Rotate It Like Ronaldo?

"Rotate it like Ronaldo" just doesn't have the same ring to it as "Bend it like Beckham", but the curving free kick is still one of the most exciting plays in soccer/football. Starting with Rivelino in the 1970 World Cup and on to the specialists of today, more players know how to do it and understand the basic physics behind it, but very few can perfect it. But, when it does happen, by chance or skill, it is the highlight of the game.



But let's take a look at this from the other side, through the eyes of the goalkeeper. Obviously, its their job to anticipate where the free kick is going and get to the spot before the ball crosses the line. He sets up his wall to, hopefully, narrow the width of the target, but he knows some players are capable of bending the ball around or over the wall towards the near post. If you watch highlights of free kick goals, you often see keepers flat-footed, just watching the ball go into the top corner. Did they guess wrong and then were not able to react? Did they guess right but misjudged the flight trajectory of the ball. How much did the sidespin or "bend" affect their perception of the exact spot where the ball will cross the line? To get an idea of the effect of spin, here's a compilation of Beckham's best free kick goals (there's a 15 second intro, then the highlights) :







Researchers at Queen's University Belfast and the University of the Mediterranean in France tried to figure this out in this paper. They wanted to compare the abilities of expert field players and expert goalkeepers to accurately predict if a free kick would result in an on-target goal or off-target non-goal. First, a bit about why the ball "bends". We can thank what's called the "Magnus Force" named after the 19th-century German physicist Gustav Magnus. As seen in the diagram below, as the ball spins counter clockwise (for a right-footed player using his instep and kicking the ball on the right side), the air pressure on the left side of the ball is lower as the spin is in the same direction as the oncoming air flow. On the right side of the ball, the spin is in the opposite direction of the air flow, building higher pressure. The ball will follow the path of least resistance, or pressure, and "bend" or curve from right to left. The speed of the spin and the velocity of the shot will determine the amount of bend. For a clockwise spin, the ball bends from left to right.







The researchers showed the players three different types of simulated kicks, a kick bent to the right, a kick bent to the left and a kick with no spin at all. They showed the players these simulations with virtual reality headsets and computer controlled "kicks" and "balls" which they could vary in flight with different programming. The balls would disappear from view at distances of 10 and 12.5 meters from the goal. The reasoning is that this cutoff would correspond with the deadline for reaction time to make a save on the ball. In other words, if the keeper does not correctly guess the final trajectory and position of the ball by this point, he most likely will not be able to physically get to the ball and make the save.







The results showed that both the players and the keepers, (all 20 were expert players from elite clubs like AC Milan, Marseille, Bayer Leverkusen, Schalke 04), were able to correctly predict the result of the kicks with no spin added. However, as 600 RPM spin, either clockwise or counter-clockwise, was added to the ball, the players success declined significantly. Interestingly, the keepers did no better, statistically, then the field players. The researchers conclusion was that the players used the "current heading direction" of the ball to predict the final result, rather than factoring the future affect of the acceleration and change in trajectory caused by the spin.



Just as we saw in the Baseball Hitting post, our human perception skill in tracking flying objects, especially those that are spinning and changing direction, are not perfect. If we understand the physics of the spinning ball, we can better guess at its path, but the pitcher or the free kick taker doesn't usually offer this information beforehand!



Craig, C.M., Berton, E., Rao, G., Fernandez, L., Bootsma, R.J. (2006). Judging where a ball will go: the case of curved free kicks in football. Naturwissenschaften, 93(2), 97-101. DOI: 10.1007/s00114-005-0071-0

Baseball Brains - Hitting Into The World Series

Ted Williams, arguably the greatest baseball hitter of all-time, once said, "I think without question the hardest single thing to do in sport is to hit a baseball". Williams was the last major league player to hit .400 for an entire season and that was back in 1941, 67 years ago! In the 2008 Major League Baseball season that just ended, the league batting average for all players was .264, while the strikeout percentage was just under 20%. So, in ten average at-bats, a professional ballplayer, paid millions of dollars per year, gets a hit less than 3 times but fails to even put the ball in play 2 times. So, why is hitting a baseball so difficult? What visual, cognitive and motor skills do we need to make contact with an object moving at 70-100 mph?

In the second of three posts in the Baseball Brains series, we'll take a quick look at some of the theory behind this complicated skill. Once again, we turn to Professor Mike Stadler and his book "The Psychology of Baseball" for the answers.  First, here's the "Splendid Splinter" in action:

A key concept of pitching and hitting in baseball was summed up long ago by Hall of Fame pitcher Warren Spahn, when he said, “Hitting is timing. Pitching is upsetting timing.” To sync up the swing of the bat with the exact time and location of the ball's arrival is the challenge that each hitter faces. If the intersection is off by even tenths of a second, the ball will be missed. Just as pitchers need to manage their targeting, the hitter must master the same two dimensions, horizontal and vertical. The aim of the pitch will affect the horizontal dimension while the speed of the pitch will affect the vertical dimension. The hitter's job is to time the arrival of the pitch based on the estimated speed of the ball while determining where, horizontally, it will cross the plate. The shape of the bat helps the batter in the horizontal space as its length compensates for more error, right to left. However, the narrow 3-4" barrel does not cover alot of vertical ground, forcing the hitter to be more accurate judging the vertical height of a pitch than the horizontal location. So, if a pitcher can vary the speed of his pitches, the hitter will have a harder time judging the vertical distance that the ball will drop as it arrives, and swing either over the top or under the ball.

A common coach's tip to hitters is to "keep your eye on the ball" or "watch the ball hit the bat". As Stadler points out, doing both of these things is nearly impossible due to the concept known as "angular velocity". Imagine you are standing on the side of freeway with cars coming towards you. Off in the distance, you are able to watch the cars approaching your position with relative ease, as they seem to be moving at a slower speed. As the cars come closer and pass about a 45 degree angle and then zoom past your position, they seem to "speed up" and you have to turn your eyes/head quickly to watch them. While the car is going at a constant speed, its angular velocity increases making it difficult to track.

This same concept applies to the hitter. As the graphic above shows (click to enlarge), the first few feet that a baseball travels when it leaves a pitcher's hand is the most important to the hitter, as the ball can be tracked by the hitter's eyes. As the ball approaches past a 45 degree angle, it is more difficult to "keep your eye on the ball" as your eyes need to shift through many more degrees of movement. Research reported by Stadler shows that hitters cannot watch the entire flight of the ball, so they employ two tactics.

