HGH - Human Growth Hoax?
Athletes, both professional and amateur, as well as the general public are convinced that human growth hormone (HGH), Erythropoietin (EPO) and anabolic-androgenic steroids (AAS)
are all artificial and controversial paths to improved performance in
sports. The recent headlines that have included Barry Bonds, Marion
Jones, Floyd Landis, Dwayne Chambers, Jose Canseco, Jason Giambi, Roger
Clemens and many lesser known names (see the amazingly long list of doping cases in sport)
have referred to these three substances interchangeably leaving the
public confused about who took what from whom. With so many athletes
willing to gamble with their futures, they must be confident that they
will see significant short-term results. So, is it worth the risk?
Two very interesting recent studies provide some answers on at least
one of the substances, HGH.
A team at the Stanford University School of Medicine, led by Hau Liu MD,
recently reviewed 27 historical studies on the effects of HGH on
athletic performance, dating back to 1966 (see reference below). They
wanted to see if there were any definitive links between HGH use and
improved results. In some of the studies, test volunteers who received
HGH did develop more lean body mass, but also developed more lactate
during aerobic testing which inhibited rather than helped performance.
While their muscle mass increased, other markers of athletic fitness,
such as VO2max remained unchanged. “The key takeaway is that we don’t
have any good scientific evidence that growth hormone improves athletic
performance,” said senior author Andrew Hoffman, MD, professor of endocrinology, gerontology and metabolism.
Both Liu and Hoffman cautioned that the
amounts of HGH given to these test subjects may be much lower than the
the purported levels claimed to be taken by professional athletes.
They also pointed out that at a professional level, a very slight
improvement might be all that is necessary to get an edge of your
opponent. Hoffman also added an insightful comment, “So much of
athletic performance at the professional level is psychological.” If
an athlete takes HGH, sees some muscle mass growth and isn't 100% sure
of its performance capabilities, might he assume he now has other
"Superman" powers?
That is exactly the premise that a
research team from Garvan Institute of Medical Research in Sydney,
Australia used to find out if HGH users simply relied on a placebo effect.
Sixty-four participants, young adult recreational athletes, were
divided into two groups of 32 and tested for a baseline of athletic
ability in endurance, strength, power and sprinting. One group
received growth hormone and the other group received a simple placebo.
It was a "double-blind" study in that neither the participants nor the
researchers knew during the testing which substance each group received.
At the end of the 8 week treatment, the athletes were asked if they thought they were in the HGH group or the placebo group. Half of the group that had received the placebo incorrectly guessed that they were on HGH. Not too surprisingly, the majority of the "incorrect guessers" were men. Here's where it gets interesting. The incorrect guessers also thought that their athletic abilities had improved over the 8 week period. The team retested all of the placebo group and actually did find improvement across all of the tests, but only significantly in the high-jump test.
Jennifer Hansen, a nurse researcher and Dr. Ken Ho,
head of the pituitary research unit at Garvan have not released the
data on the group that did receive the HGH, but they will in their
final report coming soon.
So, let's recap. On the one hand, we have a research review that claims there is not yet any scientific evidence that HGH actually improves sports performance. Yet, we have hundreds, if not thousands, of athletes illegally using HGH for performance gain. Showing the effect of the "if its good enough for them, its good enough for me" beliefs of the public regarding professional athlete use of HGH, we now have research that shows even those who received a placebo, but believed they were taking HGH not only thought they were improving but actually did improve a little. Once again, we see the power of our own natural, non-supplemented brain to convince (or fool) ourselves to perform at higher levels than we thought possible.
Liu, H., Bravata, D.M., Olkin, I., Friedlander, A., Liu, V., Roberts, B., Bendavid, E., Saynina, O., Salpeter, S.R., Garber, A.M. (2008). Systematic review: the effects of growth hormone on athletic performance.. Annals of Internal Medicine, 148(10), 747-758.
Sideline Raging Soccer Moms (and Dads!)
From: Sideline Raging Soccer Moms (and Dads!)
Sports Are 80 Percent MentalVisit any youth soccer field, baseball diamond, basketball court or football field and you will likely see them: parents behaving badly. Take a look at this Good Morning America report:
These
are the extremes, but at most games, you can find at least one adult
making comments at the referee, shouting at their child, or having a
verbal exchange with another parent. Thankfully, these parents
represent only a small percentage of those attending the game. Does
that mean the others don't become upset at something during the game?
