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Decision Making in Sports

Why Pro Athletes Attract Trouble

As first seen on LiveScience.com

and Sports Are 80 Percent Mental

From the "athletes behaving badly" department (in the past month, anyway):

•    NHL bad boy (Sean Avery) was suspended for six games for a crude remark.

•    Six NFL players were suspended for allegedly violating the league's drug policy.

•    Another NFL player (Adam "Pacman" Jones) returned to his team's roster after being suspended, again, for an off-field altercation.

•    Oh, and NFL receiver (Plaxico Burress) accidentally shot himself in a nightclub with a gun he was not licensed to carry.

Despite the 24/7 media coverage of each of these incidents, sports fans have become accustomed to and somewhat complacent with hearing about athletes and their deviant acts.

In fact, new statistics reveal that bad behavior is clearly evident among high school athletes, particularly in high-contact sports.

It starts young

Besides the highly publicized stories, there are thousands more across the nation involving amateur athletes taking risks both on and off the field. From performance-enhancing supplements to referee/official abuse to fights, guns and recorded crimes, the image of sports as a positive influence on athletes may need a second look.

Granted, in a population of any size there will be a few bad apples. However, these actions have become so prevalent that academic researchers have created a branch of study called "deviance in sports" attached to the sports sociology tree. 

They are asking questions and challenging some assumptions about cause and effect. Is there a connection between sports participation and deviance? Does the intense competition and battle on the field shape a player's off-the-field lifestyle? Since success in sports brings attention and prestige to athletes, does the risk of losing that status cause a need to take risks to maintain their "top dog" positions?

In their new book, "Deviance and Social Control in Sport," researchers Michael Atkinson and Kevin Young emphasize the confusing environment surrounding athletes. They describe two types of deviance: wanted and unwanted.

Owners, players and fans may know that certain behaviors are literally against the rules but are at the same time appreciated as a sign of doing whatever it takes to win.  Performance-enhancing drugs are not allowed in most sports, but athletes assume they will improve their performance, which helps their team win and keeps fans happy. Fights in hockey will be, according to the rule book, penalized, but this deviance is assumed to be wanted by fans and teammates as a sign of loyalty.

However, related bad behavior can quickly turn on a player to being socially unwanted. 

Abuse of drugs that don't contribute to a win, (marijuana, cocaine, alcohol), will transform that same player into a villain with shock and outrage being reported in the media. In the Sean Avery example, a hockey player fighting to defend his teammates on the ice can then be suspended from the team and criticized by those same teammates for an off-color remark.

Real statistics

Most athletes who make it to the professional level have been involved in sports since youth. Sports sociologists and psychologists often look at the early development years of athletes to get a glimpse of patterns, social norms and influences that contribute to later behaviors.

In a recent American Sociological Review article, Derek Kreager, assistant professor of sociology at Penn State University, challenged the long-held belief that youth sports participation is exclusively beneficial to their moral character development. 

With the focus on teaching teamwork, fair play, and self esteem, sports are often cited as the antidote to delinquency. But Kreager notes that other studies have looked at the culture that surrounds high school and college athletes and identified patterns of clichés, privileges and attitudes of superiority. For some athletes, these patterns are used to justify deviant behavior.

In fact, his most recent research attempted to find a cause-and-effect link between deviant behavior and specific sports. Specifically, he asked if high-contact, physical sports like football and wrestling created athletes who were more prone to violent behavior off the field.

Using data from the National Longitudinal Study of Adolescent Health, more than 6,000 male students from across 120 schools were included. The data set included a wide collection of socioeconomic information, including school activities, risk behaviors and at-home influences. Kreager's study analyzed the effects of three team sports (football, basketball, and baseball) and two individual sports (wrestling and tennis) on the likelihood of violent off-field behavior, specifically, fighting.

To isolate the effect of each sport, the study included control groups of non-athletes and those that had a history of physical violence prior to playing sports. 

For team sports, football players were 40 percent more likely to be in a confrontation than non-athletes. In individual sports, wrestlers were in fights 45 percent more often, while tennis players were 35 percent less likely to be in an altercation. Basketball and baseball players showed no significant bias either way.

"Sports such as football, basketball, and baseball provide players with a certain status in society," Kreager said. "But football and wrestling are associated with violent behavior because both sports involve some physical domination of the opponent, which is rewarded by the fans, coaches and other players. Players are encouraged to be violent outside the sport because they are rewarded for being violent inside it."