First, they might follow the path of the ball for 70-80% of its flight, but then their eyes can't keep up and they estimate or extrapolate the remaining path and make a guess as to where they need to swing to have the bat meet the ball. In this case, they don't actually "see" the bat hit the ball. Second, they might follow the initial flight of the ball, estimate its path, then shift their eyes to the anticipated point where the ball crosses the plate to, hopefully, see their bat hit the ball. This inability to see the entire flight of the ball to contact point is what gives the pitcher the opportunity to fool the batter with the speed of the pitch. If a hitter is thinking "fast ball", their brain will be biased towards completing the estimated path across the plate at a higher elevation and they will aim their swing there. If the pitcher actually throws a curve or change-up, the speed will be slower and the path of the ball will result in a lower elevation when it crosses the plate, thus fooling the hitter.

To demonstrate the effect of reaction time for the batter, FSN Sport Science compared hitting a 95 mph baseball at 60' 6" versus a 70 mph softball pitched from 43' away.  The reaction time for the hitter went from .395 seconds to .350 seconds, making it actually harder to hit.  That's not all that makes it difficult.  Take a look:

As in pitching, the eyes and brain determine much of the success for hitters. The same concepts apply to hitting any moving object in sports; tennis, hockey, soccer, etc. Over time, repeated practice may be the only way to achieve the type of reaction speed that is necessary, but even for athletes who have spent their whole lives swinging a bat, there seems to be human limitation to success. Tracking a moving object through space also applies to catching a ball, which we'll look at next time.

Brains Over Brawn In Sports

Sometimes, during my daily browsing of the Web for news and interesting angles on the sport science world, I get lucky and hit a home run.  I stumbled on this great May 2007 Wired article by Jennifer Kahn, Wayne Gretzky-Style 'Field Sense' May Be Teachable.  It ties together the people and themes of my last three posts, focusing on the concept of perception in sports.


Wayne Gretzky is often held up as the ultimate example of an athlete with average physical stature, who used his cognitive and perceptual skills to beat opponents.  Joining Gretzky in the "brains over brawn" Hall of Fame would be pitcher Greg Maddux, NBA guard Steve Nash and quarterback Joe Montana.  They were all told as teenagers that they didn't have the size to succeed in college or the pros, but they countered this by becoming master students of the game, constantly searching for visual cues that would give them the advantage of a fraction of second or the element of surprise.



Kahn's story focuses on two sport scientists that we have met before.  Peter Vint, sport technologist with the US Olympic team, who I highlighted in the post, Winning Olympic Gold With Sport Science,  comments on this, "In any sport, you come across these players.  They're not always the most physically talented, but they're by far the best. The way they see things that nobody else sees — it can seem almost supernatural. But I'm a scientist, so I want to know how the magic works."  So, Vint and his team continue to search not only for the secret to the magic, but how it can be taught.



Vint acknowledges the work of one of his fellow sport scientists, Damian Farrow, of the Australian Institute for Sport, who was part of the discussion roundtable mentioned in my post, Getting Sport Science Out Of The Lab And Onto The Field.


He is also fascinated with the perceptual abilities of elite athletes.  In his own sport, tennis, he wanted to know how expert players could return serves much better than novice players.  Similar to the research we looked at in an earlier post about tennis, Federer and Nadal Can See the Difference, Farrow designed an experiment that would try to identify the cues that players might need to instinctively estimate the speed and direction of a serve.  He had three groups of players, expert, non-expert but coached, and non-expert/non-coaced novices, wear ear plugs to block out the sound of the ball hitting the racquet as well as occlusion glasses that could block vision with the touch of an assistant's button.  

By changing the point of the serve at which the glasses would go black, and the players would be "blind", he could try to isolate the action of the server that the expert players might be tuned into that the novices were not.  The decisive point was immediately before impact between the racquet and the ball.  Arm and racquet position at that point seemed to let the expert players estimate the direction of the serve more accurately than the novices.


But Vint and Farrow are not satisfied just knowing what an expert knows.  They want to understand how to teach this skill to novices.  From his own competitive tennis playing days, Farrow remembers that if he consciously focused his mind on things like arm position, racquet angle, etc., he would be miss the serve as his reaction time would drop.  He understood that players need to not only learn the cues, but learn them to the point of "automaticity" through implicit learning.  

You may remember our discussion of implicit learning from the post, Teaching Tactics and Techniques in Sports.   Malcolm Gladwell, in his best-selling book, Blink, calls this implicit decision-making ability "thin slicing" and gives examples of how we can often make better decisions in the "blink" of an eye, rather than through long analysis.  Obviously, in sports, when only seconds or sub-seconds are allowed for decisions, this blink must be so well-trained that it is at the sub-conscious level.

For Vint and Farrow, the experiments continue, looking at each sport, but beyond the raw physical and technical skills that need to be taught but often times are the only skills that are taught.   

Understanding the cognitive side of the game will provide the edge when all else is equal.

Getting Sport Science Out Of The Lab And Onto The Field

You are a coach, trying to juggle practice plans, meetings, game prep and player issues while trying to stay focused on the season's goals.  At the end of another long day, you see this in your inbox:

MEMO
To:           All Head Coaches
From:      Athletic Director
Subject:  Monthly Reading List to Keep Up with Current Sport Science Research 
-  Neuromuscular Activation of Triceps Surae Using Muscle Functional MRI and EMG
-  Positive effects of intermittent hypoxia (live high:train low) on exercise performance are not mediated primarily by augmented red cell volume
-  Physiologic Left Ventricular Cavity Dilatation in Elite Athletes
-  The Relationships of Perceived Motivational Climate to Cohesion and Collective Efficacy in Elite Female Teams

Just some light reading before bedtime...  This is an obvious exaggeration (and weak attempt at humor) of the gap between sport science researchers and practitioners.  While those are actual research paper titles from the last few years under the heading of "sport science", the intended audience was most likely not coaches or athletes, but rather fellow academic peers.  The real question is whether the important conclusions and knowledge captured in all of this research is ever actually used to improve athletic performance?  How can a coach or athlete understand, combine and transfer this information into their game?

David Bishop of the Faculty of Exercise and Sport Science at the University of Verona has been looking at this issue for several years.  It started with a roundtable discussion he had at the 2006 Congress of the Australian Association for Exercise and Sports Science with several academic sport scientists (see: Sports-Science Roundtable: Does Sports-Science Research Influence Practice? )  He asked very direct questions regarding the definition of sport science and whether the research always needs to be "applied" versus establishing a "basic" foundation.  The most intriguing question was whether there already is ample research that could applied, but it suffered from the lack of a good translator to interpret and communicate to the potential users - coaches and athletes.  The panel agreed that was the missing piece, as most academic researchers just don't have the time to deliver all of their findings directly to the field.