Usually not, as there are lots of opportunities to dispute a bad call
or observe rough play or react to one of these loud parents. The
difference is in our basic personality psyche, according to Jay Goldstein, a kinesiology doctoral student at the University of Maryland School of Public Health. His thesis, recently published in the Journal of Applied Social Psychology
(see reference below), hypothesized that a parent with
"control-oriented" personality would react to events at a game more
than a parent with an "autonomy-oriented" personality.
According to Goldstein, defending our ego
is what usually gets us in trouble when we feel insulted or take
something personally. At youth sports games, we transfer this pride to
our kids, so if someone threatens their success on the field, we often
take it personally. The control-oriented parent is more likely to
react with a verbal or sometimes physical response, while an
autonomy-oriented parent is better able to internalize and maintain
their emotions. This "control" vs. "autonomy" comparison has also been
seen in research on "road rage", when drivers react violently to
another driver's actions.
Goldstein and his team focused their
research on suburban Washington soccer parents back in 2004. They
designed a survey for parents to fill out prior to watching a youth
soccer game that would help categorize them as control or
autonomy-oriented. Immediately after the game ended, another survey
was given to the parents that asked about any incidents during the game
that made them angry on a scale of 1, slightly angry, to 7, furious.
They were also asked what action they took when they were angry.
Choices included "did nothing" to more aggressive acts like walking
towards the field and/or yelling or confronting either the referee,
their own child, or another player/parent. 53% of the 340 parents
surveyed reported getting angry at something during the game, while
about 40% reported doing something about their anger.
There was a direct and significant
correlation between control-oriented parents, as identified in the
pre-game survey, and the level of angry actions they took during the
game. Autonomy-oriented parents still got mad, but reported less
aggressive reactions. As Goldstein notes, “Regardless of their
personality type, all parents were susceptible to becoming more
aggressive as a result of viewing actions on the field as affronts to
them or their kids. However, that being said, it took
autonomy-oriented parents longer to get there as compared to the
control-oriented parents.”
So, now that we know the rather obvious
conclusion that parents who yell at other motorists are also likely to
yell at referees, what can we do about it? Goldstein sees this study
as a first step. He hopes to study a wider cross-section of sports and
socio-economic populations. Many youth sports organizations require
parents to sign a pre-season "reminder" code of conduct, but those are
often forgotten in the heat of the battle on the field. Maybe by
offering the same type of personality survey prior to the season, the
"control-oriented" parents can be offered resources to help them manage
their tempers and reactions during a game. Since referees were the
number one source of frustration reported by parents, two solutions are
being explored by many organizations; more thorough referee training
and quality control while also better training of parents on the rules
of the game which often cause the confusion.
Sports contests will always be emotional, from kids' games all the way up to professionals. Keeping the games in perspective and our reactions positive are tough things to do but when it comes to our kids, it is required.
Goldstein, J.D., Iso-Ahola, S.E. (2008). Determinants of Parents' Sideline-Rage Emotions and Behaviors at Youth Soccer Games. Journal of Applied Social Psychology, 38(6), 1442-1462. DOI: 10.1111/j.1559-1816.2008.00355.x
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 + ˝*BLK + ˝*AST – FGA – ˝*FTA – TO – ˝*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.
Play Better Golf By Playing Bigger Holes
From: Play Better Golf By Playing Bigger Holes
Sports Are 80 Percent Mental
Here are some quotes we have all heard (or said ourselves) on the golf course or at the ball diamond.
On a good day:
"It was like putting into the Grand Canyon"
"The baseball looked like a beach ball up there today"
On a bad day:
"The hole was as small as a thimble"
"I don't know, it looked like he was throwing marbles"
The baseball and the golf hole are the same size every day, so are these comments meaningless or do we really perceive these objects differently depending on the day's performance? And, does our performance influence our perception or does our perception help our performance?
Jessica Witt, an assistant professor of psychological science at the University of Virginia has made two attempts at the answer. First, in a 2005 study, "See the Ball, Hit the Ball", her team studied softball players by designing an experiment that tried to correlate perceived softball size to performance. She interviewed players immediately after a game and asked them to estimate the size of the softball by picking a circle off of a board that contained several different sizes. She then found out how that player had done at the plate that day. As expected, the players that were hitting well chose the larger sized circles to represent the ball size, while the underperforming hitters chose the smaller circles. The team was not able to answer the question of causality, so they expanded the research to other sports.
