"Donadoni rues Italian 'mistakes' against Dutch"
"Mental errors cost Demons in regional quarterfinal"
"Mental mistakes doom Rays in loss to Cardinals"
If
you are a frequent visitor to my site, you may have noticed a
customized Google news feed on the right-hand side of the page. At the
top are different phrases to
select to get relevant news stories (i.e. the "Sports Science"
selection will list stories on just that.) Every day, there is always a
new variety of stories linked to the phrase, "mental mistakes" (the
list from 6/10/08 is displayed above). 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 wide receiver 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 the 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!
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.
Both umpires and referees have been making news, despite their often repeated goal, stated by World Series rookie umpire Tom Hallion said after Game 3: “As an umpire, you never want to be involved in the outcome of the game.” He added: “We like to get every play right. We’re human beings, and sometimes we get them wrong.”
Hallion and his five partners at October's Fall Classic did not quite reach their goal. In Game 3, Hallion called Carl Crawford safe at first on a close play, but replays showed he was out. In Game 4, it was the Phillies who benefited after veteran umpire, Tim Welke, called Jimmy Rollins safe at third during a rundown, despite an obvious tag on his backside.
The men in stripes are not doing any better. Veteran NFL referee, Ed Hoculi (aka "Guns"), blew a call in Week 2's Broncos/Chargers game. Broncos' quarterback Jay Cutler let the ball slip out of his hand and the Chargers recovered. However, Hoculi ruled the play an incomplete pass. The video replay booth called it a fumble, but since Hoculi had blown his whistle, the call could not be reversed.
Not to be outdone by their American counterparts, two English soccer officials have set a new standard for head-scratching calls.
In a Sept. 22 game between Watford and Reading, referee Stuart Atwell and one of his linesmen, Nigel Bannister, combined to become the ultimate sales pitch for any type of goal-line replay technology. After a scramble in front of goal, the ball bounced across the end line, two yards wide of the nearest goalpost. As both teams headed up the field and Watford prepared for a goal kick, Bannister signaled to Atwell that he saw the ball cross the line between the goalposts and that Reading should be awarded a goal. To the astonishment of all 22 players on the field and the 14,761 fans, Atwell overruled his own eyes and gave the goal to Reading. The replay made it painfully obvious how wrong the call was:
So, assuming officials want some kind of automated technical assistance, what is available?
First, pure video instant replay gives officials a second, slower chance to see the play again and possibly adjust their live call. All four major sports leagues in the United States use replay at some level.
In addition to judging if a shot was taken before the buzzer, the NBA added replay this season to differentiate 2-point versus 3-point baskets. MLB commissioner Bud Selig has put a stop to the spread of replay beyond the home run/foul ball call for now, but public pressure may change that. The NHL’s use of replay focuses mainly on different goal scoring scenarios. The NFL is the most advanced user of replay to judge multiple situations.
Second, an emerging selection of decision-support tools can make the actual call for the officials using location-based technology. In tennis, the Hawk-Eye system is being used at such high-profile events as Wimbledon and the U.S. Open.
A
system of six high-speed cameras records a ball's movement, which is
useful when it bounces near one of the court lines. It feeds the
cameras' input to a central computer that analyzes the data from all
angles and then creates a motion graphic that simulates the ball's
location when it bounces on the court, either on the line or next to
the line, with a judgment of "in" or "out."
A
player can challenge a line umpire's original call, but Hawk-Eye's
ruling is then final. The interesting illusion that tennis fans have
accepted is watching this 3D simulation as if it is based on a single
camera’s footage of the ball. Actually, the sequence shown to viewers
is Hawk-Eye's best estimate as to what actually happened based on the
data it received from the cameras. There have been more than 550
challenges at the U.S. Open since 2006 when Hawk-Eye was installed.
Thirty percent of those challenges resulted in a call being reversed.
In soccer, Adidas and Cairos Technologies
have partnered to create an "intelligent" ball that includes a
microchip that transmits its location on the field to a computer.
The system also places a thin, underground electrical wire that surrounds each goal. If the ball's location is sensed to be completely inside the boundary of the goal, a signal is sent to a watch worn by the referee indicating that a goal has been scored.
This technology would have saved Atwell and Bannister from their embarrassment. However, after extensive testing at several FIFA tournaments, Sepp Blatter, president of FIFA, announced in March that instead of technology, two additional human referee assistants would be used to judge whether a goal was scored. "Let it be as it is and let's leave it (soccer) with errors," Blatter said. "The television companies will have the right to say he (the referee) was right or wrong, but still the referee makes the decision — a man, not a machine." Interestingly, the English Premier League was also testing the use of Hawk-Eye as an alternative to Adidas' smart ball.
Even if the umps and refs don't want to use the technology, sports television producers still want to empower the fans.
In baseball, ESPN's "K-zone" and Fox Sports' "Fox Trax" show a virtual representation of pitches and the strike zone to let us judge the accuracy of the home-plate umpire's calls. Think that last called strike was a bit outside? Watch the computer generated replay that is accurate to within one-half inch.
Then, go ahead and yell at the ump. If only they could come up with a way to transmit our voices directly into the stadium.
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
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)
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 MentalCristiano Roboto - The Soccer Playing Robot
From: Cristiano Roboto - The Soccer Playing Robot
Sports Are 80 Percent Mental
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
From: A Keeper's Nightmare - Beckham, Ronaldo or Juninho
Sports Are 80 Percent MentalWhether 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.