In a follow-up to this discussion, Bishop recently published his proposed solution titled, "An Applied Research Model for the Sport Sciences" in Sports Medicine (see citation below).  In it, he calls for a new framework for researchers to follow when designing their studies so that there is always a focus on how the results will directly improve athletic performance.  He calls for a greater partnership role between researchers and coaches to map out a useful agenda of real world problems to examine.  He admits that this model, if implemented, will only help increase the potential for applied sport science.  The "middleman" role is still needed to bring this information to the front lines of sports.

The solution for this "gathering place" community seems perfect for Web 2.0 technology.  One specific example is an online community called iStadia.com.  Keith Irving and Rob Robson, two practicing sport science consultants, created the site two years ago to fill this gap.  Today, with over 600 members, iStadia is approaching the type of critical mass that will be necessary to bring all of the stakeholders together.  Of course, as with any online community, the conversations there are only as good as the participants want to make it.  But, with the pressure on coaches to improve and the desire of sport scientists to produce relevant knowledge, there is motivation to make the connection.

Another trend favoring more public awareness of sport science is the additional, recent media attention, especially related to the upcoming Beijing Olympics.  In an earlier post, Winning Olympic Gold With Sport Science, I highlighted a feature article from USA Today.  This month's Fast Company also picks up on this theme with their cover article, Innovation of Olympic Proportions, describing several high-tech equipment innovations that will be used at the Games.  Each article mentions the evolving trust and acceptance of sport science research by coaches and athletes.  When they see actual products, techniques and, most importantly, results come from the research, they cannot deny its value.







Bishop, D. (2008). An Applied Research Model for the

Sport Sciences. Sports Medicine, 38(3), 253-263.

Teaching Tactics and Techniques In Sports

You have probably seen both types of teams. Team A: players who are evenly spaced, calling out plays, staying in their positions only to watch them dribble the ball out of bounds, lose the pass, or shoot wildly at the goal. Team B: amazing ball control, skillful shooting and superior quickness, speed and agility but each player is a "do-it-yourselfer" since no one can remember a formation, strategy or position responsibility. Team A knows WHAT to do, but can't execute. Team B knows HOW to do it, but struggles with making good team play decisions. This is part of the ongoing balancing act of a coach. At the youth level, teaching technique first has been the tradition, followed by tactical training later and separately. More recently, there has been research on the efficiency of learning in sports and whether there is a third "mixed" option that yields better performance.


Earlier, we took an initial look at Dr. Joan Vickers' Decision Training model as an introduction to this discussion. In addition, Dr. Markus Raab of the Institute for Movement Sciences and Sport, University of Flensburg, Germany, (now of the Institute of Psychology, German Sport University in Cologne), took a look at four major models of teaching sports skills that agree that technical and tactical skills need to be combined for more effective long-term learning.Each of the four models vary in their treatment of learning along two different dimensions; implicit vs. explicit learning and domain-specific vs. domain-general environments. 


Types of Learning

Imagine two groups of boys playing baseball. The first group has gathered at the local ball diamond at the park with their bats, balls and gloves. No coaches, no parents, no umpires; just a group of friends playing an informal "pick-up" game of baseball. They may play by strict baseball rules, or they may improvise and make their own "home" rules, (no called strikes, no stealing, etc.). In the past, they may have had more formal coaching, but today is unstructured.


The second group is what we see much more often today. A team of players, wearing their practice uniforms are driven by their parents to team practice at a specific location and time to be handed off to the team coaches. The coaches have planned a 90 minute session that includes structured infield practice, then fly ball practice, then batting practice and finally some situational scrimmages. Rules are followed and coaching feedback is high. Both groups learn technical and tactical skills during their afternoon of baseball. They differ in the type of learning they experience.

The first group uses "implicit" learning while the second group uses "explicit" learning. Implicit learning is simply the lack of explicit teaching. It is "accidental" or "incidental" learning that soaks in during the course of our play. There is no coach teaching the first group, but they learn by their own trial and error and internalize the many if-then rules of technical and tactical skills. Explicit learning, on the other hand, is directed instruction from an expert who demonstrates proper technique or explains the tactic and the logic behind it.



An interesting test of whether a specific skill or piece of knowledge has been learned with implicit or explicit methods is to ask the athlete to describe or verbalize the details of the skill or sub-skill. If they cannot verbalize how they know what they know, it was most likely learned through implicit learning. However, if they can explain the team's attacking strategy for this game, for example, that most likely came from an explicit learning session with their coach.



Types of Domains

The other dimension that coaches could use in choosing the best teaching method is along the domain continuum. Some teaching methods work best to teach a skill that is specific to that sport's domain and the level of transferability to another sport is low. These methods are known as domain-specific. For more general skills that can be useful in several related sports, a method can be used known as domain-general.

Why would any coach choose a method that is not specific to their sport? There has been evidence that teaching at a more abstract level, using both implicit and explicit "play" can enhance future, more specific coaching. Also, remember our discussion about kids playing multiple sports.Based on these two dimensions, Dr. Raab looked at and summarized these four teaching models:

• Teaching Games for Understanding (TGFU)
• Decision Training (DT)
• Ball School (Ball)
• Situation Model of Anticipated Response consequences of Tactical training (SMART)

TGFU

The TGFU approach, (best described by Bunker, D.; Thorpe, R. (1982) A model for the teaching of games in the secondary school, Bulletin of Physical Education, 10, 9–16), is known for involving the athlete early in the "cognition" part of the game and combining it with the technical aspect of the game. Rather than learn "how-to" skills in a vacuum, TGFU argues that an athlete can tie the technical skill with the appropriate time and place to use it and in the context of a real game or a portion of the game.

This method falls into the explicit category of learning, as the purpose of the exercise is explained. However, the exercises themselves stress a more domain-general approach of more generic skills that can be transferred between related sports such as "invasion games" (soccer, football, rugby), "net games" (tennis, volleyball), "striking/fielding games" (baseball, cricket) and "target games" (golf, target shooting). 



Decision Training

The DT method, (best described by Vickers, J. N., Livingston, L. F., Umeris-Bohnert, S. & Holden, D. (1999) Decision training: the effects of complex instruction, variable practice and reduced delayed feedback on the acquisition and transfer of a motor skill, Journal of Sports Sciences, 17, 357–367), uses an explicit learning style but with a domain-specific approach. Please see my earlier post on Decision Training for details of the approach. 


Ball School

The Ball School approach, (best described by Kroger, C. & Roth, K. (1999) Ballschule: ein ABC fur Spielanfanger [Ball school: an ABC for game beginners] (Schorndorf, Hofmann), starts on the other end of both spectrums, in that it teaches generic domain-general skills using implicit learning. It emphasizes that training must be based on ability, playfullness, and skill-based. Matching the games to the group's abilities, while maintaining an unstructured "play" atmosphere will help teach generic skills like "hitting a target" or "avoiding defenders". 



