baseline is the "leverage" for that movement. Higher leverage generally indicates that a weakness on this movement will hurt an athlete a lot.
• Repeat this for each movement.

Based on the archived live footage of the top men's and women's heats from the South Central and Northern California, I calculated splits for as many athletes as possible. Camera angles prevented me from getting the entire field, but in total, I got 11 men and 10 women (I only included athletes for whom I could get all three of their splits). Applying the approach listed above yields these results:

These results would indicate that actually, the row is the most important movement, by a longshot. A 20% reduction in row speed really hurts the athlete, even with an improvement in the other two areas. Problem solved, right?

Well, not really. This analysis is useful, but the underlying assumption here is that an athlete might actually vary by 20% on the row just as easily as they might vary by 20% on the thrusters or pull-ups. In reality, these athletes will all post row times that are much closer to each other than that. Our average row pace for men was a 3:24 (remember, these are elite athletes only). A 20% reduction in pace would give us a 4:15 pace - none of these athletes are rowing at that pace unless they're rowing for at least 10K. On the other hand, the average athlete took 38 seconds to complete the pull-ups. A 20% reduction in speed means taking 48 seconds - that's very possible, even for an elite athlete.

What I did to try to account for this is to calculate the standard deviation in the split time for each movement. For those unfamiliar, standard deviation is a measure of how much variation there is among a set of values. The higher the value, the more variation there is. Below is a chart showing the average time for each station, the average time with pace increased by 2 standard deviations and the average time with pace decreased by 2 standard deviations*.

You can see that even though the row takes much longer, there is much less variation. The coefficient of variation (standard deviation divided by average) was 3% for men's and women's row, 8% for the women's thrusters, 9% for the men's thrusters, 14% for the men's pull-ups and 24% for the women's pull-ups.

With these values in hand, instead of calculating the leverage as I described earlier, I used the following method:

• Use the average pace for each movement to calculate a baseline score.
• For each movement, reduce the average pace by 2 standard deviations.
• For the other movements, increase their pace by a number of standard deviations such that we composite to a 0 standard deviations moved. If we have 3 movements, that means increasing the pace of the other two movements by 1 standard deviation each.
• Re-calculate the time for the workout. The percentage reduction in the overall score from our baseline is the "normalized leverage" for that movement.
• Repeat this for each movement.

Applying that to Jackie, we get the following:

What we see here are two very different stories: 

• For the men, the workout is balanced. Thrusters are most important, but the row is critical as well. The pull-ups aren't vitally important for these athletes because nearly all of them are going unbroken.
• For the women, the workout is won or lost on the pull-ups. The row doesn't separate the ladies that much, nor do the thrusters. However, athletes who were strong on the pull-ups could make up 20 seconds or more on that station alone.

To understand how some of the top athletes hit this workout, consider Jason Khalipa and Pat Barber:

• Khalipa set the current record (5:04) largely based on his blazing row time - his row pace of 314 meters/minute was 2.0 standard deviations above average, his thrusters were right at the average and his pull-ups were 0.8 standard deviations above average (remember, these "averages" are for the elite of the elite).
• Barber finished 15 seconds behind Khalipa (5:19), almost entirely due to the row. His row pace of 274 meters/minute was 2.1 standard deviations below average, and even after going 1.8 standard deviations above average on the thrusters and 1.6 standard deviations above average on the pull-ups, he still couldn't make up all of the ground he lost on the row.

In my view, this is an excellent way to understand the strategy for each workout, but there are limitations. The biggest problem is that data like this doesn't always exist without the benefit of video footage. The process of gathering it is also time-consuming and challenging (I'd love a bigger sample size, but it takes about 15 minutes to get the splits for a single heat). And obviously, this particular analysis really only applies to elite athletes - for someone shooting for a Jackie time closer to 8:00, the row is probably less of a factor since it's likely the pull-ups or thrusters that are sapping more of the time. The averages and the standard deviations need to be calculated using athletes of a similar caliber for them to make sense. 

