In big soaring competitions, at times there will be massive hordes of gliders in close proximity to one another. We refer to a swarm of gliders as a gaggle. Prior to starting in Australia, it was not uncommon to see upwards of 30 gliders all in one spot. Many in the United States abhor gaggles and the flying associated with them. They often inspire images of a swarm of gliders following the local champion, blinding being led on and stumbling in each others way. The rules and tasking has been set to avoid this gaggling behavior and it is fundamentally looked upon as a disease.
In FAI rules and World Championships however, gaggles are the basis of the tactics and strategy of competition flying. Whether you like them or not, flying under FAI rules requires understanding and taking advantage of them whenever possible. They also form frequently enough in the United States that using them effectively could be a winning strategy.
This suggests that it is critical to understand this group behavior of gliders. Most people see gaggles as a herd, but there are times this reasoning is quite flawed. When conditions are good and pilots are risk-seeking, individuals within gaggles will be motivated to find small inefficiencies and attempt to take advantage of them. Pilots are certainly operating in a group environment, but if they see an opportunity to find better air, they will jump at the opportunity to take advantage of it. As a result, within a gaggle, there are quite a few pilots that are making independent judgments about the air ahead, specifically the tactical decisions of which line to take and which cloud may be the best. Quite often, pilots will make a similar judgment and then the whole horde will fly to a particular place. In this case, it will be very difficult, if not impossible to beat the gaggle’s judgment.
Group forecasts are categorically much more accurate than individual ones, particularly over the long run. This is known as the “Wisdom of the Crowd”. The idea is that groups of individuals looking at a particular problem will observe certain bits and pieces of information that perhaps others do not see. When the participants make their own judgments independent of others and the results are put together, the group forecast performs a lot better.
Philip Tetlock explained this principle with an example of, “A fair where about 800 people had tried to guess the weight of a dead ox in a competition. After the prize was awarded, Galton collected all the guesses so he could figure out how far off the mark the average guess was. It turned out that most of the guesses were really bad — way too high or way too low. But when Galton averaged them together, he was shocked: The dead ox weighed 1,198 pounds. The crowd’s average: 1,197.”
An example of this methodology in action is a prediction website for political elections, Fivethirtyeight.com. They aggregate many state and national polls and in doing so, they build a much better composite picture of the probability of a given candidate winning. Another example is the use of prediction markets such as the Iowa Electronic Market. In this case, contracts and share are made out that will pay up if certain future events occur. An example would be suppose a certain candidate wins the election. Over the course of an election cycle, as new information comes out, the overall people’s views about who is likely to win the election change to incorporate the news. As a result, the price of the shares changes. Both of these methods have been remarkably effective in predicting the outcomes of many events, by using the benefit of aggregating forecasts.
As a result, if a gaggle has enough pilots who are independently making judgments about the air and especially if enough people come to the same conclusion, the whole gaggle benefits quite a bit from this aggregated forecast of what is the best tactical decision at that time. The gaggle will likely be fast moving and consist of a fast-moving pack at its helm. Deviating from the group consensus is likely to be both highly aggressive and also unlikely to succeed.
However, when many individual pilots become risk-averse, then the group dynamic rapidly shifts to a herd mentality and develops major inefficiencies. In a risk-averse scenario, individuals are scared of the possibility of landing out and seek others to make decisions for them. However, since everyone in the group is thinking along the same lines, the gaggle becomes a herd, with no sheep dog to guide it. When this occurs, gliders will not want to lead out of a thermal, even at the top of the lift. Pilots will fly slow in between thermals to make sure that they have as many other gliders around them as possible. They will take turns in weak lift and suck along many others to try the same. These are the gaggles that pilots abhor. The ones that require the patience of a pilot to stick with, but yet is inefficient and stumbling along.
My limited experience in the worlds indicates to me that the game is about predicting and taking advantage of these aspects of group behavior. Simply stated, the game is about playing the gaggle as best as possible. Let’s consider some possible scenarios where the gaggle will be risk seeking or risk averse.
The behavior a gaggle before start is a great example of risk-averse behavior of the group. Individuals are steeply penalized for starting before a critical mass of the group goes. However, no one wants to be the one to lead out, because this entails taking a near sure loss in points. As a result, everyone waits and waits, until enough people are emotionally wound up enough to finally accept their losses and get going. My hunch is that this occurs when a particular team or group of pilots makes a feint at the start, leads out a couple minnows and then the minnows are too afraid to spend anymore time to climb up from the bottom a pre-start thermal and be 10-15 minutes behind the main group.
While there is little incentive for risk-seeking behavior prior to start, but the fact that the very nature of the start is for individuals trying to play the group sets the dynamic up in a quite important way. Since the group is risk-averse, it allows for a possibility for individual pilots to possibly take advantage of large inefficiencies that develops by delaying their start just a little and cashing in on their gains early in the contest day.
Over the course of a contest day, bottlenecks can develop when the group becomes risk averse. This is likely to happen in conditions that have high likelihood of landing out. This is more likely to develop early and late in the day, but can also occur if the group is heading into another airmass. When this shift occurs, individual pilots will be hesitant to leave the top of a thermal and the whole gaggle is stifled. If a pilot can recognize that this is likely to occur at some point, this is another possibility to run down the major group. This is best done either before start or by extending a bit farther in a turn area and hoping to catch up to the main group. This is an aggressive strategy; there’s a reason why the groups shifts to risk aversion and it is not necessarily irrational. However, this shift also exposes inefficiencies and if the competitor is willing to take a little bit more risk and succeeds, this is a major opportunity to do so. Using team-flying effectively under these circumstances to minimize the risk for the individual competitor could be a great tactical tool to taking advantage of these opportunities
Moderate- Strong Conditions
When the immediate tactical situation is assured and there are good thermal opportunities ahead, individual competitors will shift to risk-seeking behavior. If there are many clouds ahead and landing out is unlikely, the gaggle will become a highly effective forecasting tool. For most contest days, this is the majority of the “meat” of the day. In this case, the gaggle will become quite fast moving and very efficient. Under these conditions, the best strategy is to look for small inefficiencies, such as extending a little bit into a turn area, or pouncing on the final glide. The gaggle is unlikely to generate such major inefficiencies that allow for major gains and to deviate substantially from the group judgment is both highly aggressive and unlikely to work.
To sum up if you believe that pilots will be risk-seeking in the gaggle, it is best to benefit from the wisdom of the crowd and plan to loosely stick with. Plan on taking advantage of small inefficiencies by trying to enter thermals more efficiently, achieving a slightly better average and exiting better. The goal is to position oneself at the top of the gaggle, waiting for the right opportunity to make the break-away. In the case of turn area tasks, there are also opportunities to go a bit farther into the turnpoints and cash in on some extra distance and hopefully run down the gaggle over the next leg. If the gaggle is risk-averse, then there are possibilities for major gains, albeit at substantial risk. If the pilot can recognize that the gaggle is becoming risk-averse, then it will likely fly very inefficiently as the pilots become an emotional herd and if at this time the pilot chooses to start later or go substantially deeper into a turnpoint, he can cash in on a major bonus in speed.