SMART

Dr. Raab's own SMART model, (best described in Raab, M. (2003) Decision making in sports: implicit and explicit learning is affected by complexity of situation, International Journal of Sport and Exercise Psychology, 1, 406–433), blends implicit and explicit learning within a domain-specific environment. The idea is that different sports' environmental complexity may demand either an implicit or explicit learning method. Raab had previously shown that skills learned implicitly work best in sport enviroments with low complexity. Skills learned explicitly will work best in highly complex environments. Complexity is measured by the number of variables in the sport. So, a soccer field has many moving parts, each with its own variables. So, the bottom line is to use the learning strategy that fits the sport's inherent difficulty. So, learning how to choose from many different skill and tactical options would work best if matched with the right domain-specific environment.  



Bottom-Line for Coaches

What does all of this mean for the coach? That there are several different models of instruction and that one size does not fit all situations. Coaches need an arsenal of tools to use based on the specific goals of the training session. In reality, most sports demand both implicit and explicit learning, as well as skills that are specific to one domain, and some that can transfer across several sport domains. Flexibility in the approach taken goes back to the evidence based coaching example we gave last time. Keeping an open mind about coaching methods and options will produce better prepared athletes.






(2007). Discussion. Physical Education & Sport Pedagogy, 12(1), 1-22. DOI: 10.1080/17408980601060184

Winning Olympic Gold With Sport Science

Its something that every coach and every athlete of every sport is searching for... the EDGE. That one training tip, equipment improvement, mental preparation or tactical insight that will tip the game towards them. The body of knowledge that exists today in each sport is assumed, with each competitor expected to at least be aware of the history, beliefs and traditions of their individual sport. But, if each team is starting with the same set of information then the team that takes the next step by applying new research and ideas will capture the edge.

To me, that is what sport science is all about. The goal is to improve sports performance by imagining, analyzing, experimenting, testing, documenting and training new methods to coaches and athletes.

You might have seen a great article in the 6/23 edition of USA Today; "In hunt for Olympic gold, techies are major players" by Jodi Upton. We meet Peter Vint, a "sport technologist" in the Performance Technology Division of the US Olympic Training Center in Colorado Springs, CO, whose job it is to find ways to win more gold medals. From the article; "The next revolution, Vint says, is breaking down the last secrets of elite athletes: response time, how they read the field and other players — everything that goes into the vision, perception and split-second decision-making of an athlete. 'We've always looked at that as mysterious, something that's unmeasurable and innate,' Vint says. 'But we think it can be taught.'"

Interestingly, Vint cites another pioneer in evidence-based sports coaching, Oakland A's general manager, Billy Beane. "We're becoming progressively more data-driven," Vint says of the center's training efforts. "We are trying to pursue what Sabermetrics and Billy Beane did for baseball, identifying factors that can truly influence performance." The radical concept that Beane created, as documented in the bestseller, "Moneyball" by Michael Lewis, is to stop searching for "the edge" in all the same places that everyone else is looking. Instead, he started from scratch with new logic about the objectives of the game of baseball itself and built metrics that gave new insight into the types of players and skill sets that he should acquire for his team.

If sport science is going to thrive and be accepted, it faces the challenge of inertia. The ideas and techniques that are the product of sport science can also be captured in the phrase, "evidence based coaching". Just as evidence based medicine has slowly found its place in the physician's exam room, the coaching profession is just beginning to trust the research. Traditionally, "belief based coaching" has been the philosophy favored in the clubhouse. Training drills, tactical plans, player selection and player development has been guided by ideas and concepts that have been handed down from one generation of coaches to the next. Most of these beliefs are valid and have been proven on the field through many years of trial and error. Subjecting these beliefs to scientific research may not produce conclusions any different than what coaching lore tells us. But, today's coaches and athletes see the competition creeping closer to them in all aspects, so they are now willing to at least listen to the scientists. Beane likens it to financial analysis and the stock market. The assumption is that all information is known by all. But, if someone can find a ratio or a statistic or make an industry insight that no one has considered, then they own the competitive advantage; at least until this new information is made public.

It takes time, though, to amass enough data to convince a head coach to change years of habits for the unknown. Reputations and championships are on the line, so the changes sometimes need to be implemented slowly. Vint describes the gradual process of converting U.S. hurdler Terrence Trammell and his coach to some of his ideas. "The relationship between the athletes and sports scientist is critical," Vint says. "But (for some), biomechanics has not yet provided useful enough suggestions."

There still is debate on evidence based coaching vs. belief based coaching. Here are two opposing opinions; evidence-based: "The Second Law of Thermodynamics" by Brent S. Rushall of San Diego State University
and belief-based: "Evidence Based vs. Belief Based Coaching" by Richard Todd of Webball.com. If you have a few minutes, please read each opinion and offer your take on this. After considering these opinions, Robert Robson, sport psychologist and management consultant, stated, "Sports coaching should absolutely be evidence-based, but any argument that places the sole source of evidence in the realm of the scientific method is, I would argue, naive and lacking in an understanding of the philosophical underpinnings of science."

Looking forward, I will dig a little deeper into this topic in the next week, so please check back or subscribe to Sports Are 80 Percent Mental.

Single Sport Kids - When To Specialize

So, your grade school son or daughter is a good athlete, playing multiple sports and having fun at all of them. Then, you hear the usual warning, either from coaches or other parents; "If you want your daughter to go anywhere in this sport, then its time to let the other sports go and commit her full-time to this one." The logic sounds reasonable. The more time spent on one sport, the better she will be at that sport, right? Well, when we look at the three pillars of our Sports Cognition Framework, motor skill competence, decision making ability, and positive mental state, the question becomes whether any of these would benefit from playing multiple sports, at least in the early years of an athlete (ages 3-12)? It seems obvious that specific technical motor skills, (i.e. soccer free kicks, baseball bunting, basketball free throws) need plenty of practice and that learning the skill of shooting free throws will not directly make you a better bunter. On the other end, learning how to maintain confidence, increase your focus, and manage your emotions are skills that should easily transfer from one sport to another. That leaves the development of tactical decision making ability as the unknown variable. Will a young athlete learn more about field tactics, positional play and pattern recognition from playing only their chosen sport or from playing multiple related sports?

Researchers at the University of Queensland, Australia learned from previous studies that for national team caliber players there is a correlation between the breadth of sport experiences they had as a child and the level of expertise they now have in a single sport. In fact, these studies show that there is an inverse relation between the amount of multi-sport exposure time and the additional sport-specific training to reach expert status. In plain English, the athletes that played several different (but related) sports as a child, were able to reach national "expert" level status faster than those that focused only one sport in grade school . Bruce Abernethy, Joseph Baker and Jean Cote designed an experiment to observe and measure if there was indeed a transfer of pattern recognition ability between related sports (i.e. team sports based on putting an object in a goal; hockey, soccer, basketball, etc.)

