7. Handball_We Are Invincible

Handball — We Are Invincible Volume 1, Issue 7 Supervising teachers: Alexandros Markoulakis 2nd General Lyceum Eugenia Potiriadou of Kamatero The e-Twinning Group: SPORT SCIENCE STORIES 2017—18 1

Contents Volume 1, Issue 7 Alexandros Markoulakis Supervising teachers: 2nd General Lyceum Eugenia Potiriadou of Kamatero Inside this issue: Front Cover 1 Contents 2 The 2nd place 3 Our video 5 Worksheet 6 Objectives and Outcomes 7 The Handball Goal 8 The Single Penalty 9 How the penalty shoot-out can be optimised 21 Physical Science Research 29 Sport Science Stories 34 Photos 37 Back Cover 48 2

The 2nd place Volume 1, Issue 7 Alexandros Markoulakis Supervising teachers: 2nd General Lyceum Eugenia Potiriadou of Kamatero Panhellenic School Games of Handball 2017– 18 The handball team of our school boys won the 2nd place in the Panhellenic School Games of Handball. The final took place on February 19th at the Olympic Athletic Center of Athens against the school boys’ team of Pylea. The match ended in a draw and the penalty shootings yielded in a difference of three goals [score: 26—23]. 3

The 2nd place Volume 1, Issue 7 Alexandros Markoulakis Supervising teachers: 2nd General Lyceum Eugenia Potiriadou of Kamatero Panhellenic School Games of Handball 2017– 18 4

Our video Volume 1, Issue 7 THE INTERVIEW 2nd General Lyceum of Kamatero https://youtu.be/iQnoi5r6Hvg YOU TUBE Our video 5

Worksheet Volume 1, Issue 7 Supervising teachers: Alexandros Markoulakis Eugenia Potiriadou What You Do 1. Find on Internet the handball 7. Shoot 10 or 20 at an empty goal dimensions (width, height). goal and calculate the accuracy of your shots. Assign percent- ages for each forth part of the 2. Find the surface area of the goal- handball goal. keeper’s (student’s) body. The problem we 3. Compare the area covered by the 8. Calculate the are going to solve student with the area of the hand-  goalkeeper’s reaction time is: Ηow high the ball goal. This yields the probability  the time the ball travels of the goalkeeper preventing a goal. probability of a and successful penalty 4. Then, we divide the goal into two  the time of the goalkeeper’s shot is (taking into halves and calculate the probability motion. account all of the of preventing the ball from going in internal and one half of the goal, using the same 9. From these calculations de- external influences method as above. cide whether the goalkeeper i.e. geometry, catches the ball. What must the reaction time, 5. This can also be calculated again, goalkeeper do? What is the role choice of side)? after dividing the goal into fourths. of his decision? 6. Make an hypothesis regarding 10. Compare your last con- the problem: Where are the best clusion regarding the handball spots to aim the shot? with the football case. 6

Objectives and Outcomes Volume 1, Issue 7 2nd General Lyceum of Kamatero 1. The students will be able to calculate the probability of a successful penalty shot, taking into account all of the internal and external influences (i.e. geometry, reaction time, choice of side). 2. The students learn how the penalty shoot-out for a team can be optimised. 3. The students must also find the perfect line-up for a penalty shoot-out as well as a “fair” alternative to it. 7

The Handball Goal Volume 1, Issue 7 The Dimensions 2nd General Lyceum of Kamatero Subtitle Text During the data Some more assumptions: analysis we will use the 1. We assume that the time reaction of a goalkeeper is equal to detailed dimensions of a handball goal. So, 171 ms or 0.171 s, the result we reached during the previous regarding the length project “Uncovering Your Reaction Time”. and the height of the goal we have: 2. We assume that the ball speed is 100 km/h. 3. An athlete’s (e.g. goalkeeper) average speed when jumping is l = 3 m approximately 16 km/h. h = 2 m 8

The Single Penalty Volume 1, Issue 7 2nd General Lyceum of Kamatero STUDING PROBABILITIES FOCUSING ON THE GOALKEEPER Instead of applying the dimensions of a professional goalkeeper, we calculated the surface area of a student’s body using the software Geogebra. We, then, compare the area covered by the student with the area of the handball goal. This yields the probability of the goalkeeper preventing the goal. 9

The Single Penalty Volume 1, Issue 7 2nd General Lyceum of Kamatero STUDING PROBABILITIES FOCUSING ON THE GOALKEEPER 10