Getting The Call Right With Technology

As first seen at LiveScience.com

and Sports Are 80 Percent Mental

The loneliest men in sports have not been making any friends lately. 

Stats Vs. Hunches - The Moneyball Era In Sports

From: Stats Vs. Hunches - The Moneyball Era In Sports

Sports Are 80 Percent Mental

Most baseball general managers live in obscurity most of their careers. Its their first hire, the manager, that usually gets the red hot spotlight, after every win and loss, second-guessed by reporters with recorders and then later by fans. The GM puts the players on the field and lets the manager and his coaches take it from there. Billy Beane , Oakland A's general manager, could have also been an unknown, albeit interesting, name to the baseball audience if it were not for author Michael Lewis' 2003 book, Moneyball . Moneyball was a runaway hit (even today, 5 years later, it is #19 on Amazon's list of baseball books). It has morphed into a full-fledged catchphrase philosophy used by everyone from Wall Street (where Beane borrowed the concept) to business consulting. The general theme is to find undervalued assets (ballplayers) by focusing on statistics that your competition is ignoring. Of course, you have to believe in your metrics and their predictive value for success (why has everyone else ignored these stats?) The source of most of Beane's buried treasure of stats was Bill James and his Sabrmetrics. Like picking undervalued stocks of soon to explode companies, Beane looked for the diamond in the dust (pun intended) and sign the player while no one was looking. Constrained by his "small-market" team revenues, or maybe by his owners' crowbar-proof wallets, he needed to make the most from every dollar.

The combination of a GM's shrewd player selection and a manager who can develop that talent should reward the owner with the best of both worlds: an inexpensive team that wins. This salary vs. performance metric is captured perfectly in this "real-time" graphic at BenFry.com . It connects the updated win-loss record for each MLB team with its payroll to show the "bang for the buck" that the GMs/managers are getting from their players. Compare the steep negative relationship for the Mets, Yankees, Tigers and Mariners with the amazing results of the Rays, Twins and Beane's own A's. While the critics of Moneyball tactics would rightly point to the A's lack of a World Series win or even appearance, the "wins to wages" ratio has not only kept Beane in a job but given him part ownership in the A's and now the newly resurrected San Jose Earthquakes of soccer's MLS. Beane believes the same search for meaningful and undiscovered metrics in soccer can give the Quakes the same arbitrage advantage. In fact, there are rumours that he will focus full-time on conquering soccer as he knows there are much bigger opportunities worldwide if he can prove his methods within MLS.

In baseball, Beane relied on the uber-stat guru, Bill James, for creative and more relevant statistical slices of the game. In soccer, he is working with some top clubs including his new favorite, Tottenham-Hotspur, of the English Premier League. While he respects the history and tradition of the game, he is confident that his search for a competitive advantage will uncover hidden talents. Analytical tools from companies such as Opta in Europe and Match Analysis in the U.S. have combined video with detailed stat breakdowns of every touch of the ball for every player in each game. Finding the right pattern and determinant of success has become the key, according to Match Analysis president Mark Brunkhart as quoted earlier this year,
"You don't need statistics to spot the real great players or the really bad ones. The trick is to take the players between those two extremes and identify which are the best ones. If all you do is buy the players that everyone else wants to buy then you will end up paying top dollar. But if you take Beane's approach - to use a disciplined statistical process to influence the selection of players who will bring the most value - then you are giving yourself the best chance of success. Who would not want to do that?"

Not to feel left out (or safe from scrutiny), the NBA now has its own sport-specific zealots. The Association for Professional Basketball Research (APBR) devotes its members time and research to finding the same type of meaningful stats that have been ignored by players, coaches and fans. They, too, have their own Moneyball-bible, "The Wages of Wins " by David Berri, Martin Schmidt, and Stacey Brook. David Berri's WoW journal/blog regularly posts updates and stories related to the current NBA season and some very intriguing analysis of its players and the value of their contributions. None other than Malcolm Gladwell, of Tipping Point and Blink fame, provided the review of Wages of Wins for the New Yorker. One of the main stats used is something called a player's "Win Score" which attempts to measure the complete player, not just points, rebounds and assists.