They recruited two group of athletes; nationally recognized experts in each of three sports (netball, basketball and field hockey) who had broad sports experiences as children and experienced but not expert level players in the same sports whose grade school sports exposure was much more limited (single sport athletes). (For those unfamiliar with netball, it is basically basketball with no backboards and few different rules.) The experiment showed each group a video segment of an actual game in each of the sports. When the segment ended the groups were asked to map out the positions and directions of each of the players on the field, first offense and then defense, as best they could remember from the video clip. The non-expert players were the control group, while the expert players were the experimental groups. First, all players were shown a netball clip and asked to respond. Second, all were shown a basketball clip and finally the hockey clip. The expectation of the researchers was that the netball players would score the highest after watching the netball clip (no surprise there), but also that the expert players of the other two sports would score higher than the non-expert players. The reasoning behind their theory was that since the expert players were exposed to many different sports as a child, there might be a significant transfer effect between sports in pattern recognition, and that this extra ability would serve them well in their chosen sport.

The results were as predicted. For each sport's test, the experts in that sport scored the highest, followed by the experts in the other sports, with the non-experts scoring the poorest in each sport. Their conclusion was that there was some generic learning of pattern recognition in team sports that was transferable. The takeaway from this study is that there is benefit to having kids play multiple sports and that this may shorten the time and training needed to excel in a single sport in the future.

So, go ahead and let your kids play as many sports as they want. Resist the temptation to "overtrain" in one sport too soon. Playing several sports certainly will not hurt their future development and will most likely give them time to find their true talents and their favorite sport.


Source:
Abernethy, B., Baker, J., Côté, J. (2005). Transfer of pattern recall skills may contribute to the development of sport expertise. Applied Cognitive Psychology, 19(6), 705-718. DOI: 10.1002/acp.1102

Why The Offsides Flag Has Been "Ruud" to Italy

Two Euro 2008 games and two questionable offsides calls against Italy, one on defense, the other on offense, are still being talked about this weekend. First, in the Netherlands opener, van Nistelrooy scores from an obvious offsides position... except for Panucci, who is lying on the ground next to the goal. In fact, UEFA had to defend their referee for a correct interpretation. The call that did not get an explanation was Luca Toni's offsides on a cross from Zambrotta in the Romania match, which disallowed a first half goal. The first call was deemed correct, the second one was a blatant error.

Calling offsides correctly is one of the most difficult officiating duties in sports. In fact, some have argued that it is nearly impossible given the limitations of the human eye and the number of objects that need to be tracked by one assistant referee. Back in 2004, Francisco Belda Maruenda, M.D. of Centro de Salud de Alquerías in Murcia, Spain, took a look at the eye movements necessary along with their associated durations to determine if it was a humanly possible task. Let's look at his logic.

First, some eye physiology definitions are needed:
Saccadic movements - when we shift our eyes' focus from one object to another, we are making a saccadic movement. As an assistant referee (AR) looks from the ball carrier to the last defender to the offensive players, he needs to make several saccadic movements to take in the whole scene.

Vergence movements - there are two types, convergence (changing gaze from objects far away to objects closer to you), and divergence (just the opposite, near to far).

Accomodation - to change the focus of the eye from far to near or near to far, the convexity of the retina lens needs to change.

All of these eye movements, saccadic, vergence and accomodations take time to accomplish. Let's see how Maruenda added these up for an offsides call:

- the AR needs to keep track of at least four objects, the ball, the last two defenders and the offensive receiver of the pass. There may also be more offensive players to track as well.
- to make saccadic movements from the first object to each of the remaining objects will take about 130ms for the first object and then another 10ms per object after that. With four objects to track, that would be a total of about 160ms.
- if some of the players are on the far side of the field and some on the near side, then a vergence movement and an accomodation would be required, taking an additional 360ms for the accomodation and 640ms for the far to near vergence movement.
- of course, the players are constantly moving during the play, so their position is changing rapidly. If the speed of an offensive player is assumed to be 7.14 m/s, then in 100ms, they will have moved 71cm. This movement could be the difference between an onside position and an offside position. See the diagrams below (taken directly from the article)

Top: No offside, players in correct position.








Bottom: 100 ms later (players' velocity 7.14 m/s), offsides











The conclusion then, is that the total time needed for the AR to focus on at least four different objects in sequential order and process their positions cognitively is beyond the 100ms that would be needed for an offensive player to move from an onside position when the ball is played to a perceived offsides position when the AR finally focuses on him.

There have been some responses to Maruenda's logic, mainly centered on the fact that ARs have long known they can't watch the ball and the last defender, so they instead listen for the sound of the ball being struck while staying focused on the line of defense. This method may be used, but the sound of the crowd, the muted sound of the boot on the ball and the slower speed of sound may also have an effect on this judgement.

There is technology being developed to make offsides calls with multiple cameras, etc., but FIFA is not in favor of taking the flag away from the AR yet, just as they are against obvious goal line technology to watch for goals. It appears the debates and arguments will live on for the near future.



Belda Maruenda, F. (2004). Can the human eye detect an offside position during a football match?. BMJ, 329(7480), 1470-1472. DOI: 10.1136/bmj.329.7480.1470

Federer and Nadal Can See the Difference

Watching Roger Federer and Rafael Nadal battle it out in the French Open final and now again in the Wimbledon final, I started thinking more about the interceptive timing task requirements of each of their visuomotor systems... yeah, right. C'mon, I just needed a good opening line for this post.


However, other than a 120 mph tennis serve, take a second to think about all of the different sports that send an object flying at you at very high speeds that you not only have to see, but also estimate the speed of the object, the movement of the object and what you want to do with the object once it gets to you.



Some examples are:
- a hockey puck at a goalie (70-100 mph)
- a baseball pitch at a batter (70-100 mph)
- a soccer ball kicked at a keeper (60-90 mph)


Previously, we took a look at this in baseball and in soccer and also discussed the different types of visual skills in sports. There, we broke it down into three categories:

- Targeting tasks
- Interceptive timing tasks
- Tactical decision making tasks

The second category, interceptive timing tasks, deals with the examples above; stuff coming at you fast and you need to react. There are three levels of response that take an increasing level of brainpower.

First, there is a basic reaction, also known as optometric reaction. In other words, "see it and get out of the way". Next, there is a perceptual reaction, meaning you actually can identify the object coming at you and can put it in some context (i.e. that is a tennis ball coming at you and not a bird swooping out of the sky).

Finally, there is a cognitive reaction, meaning you know what is coming at you and you have a plan of what to do with it (i.e. return the ball with top-spin down the right line). This cognitive skill is usually sport-specific and learned over years of tactical training. Obviously, for professional tennis players, they are at the expert cognitive stage and have a plan for most shots. Federer's problem was that Nadal had better plans.