Fast forward to July, 2008 and Witt and her team have just released a very similar study focused on golf, "Putting to a bigger hole: Golf performance relates to perceived size". Using the same experiment format, players who had just finished a round of golf were asked to pick out the perceived size of the hole from a collection of holes that varied in diameter by a few centimeters. Once again, the players who had scored well that day picked the larger holes and vice versa for that day's hackers. So, the team came to the same conclusion that there is some relationship between perception and performance, but could not figure out the direction of the effect. Ideally, a player could "imagine" a larger hole and then play better because of that visual cue.
Researchers at Vanderbilt University may have the answer. In a study, "The Functional Impact of Mental Imagery on Conscious Perception", the team led by Joel Pearson, wanted to see what influence our "Mind's Eye" has on our actual perception. In their experiment, they asked volunteers to imagine simple patterns of vertical or horizontal stripes. Then, they showed each person a pattern of green horizontal stripes in one eye and red vertical stripes in the other eye. This would induce what is known as the "binocular rivalry" condition where each image would fight for control of perception and would appear to alternate from one to the other. In this experiment, however, the subjects reported seeing the image they had first imagined more often. So, if they had imagined vertical stripes originally, they would report seeing the red vertical stripes predominantly.
The team concluded that mental imagery does have an influence over what is later seen. They also believe that the brain actually processes imagined mental images the same way it handles actual scenes. "More recently, with advances in human brain imaging, we now know that when you imagine something parts of the visual brain do light up and you see activity there," Pearson says. "So there's more and more evidence suggesting that there is a huge overlap between mental imagery and seeing the same thing. Our work shows that not only are imagery and vision related, but imagery directly influences what we see."
So, back to our sports example, if we were able to imagine a large golf hole or a huge baseball, this might affect our actual perception of the real thing and increase our performance. This link has not been tested, but its a step in the right direction. Another open question is the effect that our emotions and confidence have on our perceived task. That hole may look like the Grand Canyon, but the sand trap might look like the Sahara Desert!
Witt, J.K. (2008). Putting to a bigger hole: golf performance relates to perceived size. Psychonomic Bulletin & Review, 15(3), 581-585.
Brains Over Brawn In Sports
From: Brains Over Brawn In Sports
Sports Are 80 Percent MentalSometimes, during my daily browsing of the Web for news and interesting angles on the sport science world, I get lucky and hit a home run. I stumbled on this great May 2007 Wired article by Jennifer Kahn, Wayne Gretzky-Style 'Field Sense' May Be Teachable. It ties together the people and themes of my last three posts, focusing on the concept of perception in sports.
Wayne
Gretzky is often held up as the ultimate example of an athlete with
average physical stature, who used his cognitive and perceptual skills
to beat opponents. Joining Gretzky in the "brains over brawn" Hall of
Fame would be pitcher Greg Maddux, NBA guard Steve Nash and quarterback
Joe Montana. They were all told as teenagers that they didn't have the
size to succeed in college or the pros, but they countered this by
becoming master students of the game, constantly searching for visual
cues that would give them the advantage of a fraction of second or the
element of surprise.
Kahn's story focuses on two sport scientists that we have met before. Peter Vint, sport technologist with the US Olympic team, who I highlighted in the post, Winning Olympic Gold With Sport Science, comments on this, "In any sport, you come across these players. They're not always the most physically talented, but they're by far the best. The way they see things that nobody else sees — it can seem almost supernatural. But I'm a scientist, so I want to know how the magic works." So, Vint and his team continue to search not only for the secret to the magic, but how it can be taught.
Vint acknowledges the work of one of his fellow sport scientists, Damian Farrow, of the Australian Institute for Sport, who was part of the discussion roundtable mentioned in my post, Getting Sport Science Out Of The Lab And Onto The Field.
He is also fascinated with the
perceptual abilities of elite athletes. In his own sport, tennis, he
wanted to know how expert players could return serves much better than
novice players. Similar to the research we looked at in an earlier
post about tennis, Federer and Nadal Can See the Difference,
Farrow designed an experiment that would try to identify the cues that
players might need to instinctively estimate the speed and direction of
a serve. He had three groups of players, expert, non-expert but
coached, and non-expert/non-coaced novices, wear ear plugs to block out
the sound of the ball hitting the racquet as well as occlusion glasses
that could block vision with the touch of an assistant's button. By
changing the point of the serve at which the glasses would go black,
and the players would be "blind", he could try to isolate the action of
the server that the expert players might be tuned into that the novices
were not. The decisive point was immediately before impact between the
racquet and the ball. Arm and racquet position at that point seemed to
let the expert players estimate the direction of the serve more
accurately than the novices.