Win Score (WS) = PTS + REB + STL + ½*BLK + ½*AST – FGA – ½*FTA – TO – ½*PF. (Points, Rebounds, Steals, Blocked Shots, Assists, Field Goal Attempts, Free Throw Attempts, Turnovers, Personal Fouls)

WS is then adjusted for minutes played with the stat, WS48. Of course, different player positions will have different responsibilities, so to compare players of different positions the Position Adjusted Win Score per 48 minutes or PAWS48 is calculated as: WS48 – Average WS48 at primary position played. This allows an apples to apples comparison between players at a position, and a reasonable comparison of players value across positions. Berri's latest article looks at the fascination with Michael Beasley and some early comparisons in the Orlando Summer League.

Will these statistics-based approaches to player evaluation be accepted by the "establishment"? Judging by the growing number of young, MBA-educated GMs in sports, there is a movement towards more efficient and objective selection criteria. Just as we saw in previous evidence-based coaching articles , the evidence-based general manager is here to stay.

Teaching Tactics and Techniques in Sports

From: Teaching Tactics and Techniques In Sports

Sports Are 80 Percent Mental

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), summarized the 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.

Of course, we are always interested in your thoughts and opinions!  Please add your comments.



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

Why The Offsides Flag Has Been "Ruud" to Italy

From: Why The Offsides Flag Has Been "Ruud" to Italy

Sports Are 80 Percent Mental

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.



Source: 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

From: Federer and Nadal Can See the Difference

Sports Are 80 Percent Mental

Watching Roger Federer and Rafael Nadal battle it out in the French Open final last month, and now the epic 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"?

What do you think?

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

From:

The Coach's Curse - Mental Mistakes

Sports Are 80 Percent Mental

Cristiano Roboto - The Soccer Playing Robot

From: Cristiano Roboto - The Soccer Playing Robot

Sports Are 80 Percent Mental

A Keeper's Nightmare - Beckham, Ronaldo or Juninho

From: A Keeper's Nightmare - Beckham, Ronaldo or Juninho

Sports Are 80 Percent Mental

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.

Baseball and the Brain - Hitting

 

From: Baseball and the Brain - Hitting

Sports Are 80 Percent Mental

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". Certainly, at the major league level, where pitches can reach 100 miles per hour, this is believable, but even at Little League, High School and College/Minor leagues, the odds are against the hitter. Looking at batting averages, 3 hits out of 10 at-bats will earn a player millions of dollars in the bigs, while averaging 4 or 5 hits out of 10 at the lower leagues will earn you some attention at the next level. As most of you know, Williams was the last major league player to hit .400 for an entire season and that was back in 1941, almost 67 years ago! In my second of three posts of the Baseball and the Brain series, we'll take a quick look at some of the theory behind this complicated skill.

Again, my main reference for these ideas is "The Psychology of Baseball" by Mike Stadler.


Some questions that come to mind regarding hitting a pitched baseball:
- What makes this task so hard? Why can't players, who practice for years and have every training technique, coach and accumulated knowledge at their disposal, perform at a consistenly higher level?
- What can be improved? Hand-eye reaction time? Knowledge of situational tendencies (what pitch is likely to be thrown in a given game situation)?

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. As was discussed in the Pitching post, 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. So, a hitter must 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 in his book, doing both of these things is 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. This perception is known as angular velocity. The car is going a constant speed, but appears to be "speeding up" as it passes you, because your eyes need to move more quickly to keep up. This same concept applies to the hitter. 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.

Game Summary
As in pitching, our eyes and brain determine much of the success we have as hitters. We took a quick look as it relates to hitting a baseball, but the same concepts apply to hitting any moving object; tennis, hockey, soccer, etc. In future posts, we'll look at practical ways to improve this tracking skill and the hand/eye/brain connection. As usual, practice will improve performance, but we want to identify the unique practice techniques which will be most effective. Tracking a moving object also applies to catching, which we'll look at next.

Baseball and the Brain - Pitching

From: Baseball and the Brain - Pitching

Sports Are 80 Percent Mental

As promised, we begin our look at the three most important technical skills of baseball: Pitching, Hitting and Catching. Each of these skills apply to other sports as well, but I thought we'd stick with the current season of baseball as the sport du jour. Again, my focus for "80 Percent Mental" is to look at sports cognition in a generic sense across all sports, occasionally digging deeper into individual sport specialties. The practical side of this is to understand how our brains and nervous system perform these skills that we often take for granted, so that we can brainstorm (yuk-yuk) on new ways to teach, practice and perfect these skills.