But, in order to reach that cognitive stage, they first need to have excellent optometric and perceptual skills. Can those skills be trained? Or are the best tennis players born with naturally better abilities? Did their training make them better tennis players or are they better players because of some natural skills?


Leila Overney and her team at the Brain Mind Institute of Ecole Polytechnique Federale de Lausanne (EPFL) recently studied whether expert tennis players have better visual perception abilities than other athletes and non-tennis players. Typically, motor skill research compares experts to non-experts and tries to deduce what the experts are doing differently to excel.

In this study, an additional category was added. Overney wanted to see if the perceptual skills of the tennis players were significantly more advanced than athletes of a similar fitness level, (in this case triathletes), to eliminate the variable of "fitness", and also more advanced than novice tennis players (the typical comparison). To eliminate the cognitive knowledge difference between the groups, she used seven non-sport specific visual tests. Please see the actual study for details of all the tests.

The bottom line of the results was that certain motion detection and speed discrimination skills were better in the tennis players (in other words, being able to track a ball coming at you and its movement side to side).


So, the expert tennis players were better at tracking balls coming at them than triathletes and non-tennis players.... seems pretty obvious(!) But, these results are a first step to answering the question of "can these skills be trained"? We see that there is, indeed, a difference in ability level between expert players and athletes that are in similar shape and competitive spirit. Now, the question becomes, "how did these tennis players acquire a higher level of perception skill"? Was it "nature or nurture", "genetically gifted or trained through practice"?


Source: Overney, L.S., Blanke, O., Herzog, M.H., Burr, D.C. (2008). Enhanced Temporal but Not Attentional Processing in Expert Tennis Players. PLoS ONE, 3(6), e2380. DOI: 10.1371/journal.pone.0002380

The Coach's Curse - Mental Mistakes

"Donadoni rues Italian 'mistakes' against Dutch"

"Mental errors cost Demons in regional quarterfinal"

"Mental mistakes doom Rays in loss to Cardinals"

 
Every day, there is always a new variety of stories linked to the phrase, "mental mistakes".  Either the writer recaps a game, calling out the mistakes or a coach or player claims that mistakes were made. It has become sort of a throwaway phrase, "...we made a lot of mental mistakes out there today, that we need to avoid if we want to get to the playoffs..." The million dollar question then is HOW to reduce these mental mistakes. And, to answer that, we need to define WHAT is a mental mistake?

In a previous post, I introduced the "Sports Cognition Framework", which is a trio of elements needed for success in sports. These three elements are:

- decision-making ability (knowing what to do)

- motor skill competence (being physically able to do it)

- positive mental state (being motivated and confident to do it)

Most of the time, a mental mistake is thought of as a breakdown of decision-making ability. The center fielder throws to the wrong base, the tight end runs the wrong route, or the defender forgets to mark his man, etc. These scenarios describe poor decisions or even memory lapses during the stress of the game. They are not necessarily the lack of skill to execute a play or the lack of confidence or motivation to want to do the right thing. It is a recognition, in hindsight, that the best option was not chosen. In addition to glaring negative plays, there are also missed opportunities on the field (i.e. taking a contested shot on goal, instead of passing to the open teammate).

So, back to the payoff question: HOW do we reduce mental mistakes and poor decisions? Just as we practice physical skills to improve our ability to throw, catch, shoot, run, etc., we need to practice making decisions using a a training system that directly exposes the athlete to these scenarios. Dr. Joan Vickers, who we met during our discussion of the Quiet Eye, has created a new system which she calls the "Decision-Training Model", and is the focus of the second half of her book, "Perception, Cognition, and Decision Training". As opposed to traditional training methods that separate skill training from tactical decision making training, the Decision-Training model (D-T) forces the athlete to couple her skill learning with the appropriate tactical awareness of when to use it.

So, instead of an "easy-first" breakdown of a skill, and then build it up step by step, D-T begins with a "hard-first" approach putting the "technique within tactics" demanding a higher cognitive effort right up front. The theory behind D-T is that the coach is not on the field with the player during competition, so the player must learn to rely on their own blended combination of skill and game awareness. Research from Vickers and others shows that D-T provides a more lasting retention of knowledge, while more traditional bottom-up training with heavy coach feedback delivers a stronger short-term performance gain, but that success in practice does not often translate later in games. Practice and training need to mirror game situations as often and as completely as the real thing.

There are three major steps to Decision-Training (p. 167):

1. Identify a decision the athlete has to make in a game, using one of the seven cognitive skills (anticipation, attention, focus/concentration, pattern recognition, memory, problem solving and decision making)

2. Create a drill(s) that trains that decision using one of the seven cognitive triggers (object cues, location cues, Quiet Eye, reaction-time cues, memory cues, kinesthetic cues, self-coaching cues)

3. Use one or more of the seven decision tools in the design of the drill (variable practice, random practice, bandwidth feedback, questioning, video feedback, hard-first instruction, external focus of instruction)

This post was just to serve as an introduction to D-T. Dr. Vickers and her team at University of Calgary offer full courses for coaches to learn D-T and apply it in their sport. Combined with the visual cues of the playing environment provided by the Quiet Eye gaze control, D-T seems to offer a better tactical training option for coaches and athletes. Coming up, we will continue the discussion of decision-making in sports with a look at some other current research. Please give me your thoughts on D-T and the whole topic of mental mistakes!

Take A Nap - Wake Up a Champion!

Hopefully, you have found this blog to be a nice source of information regarding the link between cognitive science/brain research and sports. Well, today, I have uncovered one of the most exciting, breakthrough, radical, theory-busting pieces of research on sports performance..... wait for it...... here it is:



"EXTRA SLEEP IMPROVES ATHLETIC PERFORMANCE"



I ran across this headline in my usual scan of science news feeds and did a double take. I thought, "there must be more to this than just the headline...". Nope, the title pretty much sums it up. The Onion could not have written it any better.



Here's the details of the study:

- Participants were five (5!) student-athletes on the Stanford Univ. swim team (Men's and Women's)

- First 2 weeks, they slept their "normal" amounts.

- Then, they extended their sleep to 10 hours per night for six to seven weeks.

- After the extended sleep period, they improved their 15 meter sprint time by .51 seconds and improved their start times off the blocks by .15 seconds.



I'm guessing that this improvement is significant for swimmers. But, doesn't this belong in the "Do we really need to study this or can we just believe what our Moms told us" category? This study helped confirm the author's previous study of six (6!) Stanford basketball players who improved their sprint speed and free throw shooting after getting additional sleep. The study also noted improvements in the athletes' mood and alertness after sleeping more... go figure.