Still, I hope this has provided some insight into what's behind some of the times we're seeing these athletes put up at regionals. Enjoy week three everyone!

*You may notice that for the women's pull-ups in particular, the bars with plus and minus 2 standard deviations are not evenly spaced around the original average. That's because I calculated everything based on the pace (i.e. reps per minute) rather than the time (i.e. minutes per rep). When I converted it back to the time (because it's easier to visualize), the symmetry disappears. For example, 25 miles per hour converts to 0.040 hours per mile, 20 miles per hour converts to .050 hours per mile and 15 miles per hour converts to 0.067 hours per mile. The miles per hour are symmetrical, but not the hours per mile. 

Quick Hits: Regional Week 1 Recap and Week 2 Predictions

Welcome back, all. It's been a long week for me with my Final Assessment last weekend - I haven't really haven't had a day off work since the prior Monday. I've been able to keep up with Regionals and update my predictions a bit, but not as much as I'd hoped. This upcoming week should be better for sure.

But either way, I wanted to throw out some initial reaction and analysis based on week 1 of the competition, and afterwards I'll put up my predictions for top 5 in each region (men and women this week). On with it:

• Streaming video coverage of the Regionals has been great so far. While the production value still leaves a lot to be desired, the fact is we can now watch far more live regional action than ever before. For me, this meant I was able to take some crucial 10-15 minute breaks from working on my F.A. to watch Josh Bridges basically wipe the floor with everyone. Speaking of which...
• Josh Bridges basically wiped the floor with everyone. Wow. I had a sense he would do well, perhaps even win his region, but he looked like a legitimate contender for the title. By my count, Bridges was top 3 in the world on five of seven events. And quite frankly, Rich Froning hasn't been pushed in either of the past two Games, so let's hope Bridges can make things interesting this year.
• Sam Briggs also looks like the woman to beat this year. By my count, she was top 3 in the world on four of seven events. If Annie does not compete, I think Briggs has to be the favorite right now based on her 2011 performance (4th at the Games), her dominance of the Open and then what we saw last weekend. There aren't a lot of holes in her game.
• That being said, let's not get caught up in all the "world records" we've seen thus far. These top times in almost every event are going to fall, and with the Central East men's region going in week 4, I wouldn't be surprised if they own 4 or 5 of the 7 records when the dust settles. And as I showed last year in my very first post, the later regions do tend to have an advantage in most events.
• Please, can we go a week without a judging fiasco? Without being at the SoCal region in person, it's hard to comment, but we had two issues that clearly stunk:
• Ryan Fischer's temper tantrum and subsequent tongue-lashing by Dave Castro. No one really came off looking good here. The videos I saw of Fischer's no-reps did look pretty questionable, but these judges are volunteers, and as a community, we can't afford to have athletes intimidating them like that if we want to have any judges left. These events simply don't happen without volunteers. That being said, it still came off a little distasteful for HQ to make an example out of Fischer, but it's probably a good idea to get out in front of this.
• Athletes being briefed incorrectly on the minimum standards for event 2. Not sure how this is possible - and I saw one commenter say Boz actually did brief them correctly - but either way, I can't believe there could be an issue knowing the rules for an event that has been released for a month.
• I wish HQ would just come up with a solid stance on the whole "former champions get a pass to the Games" issue. In prior years, they had said former champions received automatic invitations for life. Recently, they've been boasting that even the former champions have to earn their way. Now they go and invite Kristan Clever, who finished 15 points out of 3rd place last weekend. Smart money says they're going to invite Annie if she's ready. I'd have no problem if they just said that former champions get automatic invites, but when you leave things vague like this, it just comes off as if HQ is making up the rules as they go along. That's not what the sport needs going forward.