But Vint and Farrow are not satisfied just knowing what an expert knows. They want to understand how to teach this skill to novices. From his own competitive tennis playing days, Farrow remembers that if he consciously focused his mind on things like arm position, racquet angle, etc., he would be miss the serve as his reaction time would drop. He understood that players need to not only learn the cues, but learn them to the point of "automaticity" through implicit learning. You may remember our discussion of implicit learning from the post, Teaching Tactics and Techniques in Sports. Malcolm Gladwell, in his best-selling book, Blink, calls this implicit decision-making ability "thin slicing" and gives examples of how we can often make better decisions in the "blink" of an eye, rather than through long analysis. Obviously, in sports, when only seconds or sub-seconds are allowed for decisions, this blink must be so well-trained that it is at the sub-conscious level.
For Vint and Farrow, the experiments continue, looking at each sport, but beyond the raw physical and technical skills that need to be taught but often times are the only skills that are taught. Understanding the cognitive side of the game will provide the edge when all else is equal.
Getting Sport Science Out Of The Lab And Onto The Field
From:Getting Sport Science Out Of The Lab And Onto The Field
Sports Are 80 Percent Mental
You are a coach, trying to juggle practice plans, meetings, game prep and player issues while trying to stay focused on the season's goals. At the end of another long day, you see this in your inbox:
MEMO
To: All Head Coaches
From: Athletic Director
Subject: Monthly Reading List to Keep Up with Current Sport Science Research
- Neuromuscular Activation of Triceps Surae Using Muscle Functional MRI and EMG
- Positive effects of intermittent hypoxia (live high:train low) on exercise performance are not mediated primarily by augmented red cell volume
- Physiologic Left Ventricular Cavity Dilatation in Elite Athletes
- The Relationships of Perceived Motivational Climate to Cohesion and Collective Efficacy in Elite Female Teams
Just some light reading before bedtime... This is an obvious exaggeration (and weak attempt at humor) of the gap between sport science researchers and practitioners. While those are actual research paper titles from the last few years under the heading of "sport science", the intended audience was most likely not coaches or athletes, but rather fellow academic peers. The real question is whether the important conclusions and knowledge captured in all of this research is ever actually used to improve athletic performance? How can a coach or athlete understand, combine and transfer this information into their game?
David Bishop of the Faculty of Exercise and Sport Science at the University of Verona has been looking at this issue for several years. It started with a roundtable discussion he had at the 2006 Congress of the Australian Association for Exercise and Sports Science with several academic sport scientists (see: Sports-Science Roundtable: Does Sports-Science Research Influence Practice? ) He asked very direct questions regarding the definition of sport science and whether the research always needs to be "applied" versus establishing a "basic" foundation. The most intriguing question was whether there already is ample research that could be applied that needs a good translator/professional to interpret for and communicate to the potential users - coaches and athletes. The panel agreed that was the missing piece, as most academic researchers just don't have the time to deliver all of their findings directly to the field.
In a follow-up to this discussion, Bishop recently published his proposed solution titled, "An Applied Research Model for the Sport Sciences" in Sports Medicine (see citation below). In it, he calls for a new framework for researchers to follow when designing their studies so that there is always a focus on how the results will directly improve athletic performance. He calls for a greater partnership role between researchers and coaches to map out a useful agenda of real world problems to examine. He admits that this model, if implemented, will only help increase the potential for applied sport science. The "middleman" practitioner role is still needed to bring this information to the front lines of sports.
The solution for this "gathering place" community seems perfect for Web 2.0 technology. One specific example is this online community, iStadia.com. Keith Irving and Rob Robson, two practicing sport science consultants, created this site two years ago to fill this gap. Today, with over 600 members, iStadia is approaching the type of critical mass that will be necessary to bring all of the stakeholders together. Of course, as with any online community, the conversations there are only as good as the participants want to make it. But, with the pressure on coaches to win and the desire of sport scientists to produce relevant knowledge, there is motivation to make the connection.
Another trend favoring more public awareness of sport science is the recent surge in media attention, especially related to the upcoming Beijing Olympics. In an earlier post, Winning Olympic Gold With Sport Science, I highlighted a feature article from USA Today. This month's Fast Company also picks up on this theme with their cover article, Innovation of Olympic Proportions, describing several high-tech equipment innovations that will be used at the Games. Each article mentions the evolving trust and acceptance of sport science research by coaches and athletes. When they see actual products, techniques and, most importantly, results come from the research, they cannot deny its value.
Bishop, D. (2008). An Applied Research Model for the Sport Sciences. Sports Medicine, 38(3), 253-263.
Teaching Tactics and Techniques in Sports
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