From the lead researcher:

“These results begin to elucidate the importance of sleep on athletic performance and, more specifically, how sleep is a significant factor in achieving peak athletic performance,” said lead author Cheri Mah of the Stanford Sleep Disorders Clinic and Research Laboratory. “While this study focuses specifically on collegiate swimmers, it agrees with data from my other studies of different sports and suggests that athletes across all sports can greatly benefit from extra sleep and gain the additional competitive edge to perform at their highest level.”

“Typically, many athletes accumulate a large sleep debt by not obtaining their individual sleep requirement each night, which can have detrimental effects on cognitive function, mood, and reaction time,” said Mah. “These negative effects can be minimized or eliminated by prioritizing sleep in general and, more specifically, obtaining extra sleep to reduce one’s sleep debt.” Welcome to college...



Here's some additional, useful tips from the author:

• Make sleep a part of your regular training regimen.


• Extend nightly sleep for several weeks to reduce your sleep debt before competition.


• Maintain a low sleep debt by obtaining a sufficient amount of nightly sleep (seven to eight hours for adults, nine or more hours for teens and young adults).


• Keep a regular sleep-wake schedule, going to bed and waking up at the same times every day.


• Take brief naps to obtain additional sleep during the day, especially if drowsy.

So, there you go, practical, applied research ready for you to take advantage of in your pursuit of excellence in sports.



Now, if you'll excuse me, I'm going to go lie down for a few minutes...

DanPeterson.minti.com

Source: American Academy of Sleep Medicine (2008, June 9). Extra Sleep Improves Athletic Performance. ScienceDaily. Retrieved June 9, 2008, from: http://www.sciencedaily.com/releases/2008/06/080609071106.htm

See The Ball, Be The Ball - Vision and Sports

The whistle blows and Shaq goes to the line again after being fouled on purpose for the fourth time. And, again, we watch as he takes that awkward stance, looks at the basket and then clanks one of the back of the rim. We wonder how hard this can be... just aim and shoot! Isn't it that simple? Well, not exactly. In our introduction to this series I mentioned the research of Dr. Joan Vickers and her concept of the "Quiet Eye". In her book, Perception, Cognition and Decision Training, she describes this visual targeting pathway:


"...the visual pathway begins when information is registered on the eye's retina by the focal and ambient systems, then travels to the back of the head along the optic nerve and radiates to the occipital cortex, where visual information is registered as billions of features. These then race in parallel fashion both to the top of the head to the parietal cortex (dorsal) and along the sides of the head to the temporal (ventral) areas. There is an integration of information in the somatosensory cortex as the information goes to the frontal cortex, where the goals and intentions reside and plans are formulated for the specific event that is occurring. The flow of information then goes to the premotor and motor cortex at the top of the head before going down the spinal cord to the effectors." P.26


This same process repeats constantly during any athletic event and it is the most critical determinant of the outcome of the game. Just think about the types of visual work that needs to be done by an athlete (as defined by Dr. Vickers):

1. Targeting Tasks - being able to fixate on a target, fixed or moving, to be able to throw, kick or send an object towards it. (i.e. Shooting or passing a baseball, football, basketball, soccer ball, hockey puck, etc.)

2. Interceptive Timing Tasks - being able to recognize, track and finally control an object as it comes at you (aka "catching")

3. Tactical Decision Making Tasks - being able to take in an environmental scan of the field/court and recognize patterns of all the moving objects (i.e. a quarterback scanning his receivers and choosing the best option for a pass).

All of these scenarios require the athlete to focus or "gaze" on the right points in the environment and ignore the rest of the scene. Dr. Vickers' work has been to observe athletes of different skill levels, expert and non-expert, and define the "best practices" of visual control so that the non-expert athletes can be coached to better performance. Her research lab uses "eye-trackers" (see photo) to monitor the focus and gaze of the athlete's pupils as they perform their skills.

For example, she has found that expert baseball hitters focus on the release point of the ball exclusively, rather than random fixations on the pitcher's arm, head, jersey, etc. She found that expert golf putters focus on a specific point on the cup, then a specific point on the back of the ball and remain fixated on the point on the ball after the ball has left the putter blade.

Novices allow their gaze to wander from the ball to the hole, without a very specific focal point on either the cup or the ball. The term "Quiet Eye" comes from these observations that expert performers have consciously chosen points in their space to focus on rather than allowing their eyes to wander and fixate on multiple points (i.e. a "noisy" eye).


So, why does the Quiet Eye work? When we fixate on key points in our field of vision, how does this help our neuromuscular systems perform better? The subconscious part of our brain may be recognizing a pattern that we have seen and experienced before and directing our movements based on this information. Some have called this "muscle memory", meaning our brain has learned through repetition and practice how to throw a ball to a moving receiver at that distance and speed, and so, when presented with a similar scenario, knows what to do. Think about when you shoot a jump shot and sometimes you get that sensation, as soon as it leaves your hand, that the ball is going in. Your brain may be telling you that, based on past experience, when you've executed the same aim and same muscle movement then the ball has gone in.

This takes us back to the discussion we had in our previous post on baseball fielding regarding theories of perception-action combinations. The Information Processing model claims that we perceive the environment first through our senses, primarily our vision. Then, we access our memory to find the rules, suggestions and knowledge that we have gained from past experiences and these memories guide our action in the moment.

The Ecological Psychology model removes the memory access step and claims that our perception of the environment leads directly to our actions, as there is not enough time to access our lessons. If that is true, then how does the Quiet Eye help us? It seems the Quiet Eye is what we need to connect the current scenario (standing on the free throw line looking at the basket) with our lessons learned from the past (how we made this shot hundreds of times before). Research continues on this question and I'm sure we'll come back to this in future posts.


Next time, I will take a look at Dr. Vickers' "Decision Training Model", which builds on the Quiet Eye theory to train athletes to improve their tactical in-game decision making. We will look at the athletes who are known as having good "vision of the field" and how to raise everyone's game to that level.

So Why Can't Shaq Make Free Throws?

The NBA league average for free throw shooting is about 75%. Shaquille O'Neal's career average is 52.4%. Even worse, Ben Wallace's career average is 41.9%. The average for the NCAA Division 1 teams is 69%. The obvious question is why can't Shaq or Ben or Memphis do any better, but the bigger question is why do most of the best basketball players in the world miss 2 or 3 free throws out of 10? Maybe they just haven't heard about Joan Vickers and the "Quiet Eye".

For me, the best science is applied science. The same goes for sports science. Theories, physics, psychology, etc. are only useful in sports if they can be used to improve in-game performance. That's why I have always been a fan of academic work that leads to useful techniques in the field. Professor Joan Vickers of the University of Calgary has been applying her research into the human visual system and its effects on sports performance for over 25 years. She is the discoverer of the "Quiet Eye" skill that has been shown to significantly improve accuracy in targeting and decision-making skills in many sports. In addition to this "gaze control" technique, she also has developed a 7-step teaching process to improve the in-game decision-making of athletes, based partly on their visual perception skills.