The Single Penalty Volume 1, Issue 7 2nd General Lyceum of Kamatero STUDING PROBABILITIES FOCUSING ON THE GOALKEEPER ESTIMATING THE PROBABILITY OF THE GOALKEEPER PREVENTING THE GOAL ΔΙΑΔΙΚΑΣΙΑ ΕΥΡΕΣΗΣ ΤΗΣ ΠΙΘΑΝΟΤΗΤΑΣ ΑΠΟΤΡΟΠΗΣ ΤΟΥ ΓΚΟΛ Column1 Μήκος τέρματος l (m) 3 Ύψος τέρματος h (m) 2 Μήκος τέρματος l' (GeoGebra) 8.67 Ύψος τέρματος h' (GeoGebra) 5.82 Εμβαδόν τέρματος S' (GeoGebra) 50.46 Εμβαδόν τέρματος S (m²) 6.00 Κλίμακα, S'/S 8.41 Εμβαδόν τερματοφύλακα Sαθλ' (GeoGebra) 11.49 Εμβαδόν τερματοφύλακα Sαθλ (m²) 1.37 Πιθανότητα αποτροπής του γκολ Sαθλ'/Sαθλ 0.2277 Πιθανότητα αποτροπής του γκολ (%) 22.77 11

The Single Penalty Volume 1, Issue 7 2nd General Lyceum of Kamatero STUDING PROBABILITIES FOCUSING ON THE GOALKEEPER ESTIMATING THE PROBABILITY OF THE GOALKEEPER PREVENTING THE GOAL So, the probability of a goalkeeper preventing a goal is 22.77 %. Then, we divide the goal into two halves and calculate the probability of preventing the ball from going in one half of the goal, using the same method as above. This can also be calculated again, after dividing the goal into fourths. Εμβαδόν τέρματος S Εμβαδόν μισού τέρμα- Εμβαδόν 1/4 τέρματος Εμβαδόν αθλητή S αθλητή 2 2 2 2 (m ) τος S 1/2 (m ) S 1/4 (m ) (m ) 6.00 3.00 1.50 1.37 Πιθανότητα να αποτραπεί το γκολ (S αθλητή/S) *100% (S αθλητή/S 1/2) *100% (S αθλητή/S 1/4) *100% 22.77 % 45.54 % 91.08 % 12

The Single Penalty Volume 1, Issue 7 2nd General Lyceum of Kamatero STUDING PROBABILITIES FOCUSING ON THE GOALKEEPER ESTIMATING THE PROBABILITY OF THE GOALKEEPER PREVENTING THE GOAL So, the probability of a goalkeeper preventing a goal is 22.77 %. Then, we divide the goal into two halves and calculate the probability of preventing the ball from going in one half of the goal, using the same method as above. This can also be calculated again, after dividing the goal into fourths. Εμβαδόν τέρματος S Εμβαδόν μισού τέρμα- Εμβαδόν 1/4 τέρματος Εμβαδόν αθλητή S αθλητή 2 2 2 2 (m ) τος S 1/2 (m ) S 1/4 (m ) (m ) 6.00 3.00 1.50 1.37 Πιθανότητα να αποτραπεί το γκολ (S αθλητή/S) *100% (S αθλητή/S 1/2) *100% (S αθλητή/S 1/4) *100% 22.77 % 45.54 % 91.08 % 13

The Single Penalty Volume 1, Issue 7 2nd General Lyceum of Kamatero STUDING PROBABILITIES FOCUSING ON THE GOALKEEPER ESTIMATING THE PROBABILITY OF THE GOALKEEPER PREVENTING THE GOAL CONCLUSION 1: The probability of preventing the goal is significantly larger when the goalkeeper has decided which forth of the goal to dive toward. It is hard for the penalty taker to estimate probabilities, but in general it can be said that a left-handed penalty taker will aim better at the right corner, and a right-handed penalty taker at the left corner. We accumulated data by shooting 10, 20 or more times at an empty goal. CONCLUSION 2: As a general conclusion we can say that the most successful penalties were scored in the bottom corners. 14

The Single Penalty Volume 1, Issue 7 2nd General Lyceum of Kamatero THE PROBABILITY OF SCORING To find out how high the probability of scoring is, we need to divide the penalty shot into two independent motions:  those of the goalkeeper and  those of the penalty taker. The question: Where are the best spots to aim the shot? Hypothesis: The lower corners of the goal. We use geometry to calculate the distance to that point (the lower corner of the ball). The time the ball travels can be calculated (t = s/υ), with the assumption that the average velocity of the ball is 100 km/h. 15

The Single Penalty Volume 1, Issue 7 2nd General Lyceum of Kamatero THE PROBABILITY OF SCORING 16

