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Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
Talent Development, Performance Potential and Computer Support in Sports
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Talent Development, Performance Potential and Computer Support in Sports

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A paper presented at IACSS09

A paper presented at IACSS09

Published in: Sports, Business
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  • 1. Mathematics and Sports: an Optimal Line Up Prof.dr. Gerard Sierksma University of Groningen ORTEC-TeamSupportSystems August, 2009
  • 2.
          • Intro Filmpje
  • 3. Comparing Athlete’s Performances the influence of technology
  • 4. Athletic performance + technological progress
  • 5. Tight fit clothing Indoor rinks Klapskate Artificial ice rinks Progress of the World Records
  • 6. From absolute times to time differences - Times decrease -Differences become smaller
  • 7.
    • The Competition Crisis
    • The mutual differences between athlete`s performances
    • become smaller and smaller .
    • Sometimes the differences are not measurable anymore:
    • they are within the error margins.
    • Some examples:
      • Was the fifth gold medal of Michael Phelps in China indeed gold?
      • If Simon Kuipers and Shani Davis would have skated in different pairs, then nobody would have ‘seen’ that Kuipers was the actual winner;
      • What happens exactly when skating times are permanently adjusted after the race??
      • Will the Olympic 1000m get the right gold medal winner???
  • 8. Davis Kuipers
  • 9.
    • Talent Tracking
    • Performance Potential Development
    • PerPot Tracking
    • and
    • Line up Formation
    • Computer Support
  • 10.
    • Two types of qualities/competencies:
    • Objectively measurable ( tangible ), e.g.,
      • VO2 max
      • Body-mass index
      • Fat percentage
      • Et cetera
    • Subjectively measurable ( intangible ), e.g.,
    • - Stress resistency
    • - Leadership
    • - Et cetera
  • 11.
    • For each attribute
    • target scores
    • per discipline need to be determined.
      • The estimation of the ‘target scores’ is carried out with real data and regression analysis .
  • 12. Fit score of an athlete w.r.t. an attribute is a number that expresses the relationship between that attribute and the expected/target.
  • 13. COACH & SCOUT ASSISTANT Collecting and analyzing data concerning development of skills and competences of individual players with respect to the team. PerPot graphs Line up
  • 14. DEMO CSA Pro
  • 15.
    • Subjectivity of the scores
    • Differences of Opinion:
    • Relevant or Irrelevant?
  • 16. KNSB Olympic Selection System
  • 17.
    • Which speed skaters (women/men) will represent the Netherlands at the Olympic Winter Games in 2010?
  • 18. Objective
    • Maximize the number of (gold?) medals.
  • 19. Model S1 S2 S3 Si 500m (4) 1000m (4) 1500m (4) 5000m (3) 10000m (3) Probability of winning … Skaters Disciplines
  • 20. Model data
    • Parameters
    • C ij = prob. of winning … of skater i on distance j.
    • Decision variables:
    • X ij = 1 skater i starts on distance j;
    • 0 else.
    • Z i = 1 skater i is selected;
    • 0 else.
  • 21. Integer Linear Programming Model
  • 22.
    • Effectivity in Action
    • measuring during the contest
    • on-line computer support
  • 23. Effectivity in Action
    • How can we determine the effectiveness of a player and the team?
    • What do we mean by effectiveness?
    • How to measure?
    • What is the purpose and the objective?
  • 24. Effectivity in Action
    • The effectiveness of an action of a player
    • is the rate at which
    • - the player enables a teammate to make a scoring- oriented next action, and
    • - an opponent player is prevented from making a scoring- oriented action.
  • 25. Soccer
    • The objective is scoring and preventing the opponent from scoring.
    • Action on the ball are crucial!
    • What about off-the-ball actions?
    • They are less important compared e.g. with Amer. Football.
  • 26.
    • The system
    • Effectivity in Action
    • collects and valuates all ‘ around-the-ball ’ actions.
    • The result is a graph that depicts real time the course of the effectiveness.
  • 27.  
  • 28.  
  • 29.  
  • 30.  
  • 31.  
  • 32.
    • Effectivity in Action
    • The Robben wissel
  • 33. Netherlands – England August 12, 2009
  • 34.  
  • 35.  
  • 36.  
  • 37.  
  • 38. Duitsland – Nederland 2-1 1974
  • 39. 1 2 3 4 5 6
  • 40.  
  • 41. Intuition is the engine of creativity It puts the ‘nose in the right direction’ for motivating the team players; knowing how far a team player can improve on his/her qualities; finding the right new team player.
  • 42.
    • University of Groningen, The Netherlands
    • Ruud Koning, prof. of sport economics
    • Elmer Sterker, prof. of economics, performance analysis
    • Gerard Kuper, assoc. prof. econometrics , return on investment
    • Koen Lemmink, assoc. prof., movement studies
    • Gerard Sierksma, prof., quantitative logistics and sports
    • Special programs for top sport students.
  • 43.
    • Be Quick filmpje
  • 44. What is the objective? - short - long - cheap - fast
  • 45. Laserstraal boort elke 15 sec. 3036 gaatjes in computerprintplaatjes. Probleem: Wat is de snelste route? Optimale oplossing onbekend!