Before I move onto this week's predictions, let's take a look back and see how last week's predictions turned out. I ended up hitting 7 of 13 men's qualifiers (4 qualified from Europe), and of the 20 athletes I predicted to be in the top 5 of their region, I got 10 right. That sounds pretty good, but it's roughly the same as you would have done just basing your picks off the Open. However, I did look at how my model did predicting the entire regional field (I didn't post any picks outside the top 5, but I had them set up).

• Due to time constraints, I looked back at 3 men's regions: SoCal, North East and South East. 
• The R-squared for my picks (based on predicted rank vs. actual rank) was 49% in SoCal, 22% in the South East and 40% in the North East.
• The R-squared if you had picked solely based on Open performance was 39% in SoCal, 18% in the South East and 34% in the North East. So I did do a bit better as we look at the whole field.
• For athletes in those regions who finished in the top 0.5% of the Open worldwide, I looked at how past Games and Regional experience affected their shot at the Games. 
• Of 2012 Games competitors, 38% made the Games this year. 
• Of those completing all 6 events at the Regionals last year, 5% made the Games this year. 
• Of everyone else, 10% made the Games. 
• Interesting how the newcomers fared slightly better so far. Let's see if that holds up through 3 more weeks.

It's still early, so we'll have to wait until week 4 is in the books to really see how my model held up. I'm hoping to make some headway on an alternate model this week to give estimates of the chances of each athlete making the Games, but I haven't got there yet. Anyway, on to the picks.

Men

Africa

1. David Levey

2. Jaco Van der Vyver

3. Jason Smith

4. Neil Scholtz

5. Daniel Crous

Australia

1. Chad Mackay

2. Rob Forte

3. Brandon Swan

4. Kieran Hogan

5. Brendan Clarke

Canada East

1. Albert-Dominic Larouche

2. Matthew Lefave

3. Jeff Larsh

4. Jonathan Daniel

5. Jay Rhodes

Northern California

1. Jason Khalipa

2. Neal Maddox

3. Gabe Subry

4. Garret Fisher

5. Shaun Eagan

South Central

1. Jason Hoggan

2. Aja Barto

3. Bryan Diaz

4. Paul Smith

5. Drew Bignall

Top 10 Overall

1. Jason Khalipa

2. Neal Maddox

3. Albert-Dominic Larouche

4. Chad Mackay

5. Gabe Subry

6. Rob Forte

7. Brandon Swan

8. Jason Hoggan

9. Aja Barto

10. Bryan Diaz

Women

Africa

1. Mona Pretorius

2. Rika Diedericks

3. Carla Nunes da Costa

4. Nicole Seymour

5. Janine Prinsloo

Australia

1. Rush Anderson Horrell

2. Amanda Allen

3. Amy Dracup

4. Jessica Coughlan

5. Kara Webb

Canada East

1. Camille Leblanc-Bazinet

2. Michelle Lentendre

3. Lacey Van Der Marel

4. Jennifer Lymburner

5. Isabelle Tardif

Northern California

1. Annie Sakamoto

2. Sarah Hopping

3. Miranda Oldroyd

4. Chyna Cho

5. Katie Hogan

South Central

1. Jenn Jones

2. Candice Ruiz

3. Amanda Schwartz

4. Holly Mata

5. Jenna Gracey

Top 10 Overall

1. Camille Leblanc-Bazinet

2. Michelle Letendre

3. Jenn Jones

4. Ruth Anderson Horrell

5. Annie Sakamoto

6. Candice Ruiz

7. Amanda Allen

8. Sarah Hopping

9. Amanda Schwartz

10. Miranda Oldroyd

Enjoy the weekend!

Testing, testing... 2013 Regional Predictions

The first weekend of Regionals is finally here! Unfortunately, this is also the same weekend I'll be taking my Final Assessment (which of course isn't actually the final hurdle to clear to finish my actuarial testing), so I'll have little to no time to follow the action live. I may not even be able to tune in for the live broadcasts on Sunday afternoon (the humanity!). Anyway, point being, it's a busy time right now.