She has a new book out that condenses all of these ideas, called Perception, Cognition and Decision Training. Over the next few days, I will do my best to paraphrase and explain the most useful information and techniques, but of course the best source is this book.
For an opening primer on the Quiet Eye, please take a look at this episode and this online video of PBS' Scientific American with Hawkeye himself, Alan Alda, shooting free throws.

Baseball on the Science Channel(!)

Just a quick follow-up for those that read the Baseball and the Brain series from a week ago. I found a great companion series from the Science Channel/Discovery Channel that goes into alot of the same detail about the physics and skills of Pitching, Hitting and Fielding.
Here's the Science Channel series: Baseball's Secret Formula
Inside that series is a great video sequence on the Physics of Baseball from the Discovery Channel.
Enjoy!

Cristiano Roboto - The Soccer Playing Robot

Back in April, 80 teams of researchers from 15 countries got together to compete in the 2008 RoboCup German Open, a soccer tournament where the "athletes" are all totally autonomous robots like the one pictured above. Four players and a goalkeeper per team play on a 20x14 meter field and are independent of any human remote control. They need to have sub-systems that "see" the field, opponents and the goal; have locomotion logic to move forward, sideways and back; some tactical logic to sense an opponent and avoid "it"; and targeting to kick the ball in the direction of the goal.

You can see some brief clips of the robots on the pitch here. Try the second video to see the most game highlights. The discussion is in German, if any of you speak it, but the game clips are what to focus on.

The more practical future applications of these sub-systems is to program robots to do more meaningful tasks like search and rescue operations in dangerous areas, (fire, earthquake, enemy zones), using the same visual, locomotion, search algorithms that guide the robot on the soccer field. In fact, there is a RoboRescue competition as well.

What struck me most about watching these robots was the complexity of the logic that needs to be programmed. The visual system that must learn the field, the sidelines, the dimensions of the goal, the difference between a teammate and an opponent. The tactical system that must be "goal" directed, (pun intended). It must learn that the object of the game is to put the ball into the opponent's goal and stop the ball from entering your own goal.

The constant motion sensor to understand where they are on the field, when to dribble, when to stop, when to aim and when to kick. The researchers/programmers in this competition are some of the brightest minds in the world, yet when you watch the video, you might have the same reaction that I did; that this is an impressive start, but they still look rather rudimentary.

Thinking about the topics we cover here, we often take for granted all of the logic and skills that human athletes demonstrate every day. I'm thinking especially of our kids that can easily surpass the performance of these robots, even as young as 3 years old. My fascination, and probably these researchers, is HOW we are able to do these tasks so easily. If we understand more about the "how", then we can also design better practice environments to advance those skills even faster.
Source: Fraunhofer-Gesellschaft (2008, April 4). Soccer Robots Compete For The Title. ScienceDaily. Retrieved May 29, 2008, from http://www.sciencedaily.com/releases/2008/04/080401110128.htm#

A Keeper's Nightmare - Beckham, Ronaldo or Juninho

Whether you bend it like Beckham or Ronaldo or Juninho or even Nakamura; the curving free kick is one of the most exciting plays in soccer/football. Starting with Rivelino in the 1970 World Cup and on to the specialists of today, more players know how to do it and understand the basic physics behind it, but very few can perfect it. But, when it does happen, by chance or skill, it is the highlight of the game.

But let's take a look at this from the other side, through the eyes of the goalkeeper. Obviously, its their job to anticipate where the free kick is going and get to the spot before the ball crosses the line. He sets up his wall to, hopefully, narrow the width of the target, but he knows some players are capable of bending the ball around or over the wall towards the near post. If you watch highlights of free kick goals, you often see keepers flat-footed, just watching the ball go into the top corner. Did they guess wrong and then were not able to react? Did they guess right but misjudged the flight trajectory of the ball. How much did the sidespin or "bend" affect their perception of the exact spot where the ball will cross the line?

Researchers at Queen's University Belfast and the University of the Mediterranean in France tried to figure this out in this paper. They wanted to compare the abilities of expert field players and expert goalkeepers to accurately predict if a free kick would result in an on-target goal or off-target non-goal. First, a bit about why the ball "bends". We can thank what's called the "Magnus Force" named after the 19th-century German physicist Gustav Magnus. As seen in the diagram below, as the ball spins counter clockwise (for a right-footed player using his instep and kicking the ball on the right side), the air pressure on the left side of the ball is lower as the spin is in the same direction as the oncoming air flow. On the right side of the ball, the spin is in the opposite direction of the air flow, building higher pressure. The ball will follow the path of least resistance, or pressure, and "bend" or curve from right to left. The speed of the spin and the velocity of the shot will determine the amount of bend. For a clockwise spin, the ball bends from left to right.



The researchers showed the players three different types of simulated kicks, a kick bent to the right, a kick bent to the left and a kick with no spin at all. They showed the players these simulations with virtual reality headsets and computer controlled "kicks" and "balls" which they could vary in flight with different programming. The balls would disappear from view at distances of 10 and 12.5 meters from the goal. The reasoning is that this cutoff would correspond with the deadline for reaction time to make a save on the ball. In other words, if the keeper does not correctly guess the final trajectory and position of the ball by this point, he most likely will not be able to physically get to the ball and make the save.

The results showed that both the players and the keepers, (all 20 were expert players from elite clubs like AC Milan, Marseille, Bayer LeverkusenSchalke 04), were able to correctly predict the result of the kicks with no spin added. However, as 600 RPM spin, either clockwise or counter-clockwise, was added to the ball, the players success declined significantly. Interestingly, the keepers did no better, statistically, then the field players. The researchers conclusion was that the players used the "current heading direction" of the ball to predict the final result, rather than factoring the future affect of the acceleration and change in trajectory caused by the spin.

Game Highlights
Just as we saw in the Baseball Hitting post, our human perception skill in tracking flying objects, especially those that are spinning and changing direction, are not perfect. If we understand the physics of the spinning ball and we can better guess at its path, but the pitcher or the free kick taker doesn't usually offer this information beforehand! In the next few posts, I'll be looking at a related topic in perception; a concept known as "Quiet Eye", developed by Prof. Joan Vickers. Check back as this is one of the best applications of cognitive science in sports that I have seen.

Source:
Craig, C.M., Berton, E., Rao, G., Fernandez, L., Bootsma, R.J. (2006). Judging where a ball will go: the case of curved free kicks in football. Naturwissenschaften, 93(2), 97-101. DOI: 10.1007/s00114-005-0071-0