  • 46. Elke dag vliegen helicopters naar de 51 boorplatforms op de Noordzee om werknemers te vervangen. Probleem: Minimaliseer het aantal te vliegen zeemijlen. Optimale oplossing niet bekend!
  • 47. … .. how many tours are there? Locations Tours 3 1 4 3 5 12 6 60 7 360 8 2520 9 20160 10 181440 11 1814400 12 19958400 13 239500800 20 60822550204416000 50 30414093201713378043612608166064768844377641568960512000000000000 ….. a lot!
  • 48. Practical problems cannot wait for scientist to find the solution.
  • 49. When is a problem hard and when is it easy ? ‘ Paradox’: Very difficult decision problems are ‘ easy’ to solve!! Complexity Theory
  • 50.
    • What has this all to do with team composition?
  • 51. Coach & Scout Assistant
    • Coach & Scout Assistant selects an optimal team of players from a large selection.
    • The number of possibilities to choose a line-up of 11 persons from a group of, say, 26 players is 308,403,583,488,000 big number!
    • Each choice has a certain (team-)value.
    • The “eleven” with the highest team value is the optimal team.
    • ………………………………………… ..……… How to find?
  • 52. Gasunie N.V. Nederland
    • Multiple Team Problem :
    • Design a (given) number of teams, where the team
    • members are selected from one group of
    • persons (applicants), with team values
    • as close as possible to given target values.
    • Multi-objective optimization : minimize the
    • deviations from the team targets.
  • 53. Last minute changes If a player is not mentally fit, then the coach changes its score on ‘mental fitness’ to a lower number. Within seconds Coach & Scout Assistant presents the new line-up together with the loss in the team score.
  • 54.  
  • 55.  
  • 56.  
  • 57. More difficult problems
    • e.g. heptathlon and decathlon training schedules
  • 58.
    • Three main functionalities:
    • Talent Track System:development of each player on all positions;
    • Scouting: surplus/financial value, and best position of scouted players;
    • Line up: optimal team composition.
  • 59. Further applications : Volleyball Hockey Rowers-8 Amer. Football Speed skating Decathlon Management teams
  • 60. Coach & Scout Assistant - Screenshots
  • 61.  
  • 62.  
  • 63.  
  • 64. Gould’s Hypothesis 1986
    • Due to an increase of the maturity of the sport over time, athletes will perform ‘better’ and the variance between the performances will decrease.
  • 65.  
  • 66. Best Skaters All Times, man Name Country Score Best four years 1 Eric Heiden USA -0.25 1979 1978 1980 1977 2 Ard Schenk NED -0.24 1972 1973 1971 1967 3 Johann Olav Koss NOR -0.19 1994 1991 1993 1990 4 Oscar Mathisen NOR -0.15 1912 1914 1908 1913 5 Gianni Romme NED -0.14 1998 2000 2003 2002 6 Jaap Eden NED -0.11 1896 1895 1893 1894 7 Hjalmar Andersen NOR -0.11 1951 1952 1950 1954 8 Ivar Ballangrud NOR -0.08 1936 1926 1930 1929 9 Rintje Ritsma NED -0.05 1995 1998 1996 1993 10 Clas Thunberg FIN -0.04 1925 1924 1929 1931
  • 67. Best Skaters All Times, woman Name Country Score Best four years 1 Gunda Niemann GER -0.46 1995 1991 1996 1998 2 Karin Enke GDR -0.41 1986 1987 1984 1980 3 Andrea Mitscherlich GDR -0.24 1985 1984 1987 1983 4 Lidia Skoblikova URS -0.16 1963 1964 1960 1962 5 Claudia Pechstein GER -0.12 2000 1998 1994 2001 6 Anni Friesinger GER -0.10 2005 2004 2001 2002 7 Stien Kaiser NED -0.08 1967 1972 1971 1965 8 Inga Artamonova URS -0.08 1965 1958 1962 1957 9 Cindy Klassen CAN -0.06 2006 2005 2003 2001 10 Natalya Petrusyova URS -0.04 1981 1982 1980 1979
  • 68.  
  • 69. Tournametsooien
    • Prestaties op de volgende toernooien zijn momenteel bepalend:
    • Internationale toernooien;
    • Nationale toernooien;
    • Nationale selectie/skate-offwedstrijden.
  • 70. Bepalen van de winkans
    • Resultaten internationale toernooien.
    • Statistische analyse, waarmee de kans bepaald wordt dat een schaatser bij de beste 3 zit. (of bij de beste 4, 5, 6, …)
    • Deze analyse is gebaseerd op onderlinge verschillen in de gereden schaatstijden.
  • 71. TURIJN 2006 Olympische Spelen
    • Wedstrijden vanaf WChSD 2005
    • OKT ook meegenomen
  • 72. Olympische Schaatploeg Turijn 2006 KNSB Selectie /////////////////////////////////////////////////////////// Erben Wennemars Carl Verheijen Simon Kuipers Stephan Groothuis Simon Kuipers Sven Kramer Beorn Nijenhuis Bob de Jong Jan Bos 10k 5k 1500m 1000m 500m DSSselectie Beorn Nijenhuis ///////////////////////////////////////////////////////////// Erben Wennemars Carl Verheijen Mark Tuitert Stephan Groothuis Simon Kuipers Sven Kramer Gerard v Velde Bob de Jong Jan Bos 10k 5k 1500m 1000m 500m
  • 73.
    • Globally there are two types of attributes:
    • “ The more, the better”,
    • and “The less the worse”;
      • “ The more deviating from the target score, the worse”.
  • 74. PerPot graph of athlete i on the 500m supply demand PerPot scores
  • 75.
    • General problem:
      • What is the relationship between
      • the performance of an individual athlete
      • and
      • the performance of (groups of) athletes from the same discipline?
      • Team and time (rankings),
  • 76. Wiskundige aanpak
    • Maximaliseren van
    • de winkans op goud, of
    • de winkans op medailles, of
    • nog iets anders,
    • op basis van behaalde resultaten.
    • Wij hebben voorlopig gekozen voor ‘de winkans op medailles’.

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