Pitching/Throwing
Pitching a 3" diameter baseball 46 feet (for Little League) or 60 feet, 6 inches over a target that is 8 inches wide requires an accuracy of 1/2 to 1 degree. Throwing it fast, with the pressure of a game situation makes this task one of the hardest in sports. In addition, a fielder throwing to another fielder from 40, 60 or 150 feet away, sometimes off balance or on the run, tests the brain-body connection for accuracy. So, how do we do it? And how can we learn to do it more consistently?

Questions that come to my mind regarding pitching/throwing skills and baseball include:
- Why can't a pitcher control ALL of his/her pitches? Why do some not only miss the strike zone, but are wild?
- Is the breakdown physical in the muscle sequence of the throw or is it in the connection between eyes, brain and body?

Again, one the best references I have found on this is "The Psychology of Baseball" by Mike Stadler, published by Gotham Books. Prof. Stadler digs into many of these topics and I will paraphrase from his findings. I won't do it justice here, so please put it on your reading list.

There are two dimensions to think about when throwing an object at a target: vertical and horizontal. The vertical dimension is a function of the distance of the throw and the effect of gravity on the object. So the thrower's estimate of distance between himself and the target will determine the accuracy of the throw vertically. Basically, if the distance is underestimated, the required strength of the throw will be underestimated and will lose the battle with gravity, resulting in a throw that will be either too low or will bounce before reaching the target. An example of this is a fast ball which is thrown with more velocity, so will reach its target before gravity has a path-changing effect on it. On the other hand, a curve ball or change-up may seem to curve downward, partly because of the spin put on the ball affecting its aerodynamics, but also because these pitches are thrown with less force, allowing gravity to pull the ball down. In the horizontal dimension, the "right-left" accuracy is related to more to the "aim" of the throw and the ability of the thrower to adjust hand-eye coordination along with finger, arm, shoulder angles and the release of the ball to send the ball in the intended direction.

So, looking at our first question, how do we improve accuracy in both dimensions? Prof. Stadler points out that research shows that skill in the vertical/distance estimating dimension is more genetically determined, while skill horizontally can be better improved with practice. Remember those spatial organization tests that we took that show a set of connected blocks in a certain shape and then show you four more sets of conected blocks? The question is which of the four sets could result from rotating the first set of blocks. Research has shown that athletes that are good at these spatial relations tests are also accurate throwers in the vertical dimension. Why? The thought is that those athletes are better able to judge the movement of objects through space and can better estimate distance in 3D space. Pitchers are able to improve this to an extent as the distance to the target is fixed. A fielder, however, starts his throw from many different positions on the field and has more targets (bases and cut-off men) to choose from, making his learning curve a bit longer.

If a throw or pitch is off-target, then what went wrong? Prof. Stadler collects many different studies that review the possible physiological/mechanical reasons for "bad throws". Despite all of the combinations of fingers, hand, arm, shoulder and body movements, it seems to all boil down to the timing of the finger release of the ball. In other words, when the pitcher's hand comes forward and the fingers start opening to allow the ball to leave. The timing of this release can vary by hundredths of a second but has significant impact on the accuracy of the throw. But, its also been shown that the throwing action happens so fast, that the brain could not consciously adjust or control that release in real-time. This points to the throwing action being controlled by what psychologists call an automated "motor program" that is created through many repeated practice throws. But, if a "release point" is incorrect, how does a pitcher correct that if they can't do so in real-time? It seems they need to change the embedded program by more practice.

Another component of "off-target" pitching or throwing is the psychological side of a player's mental state/attitude. Stadler identifies research that these motor programs can be called up by the brain by current thoughts. There seems to be "good" programs and "bad" programs, meaning the brain has learned how to throw a strike and learned many programs that will not throw a strike. By "seeding" the recall with positive or negative thoughts, the "strike" program may be run, but so to can the "ball" program. So, if a pitcher thinks to himself, "don't walk this guy", he may be subconsciously calling up the "ball" program and it will result in a pitch called as a ball. So, this is why sports pscyhologists stress the need to "think positively", not just for warm and fuzzy feelings, but the brain may be listening and will instruct your body what to do.

Game Summary
I've only touched the surface for this topic. We'll see some of these themes in the hitting and catching posts that are coming up. One useful takeaway here for youth coaches is that some players will have a genetic advantage in throwing and may be your "natural" pitchers. As we dig deeper into these topics, we will be able pull out more practical tips for players and coaches.

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