At the same time, I did want to give predicting the Regionals a shot this year. For this first week, I had to compromise a bit: I've got a set of predictions for the four men's competitions this weekend, but I didn't have time to get through the women. On top of that, I knew the methodology I'd really like to use would be too time-consuming for this first week, so I opted for something a bit simpler. Consider this a sort of beta test for making Regional predictions.

Making these predictions posed quite a different challenge from the Games predictions for a few reasons: 1) we only have one set of results so far this season; 2) there are about 15-20 times more athletes; 3) there are multiple regions, meaning an athlete's success is dictated (to some extent) by the strength of his/her region. With that in mind, here is the basic methodology I employed to make these predictions:

I felt that using only the 2013 Open results to predict the 2013 Regionals was insufficient, so I decided to go back and grab the 2012 Games results and the 2012 Regional results. I wanted to develop 3 sets of models: for athletes who qualified for the Games last year, I would use all three competitions to inform these predictions; for athletes who missed the Games last year but competed in Regionals individually, I would use the 2013 Open and 2012 Regionals to inform these predictions; for the rest of the athletes, I would use only the 2013 Open.

To build these models, I had to go back in time a year and look at how the 2011 Regionals, 2011 Games and 2012 Open related to 2012 Regional results. Gathering all this information was time-intensive, and also forced a couple limitations upon me. First, I only had 2011 Regional information available for athletes that reached the final event (i.e., the top 12 in each region). This meant I had to be consistent in making my 2013 predictions and only use Regional results in my predictions for athletes who reached the finals in 2012. Also, because I often had funky Open result coming through for athletes with common names (Ben Smith, for example), I wound up limiting my work from last year to athletes finishing in the top 7.5% of the Open. This gave me confidence that the scores I did use were correct.

Anyway, let's go ahead and give the top 5 for each region this year (men only - sorry, not sexist, just short on time):

South East
1) Chase Daniels
2) Brandon Phillips
3) Guido Trinidad
4) Elijah Muhammad
5) Irving Hernandez

North East
1) Daniel Tyminski
2) Austin Malleolo
3) Spencer Hendel
4) Mike McKenna
5) Dan Goldberg

Europe
1) Frederik Aegidius
2) Mikko Aronpaa
3) Mikko Salo*
4) Lacee Kovacs
5) Jakob Magnusson

Southern California
1) Kenneth Leverich
2) Jeremy Kinnick
3) Josh Bridges*
4) Ryan Fischer
5) Bill Grundler

Top 10 Overall Performers of the Weekend
1) Kenneth Leverich
2) Daniel Tyminski
3) Austin Malleolo
4) Spencer Hendel
5) Chase Daniels
6) Frederik Aegidius
7) Jeremy Kinnick
8) Brandon Phillips
9) Mikko Aronpaa
10) Mikko Salo

In developing these models, what I found were two key things: 1) athletes who reached the Games last year have a much better chance of reaching the Games this year than other athletes, even given a similar Open result; 2) similarly, athletes who competed at a high level at Regionals last year have a much better chance of reaching the Games this year than other athletes, even given a similar Open result. In 2012, 81% of athletes who made the 2011 Games and were in the top 0.5% in the world in the 2012 Open ended up finishing in the top 50 worldwide at Regionals. Of those who reached the finals at 2011 Regionals but did not make the Games (still top 0.5% in the 2012 Open), that percentage drops to 33%. For those who didn't make the finals at the 2011 Regionals (still top 0.5% in the 2012 Open), the figure drops to 14%.

Sure, last year we had guys like Scott Panchik and Marcus Hendren who made a splash in their first Regionals, but for every one of them, there were generally about 6 other guys with similar Open performances who didn't do anything special at Regionals. Meanwhile, you had veterans like Patrick Burke who put up sub-par Open performances and still excelled at Regionals. To be sure, there will be some new faces who do amazing things at Regionals this year, but it's just hard to predict exactly who those will be.

