question: How do sports scientists collect data about what a player does in a game?
comment: The overwhelming majority of it is people simply watching the game and writing all the stuff down. Of course, nowadays computers make it much, much easier to actually sort through all that data and come up with all these weird statistics.
passages: Section::::Commonly used techniques.:Self-talk.
   In 2009 the Chicago Blackhawks turned to an outside company to produce analytical assessments for them. Subsequently the Blackhawks have achieved unparalleled success in the NHL, winning three Stanley Cups in six seasons. With this success has come a number of difficult decisions for Blackhawks management as they are often only able to hang onto a core group of players following each cup run, while other key players receive offers that the Blackhawks simply cannot match under the NHL's salary cap. However, by using this analytics based system, the team has continuously been able to fill these gaps by finding players who are undervalued by other teams but will fit well with the Blackhawks' style of play. This process has been refined by the Blackhawks who provide yet another example of the longevity that can be associated with analytic base decision making.
   In the early stages of this area statistics on biomechanical data, like different kinds of forces or rates, played a major role. Scientists started to analyze sports games by collecting and looking at such values and features in order to interpret them. Later on, with the continuous improvement of computer hardware - in particular microprocessor speed – many new scientific and computing paradigms were introduced, which were also integrated in computer science in sport. Specific examples are modeling as well as simulation, but also pattern recognition, design, and (sports) data mining.
   Section::::Commonly used techniques.:Biofeedback.
  
  Biofeedback uses external technology to measure and make an individual aware of internal physiological processes. There is some evidence that physiological measures, such as heart rate or brain waves, appear to be different in elite athletes than that of the typical person. This is a field that should be further looked into; however, it could have beneficial implications for athletes to be able to monitor and control these physiological measures to maximize performance.
  
  Section::::Commonly used techniques.:Modeling.
   3. To provide a useful function of the player's contributions to his team. When analyzing data, one is able to understand the contributions a player makes to the success/failure of his team. Given that correlation, we can sign or release players with certain characteristics.
  
  Section::::Applications.:Machine learning for predicting game outcome.
   In 1979, Rainer Martens published an article entitled ""About Smocks and Jocks"", in which he contended that it was difficult to apply specific laboratory research to sporting situations. For instance, how can the pressure of shooting a foul shot in front of 12,000 screaming fans be duplicated in the lab? Martens contended: "I have grave doubts that isolated psychological studies which manipulate a few variables, attempting to uncover the effects of X on Y, can be cumulative to form a coherent picture of human behavior. I sense that the elegant control achieved in laboratory research is such that all meaning is drained from the experimental situation. The external validity of laboratory studies is at best limited to predicting behavior in other laboratories." Martens urged researchers to get out of the laboratory and onto the field to meet athletes and coaches on their own turf. Martens' article spurred an increased interest in qualitative research methods in sport psychology, such as the seminal article "Mental Links to Excellence."
   Section::::History.
   Based on the fields from above, the main areas of research in computer science in sport include amongst others:
  
  BULLET::::- Training and coaching
  
  BULLET::::- Biomechanics
  
  BULLET::::- Sports equipment and technology
  
  BULLET::::- Computer-aided applications (software, hardware) in sports
  
  BULLET::::- Ubiquitous computing in sports
  
  BULLET::::- Multimedia and Internet
  
  BULLET::::- Documentation
  
  BULLET::::- Education
  
  Section::::Research communities.
   As another result of this development, the term 'computer science in sport' has been added in the encyclopedia of sports science in 2004.
  
  Section::::Areas of research.
  
  The importance and strong influence of computer science as an interdisciplinary partner for sport and sport science is mainly proven by the research activities in computer science in sport. The following IT concepts are thereby of particular interest:
  
  BULLET::::- Data acquisition and data processing
  
  BULLET::::- Databases and expert systems
  
  BULLET::::- Modelling (mathematical, IT based, biomechanical, physiological)
  
  BULLET::::- Simulation (interactive, animation etc.)
  
