How Science Predicts Which Olympic Events Will Be the Most Exciting to Watch

You can't watch everything, so let an analysis of physics data guide you to this summer's most competitive events

The Olympics represent something very special in the culture of sport, but from a viewing perspective they are a logistical nightmare. Multiple events play out at the same time, forcing you to pick and choose between your favorite events. Where will the next dazzling, record-breaking performance take place? Will someone rob Usain Bolt of his 100-meter record? Will there be a Kerri Strug moment in the gym? There’s no way to to tune into the Games with absolute certainty that you’ll see something historic, but Steve Haake thinks you can increase your chances. Science can tell us where we’re most likely to see the closest competitions or record-breaking performances, and where we’re least likely to see anything exciting at all.

Haake has made a career out of applying scientific principles to the often hard-to-quantify medium of sports performance. As the director of the Center for Sports Engineering Research at Sheffield Hallam University in the UK, Haake studies everything from the physics of tennis to the role technology has played in the history of sport. Haake recently penned a story for Physics World on this exact topic–the effect of rule change and technology on sporting performance over time. In it he describes why sporting performance has continued to improve through the years (better coaching and nutrition, population increases) as well as why we see step-changes in the data–peaks and valleys that are generally the result of some kind of external factor beyond athletic performance, like a new technology, a change in the rules, or even simply the weather. But this kind of analysis can also serve a more urgent purpose–to make sure we don’t miss any water-cooler-worthy moments in London over the next two weeks.

To do this, we first need a way to objectively look at where and how athletic performances are improving across various sports, and luckily Haake has provided that for us. In order to create an apples to apples means of comparison across sports that evaluate performance via many different metrics, Haake and grad student Leon Foster first extracted the 25 best results from the 25 best athletes across a range of sports and events (that is, each athlete was only counted once for his/her top performance so there are 25 different athletes in each data set). Reaching back to 1891, they created a picture of average top-level sports performance over time.

But they still needed a general way to quantify performance increases across sports. For this, they created the performance improvement index (PII), a means of determining the amount of useful work (“work” in the physics sense, which is basically the product of a force and its direction exerted on an object) going into a performance. This is calculated slightly differently for different events (for instance, in the javelin throw the body is exerting force on an object, while in track or swimming the body is battling against the ubiquitous force of drag), but it’s all to the same end–to determine in a very physics-based way how much useful work is done in a given performance.

Using these useful work values, Haake can look at two different years and see what kinds of increases (or decreases) in performance have occurred among the top 25 performances between any two given years. PII expresses this increase or decrease as a percentage, and those percentages can be compared across events and sports to reveal where athletes are improving and where performance has plateaued. For events like gymnastics that are scored subjectively by judge’s ruling, or that are decided by head-to-head matchup like wrestling, PII isn’t necessarily ideal. But for sports measured by time or some measure of distance or height–by physics–it offers us at least one scientific way to compare the rate of athletic improvement between very different events. You can’t compare the flat work figure between swimming and discus, but you can compare the percentage change over time.

“We can compare like with like across sports, whether its swimming or javelin,” Haake says. “Using PII, things are more intuitive, they make more sense. So now we are looking at anecdotes that exist in literature or in popular myth and seeing if there’s data to back the popular myth.”

For a good modern example of data validating a popular idea, look no further than the 2008 Olympic Games and the controversial LZR Racer swimsuits that were so popular among Olympic swimmers that year. These suits–more like full-body leotards–were very tight, pulling the body into a more cylindrical shape to reduce drag. They reduced skin friction and also trapped air, giving the body more buoyancy and making it ride higher in the water. Records fell all over the place in 2008 in Beijing. Later in 2008, at a competition in Croatia, 17 more records were broken. Many argued that the performance increase in 2008-2009 was purely technological. The suits imparted such an edge that in January 2010, they were banned from competition by swimming’s governing body.

You can see these technological and regulatory impacts in the data, Haake says. PII in the women’s 100-meter freestyle, for instance, spiked in the second half of the 2000s, but since 2010 has plunged back to 2004 levels. The point here is that the data can tell you that performances improved and then declined during that period, but you have to look outside the data for the actual anecdotal cause. In the case of LZR suits, the popular idea that they were giving swimmer’s a huge advantage is supported.

How do you use this kind of model to plan your Olympic viewing regimen? Those with a reasonable knowledge of Olympic sports can scan the data and do their own quick analyses based on what they already know. You want to look for events where performance is on a steady uptick and where external influences aren’t influencing the outcome (or, as in the case of the 2008 Games, where external influences are going to make things really exciting). For an example, just look at the two banner sports of sprinting and swimming.

Anecdotally, nothing has changed in the 100 meter since 2008–no major rule changes, no shifts in the timing technology or major developments in shoes or other sprinters’ accoutrement. In fact, according to Haake’s PII data in the men’s 100 meter, Usain Bolt’s otherworldly performance in 2008 seems to be dragging the entire field forward. Even if you remove Bolt’s time from the top 25 performances in 2008, the change in PII is almost the same among the other 24 athletes. Bolt’s record is far from secure.

“You’ve got 25 people there that are all performing exceptionally well, and you’ve got your top eight that are just fantastic,” Haake says. “Any one of them on the day could win it, and a few of them could set records.”

In fact, both men’s and women’s short sprinting events look good from a PII standpoint. Races are going to be close, records could be toppled, and the gold is generally up for grabs. But this is less and less true the longer the distances grow, Haake says. In the 400 meter race we might see some competition, but in the 800 and 1500 definitely not. Haake has heard some theories explaining this (one popular idea is that humans are–evolutionarily speaking–natural distance runners but unnatural sprinters, so there’s more room for improvement there) but he doesn’t offer his own scientific reason. He just lets the data speak for itself: at short distances humans are still getting faster, and there appears to be nothing external getting in the way. The shorter foot races are the ones to watch.

Short-distance swimming events, on the other hand, could be in for a disappointing year. To understand why, take a look at the javelin. Back in the 1980s, the rules in the javelin event were changed. For reasons of both safety and scoring, the center of gravity in a regulation javelin was moved slightly forward to force it to nose downward in flight–enough to shave nearly ten meters off the average throw and push the world record of 104.8 meters out of reach. (Note: the javelin throw is still not an event to watch in 2012).

Swimming is dealing with the same step-change downward in PII. The banning of the LZR suit in 2010 has ensured that another string of broken records is not in the cards in London this summer.

“It’s going to take a long time for those sprint events to catch up with the world records of 2008-2009,” Haake says. “I’d be surprised if we saw any records broken in the men’s or women’s sprint swimming events.”

But swim fans take heart; in the endurance swimming events like the 1500 meter freestyle the high-tech swimsuits didn’t have the same impact as they did in the short races. In fact, because they were so tight and stiff, Haake theorizes, they may have actually impeded performance to some degree. If you’re looking for record-breaking performances in the water, go for distance.

For further reading (and a more mathematical explanation) on how to scientifically evaluate the Summer Games, check out Haake’s piece in Physics World (you’ll need a subscription).