These are interesting facts, but they make for somewhat boring predictions (i.e. huge advantage to prior Games athletes). This is why I'd like to work on some different techniques for next week (or maybe the 3rd or 4th week - no promises). Ideally I'd like to make some sort of stochastic model that gives a probability of reaching regionals for each athlete, not simply a best estimate of how each athlete will do.

So again, consider these a beta test, and don't take them too seriously. Enjoy the weekend, and I'll see you again soon!

Before I go, I'd also like to give a shout-out to Michael Girdley (see his blog at girdley.com for some 2013 Open analysis and more). Through some programming wizardry, Michael has been able to pull down all the detail from the 2013 Open (including age, height, weight, current maxes, etc.), which will allow for some more in-depth analysis of the Open (some of which he's already done on his site). I'm looking forward to digging more into that in the coming weeks and months.

*For Josh Bridges and Mikko Salo, I manually entered them with a Regional and Games result of 47th for last year (i.e. last place at the Games). They were special cases of athletes who have done exceptionally well in the past but missed last year due to injury. This was my compromise on them.

Quick Hits: All Regional WODs Announced

We're back for the third post in three days. Today HQ finalized the lineup of Regional WODs for the individuals and announced all of the team WODs. I'm not going to be covering the team WODs at all, since that's never really been an emphasis of this blog (maybe someday), but let's go ahead and break down the individual lineup now that it's complete.

Here's a recap of some of the key metrics I typically track:

• Currently, I have calculated the average relative weight at 1.49 and 1.01 for women. This is above the past two years for each. I should note that these numbers lack a little bit of precision at the moment for two reasons: 1) the average load that will be attained on the OHS 3 RM is not known yet; and 2) I had to make a new assumption about the base weight for the weighted front rack lunge (I used 75-lbs. as a 1.00 on this one, equivalent to a 135-lb. clean). I'm reserving the right to adjust this after watching the competition and gauging just how difficult those lunges appear (or just trying it myself, I suppose). Regardless, the key takeaway here is that the average loading is at or above what we've seen in prior regionals.
• If we limit that to metcons only, the numbers drop to 1.13 for men and .75 for women. These are right in line with prior years.
• Despite the average-to-above-average loading, the load-based emphasis on lifting (LBEL) is just .64 for men and .43 for women, which is below both of the past two years. Why? Simple: lifts account for only 43% of the points this year, compared to 48% in 2011 and 67% in 2012. As I mentioned yesterday, that's a bit deceiving because rowing is not counted as lift, but yet it tends to favor larger athletes. I still believe this year's programming favors smaller athletes more so than last year and probably about the same as 2011 (do I smell Spealler for a 7th straight, perhaps?).

To illustrate these a bit better, here's a chart showing the average loading and LBEL for the past three regionals. Note the spike in LBEL last year.

I think we'll have to wait and see how things actually play out to truly judge this year's programming as "good" or "bad," but on paper, I think it looks pretty decent. I think HQ restored some balance after going probably a little bit overboard with the lifting last year, and they hit a wide range of movements (20 by my count, about the same as prior years). When lifting is used this year, it's at or above the level of prior years, but that's offset by a heavy dose of bodyweight movements, which has been more typical of programming at the Games in the past.

My one concern is the lack of running. We do have some sprints (in the final event only), but in total, there are less than 300 meters worth of running this year. I'm going to assume that's a logistical issue, but I think as we move forward, HQ should not continue to ignore any sort of distance running for the first two rounds of competition and then test it in a big way at the Games. My feeling is that you want the athletes who will perform best at the Games to qualify for the games. Having a bunch of bad runners qualify for the Games and then having them run a 15K just doesn't make sense to me. Let's hope this is something that can get worked out with better venues in the future.

Well that's it for me for now. I'll be back in the next couple weeks to make some sort of predictions about Regionals, although I can't commit to how specific they'll be. I haven't taken a stab at predicting Regionals before, and I fully expect it will not be easy.

See you all again soon.