  BULLET::::- Presentation
   The biggest contribution to the team level metrics came from Arizona State University researchers led by Jennifer H. Fewell. Using 2010 NBA first round playoff data, they constructed the networks for each team using players as nodes and ball movement between them as links. They distinguish the trade-off between not necessarily mutually exclusive division of labor and team`s unpredictability that are measured by Uphill downhill flux and Team entropy respectively.
   Additionally, there are specific psychological skills that are ingrained in personality that are possessed at higher levels in elite athletes than the typical person. These include arousal regulation, goal setting, imagery, pre-performance routines, and self-talk, which are discussed further under Commonly used techniques.
   As technology has advanced over the last number of years data collection has become more in-depth and can be conducted with relative ease. Advancements in data collection have allowed for sports analytics to grow as well, leading to the development of advanced statistics as well sport specific technologies that allow for things like game simulations to be conducted by teams prior to play, improve fan acquisition and marketing strategies, and even understand the impact of sponsorship on each team as well as its fans.
   The Astros rely heavily on analytics when making decisions. The team has employees with titles like, director of decision sciences, medical risk manager and mathematic modeler. Unlike other professional teams who typically use analytics solely for player transactions and signings, the Astros have begun to use analytics to make decisions on how they will play on the field, "applying the defensive shift more than any other team in the MLB last season." Using this approach, the Houston Astros captured their first World Series victory in franchise history in 2017.
  
  Section::::Notable applications.:San Antonio Spurs (NBA).
   In sport, systems have been developed to provide a high level of task, performance and physiological data to coaches, teams and players. The objective is to improve individual and team performance and/or analyse opposition patterns of play to give tactical advantage. The repetitive and patterned nature of sports games lends itself to video analysis in that over a period of time real patterns, trends or habits can be discerned.
   A more complete explanation of possession-based analysis is available in "A Starting Point for Analyzing Basketball Statistics" in the Journal of Quantitative Analysis in Sports.
  
  Section::::History.
   The most recent project that the AFS has embarked upon is the Football Genome Project - the compilation of every football match played in professional football ever. Much of this work has been completed, with UK data going back to the first games in the 1800s through to the present day.
   BULLET::::- 2017 – John Maxymuk
  
  BULLET::::- 2016 – Mark L. Ford
  
  BULLET::::- 2015 – Jack Clary
  
  BULLET::::- 2014 – Pete Fierle
  
  BULLET::::- 2013 – Cliff Christl
  
  BULLET::::- 2012 – Chris Willis
  
  BULLET::::- 2011 – Ken Crippen
  
  BULLET::::- 2010 – Pete Palmer
  
  BULLET::::- 2009 – Bob Carroll
  
  BULLET::::- 2008 – Ralph Hickok
  
  BULLET::::- 2007 – Vince Popo
  
  BULLET::::- 2006 – Emil Klosinski
  
  BULLET::::- 2005 – John Gunn
  
  BULLET::::- 2004 – Jeffrey J. Miller
  
  BULLET::::- 2003 – John Hogrogian
  
  BULLET::::- 2002 – Ken Pullis
  
  BULLET::::- 2001 – Tod Maher
  
  BULLET::::- 2000 – Mel "Buck" Bashore
  
  BULLET::::- 1999 – Stan Grosshandler
   Section::::Common areas of study.:Evolutionary perspectives.
   Section::::Common areas of study.
  
  Listed below are broad areas of research in the field. This is not a complete list of all topics, but rather, an overview of the types of issues and concepts sport psychologists study. Recently, criticism of the quality, assumptions, and methods of sport psychology stress research has drawn increasing attention, and a flourishing academic debate has evolved regarding the quality of sport research its limitations and future directions.
  
  Section::::Common areas of study.:Personality.
   Section::::History.:Coleman Griffith: "America's first sport psychologist".
   Beginning in the 1990s, Dean Oliver began to popularize the use of possession statistics. Oliver and John Hollinger are credited with moving this use of basketball statistics into the view of more basketball fans through their websites in the late 1990s. Oliver published his book "Basketball On Paper" in 2003, while Hollinger began writing the "Pro Basketball Forecast" series in 2002.
   The Lead Engineer throughout the "Sport Science" series has been Dr. Cynthia Bir, Professor of Biomedical Engineering at Wayne State University in Detroit, Michigan. Using methods that have been developed to understand human injury biomechanics, and developing new techniques to address the unique challenges found when studying live volunteers in high impact and high speed activities, Dr. Bir helps viewers to understand the forces (internal and external) sustained and generated by the body during high level athletic activities.
   Section::::Commonly used techniques.
  
  Below are some of the more common techniques or skills sport psychologists teach to athletes for improving their performance.
  
  Section::::Commonly used techniques.:Arousal regulation.
   One common area of study within sport psychology is the relationship between personality and performance. This research focuses on specific personality characteristics and how they are related to performance or other psychological variables.
   Section::::Commonly used techniques.:Goal setting.
  
raw_presuppositions: Sports Scientists collect the data from a game.
raw_corrections: They do this but computers also help them collect it. 