The Single Penalty Volume 1, Issue 7 2nd General Lyceum of Kamatero THE PROBABILITY OF SCORING So, the distance the ball travels is γ = 7.36 m.  The time the ball travels: t = ball where υ = 100 km/h = 100∙ m/s => υ = 27.78 m/s So, t = = => t ball = 0.27 s ball The goalkeeper has that amount of time to react and jump into the corner. 17

The Single Penalty Volume 1, Issue 7 2nd General Lyceum of Kamatero THE PROBABILITY OF SCORING  Student’s reaction time , t reaction = We measure our own reaction time with a ruler that is dropped by one student and caught by a second student (see our 6th project, “Uncovering Your Time of Reaction”). Using the distance the ruler has travelled, the reaction time can be calculated as t reaction = 2 g: gravitational acceleration; g = 9.81m/s t: time [s] h: distance covered [m] We found: t reaction = 171 ms => t reaction = 0.17 s 18

The Single Penalty Volume 1, Issue 7 2nd General Lyceum of Kamatero THE PROBABILITY OF SCORING  The time the goalkeeper moves: t goalkeeper = where x = 1.5 m and an athlete’s average speed is approximately: v = 16 km/h = 16∙ m/s => v = 4.44 m/s So, t goalkeeper = = => t goalkeeper = 0.34 s But, t ball – t reaction = 0.27 s – 0.17 s = 0.1 s < 0.34 s = t goalkeeper which means that the time the goalkeeper has to catch the ball (0.1 s) is not enough. 19

The Single Penalty Volume 1, Issue 7 2nd General Lyceum of Kamatero THE PROBABILITY OF SCORING CONCLUSION 3: This yields the conclusion that the goalkeeper cannot allow for any reaction time and must choose which corner to dive toward before the penalty has been taken. 20

How the penalty shoot-out can be optimised Volume 1, Issue 7 2nd General Lyceum of Kamatero PENALTY SHOOT-OUT Penalty shoot-outs always take the same form. Five players from each team are nominated to take penalties in a fixed order. A coin is tossed to decide which team gets to choose which team should shoot first. The teams then take turns shooting a penalty. 21

How the penalty shoot-out can be optimised Volume 1, Issue 7 2nd General Lyceum of Kamatero THE APP WE USED 22

How the penalty shoot-out can be optimised Volume 1, Issue 7 2nd General Lyceum of Kamatero HANDBALL PLAYERS AVERAGE SCORING PROBABILITIES The students are given a list of players with their average scoring probabilities. They choose five of these players and determine the line- up in which they will shoot. Handball Players Statistics Games Shot rates Scoring s/n Player Goals Shots played (%) probability 1 Garli Martin 6 21 45 46.67 0.4667 2 Dragan Slijepcevic 6 20 26 76.92 0.7692 3 Gufler Hannes 3 7 13 53.85 0.5385 4 Gufler Michael 6 29 42 69.05 0.6905 5 Jonas Mathà 6 2 6 33.33 0.3333  Mean probability for scoring a goal: p = 23

How the penalty shoot-out can be optimised Volume 1, Issue 7 2nd General Lyceum of Kamatero MEAN PROBABILITY FOR SCORING A GOAL Since the mean probability for scoring a goal is p = (p + p + p + p + 4 3 1 2 p )/5 all of the line-ups are equal. 5 But in real-life handball, the pressure on each penalty taker rises as the penalty shoot-out progresses. This value can be set at about 5 %. This will lead to the following equation for the mean probability: p = So, the mean probability for scoring a goal, for a team having the above handball players, is: p = 51 % 24

How the penalty shoot-out can be optimised Volume 1, Issue 7 2nd General Lyceum of Kamatero MEAN PROBABILITY FOR SCORING A GOAL MEAN PROBABILITY FOR A TEAM SCORING A GOAL Scoring probabil- Pressure on Scoring probabil- s/n Player ity (Without pres- each penalty ity (In real life sure) taker (5%) handball) 1 Garli Martin 0.4667 0.4667 2 Dragan Slijepcevic 0.7692 0.05 0.7308 3 Gufler Hannes 0.5385 0.10 0.4846 4 Gufler Michael 0.6905 0.15 0.5869 5 Jonas Mathà 0.3333 0.20 0.2667 0.51 Mean probability for a team scoring a goal: 51% 25

How the penalty shoot-out can be optimised Volume 1, Issue 7 2nd General Lyceum of Kamatero A WAY TO OPTIMISE THE RESULT POSSIBLE LINE-UPS The students must figure out a There are way to optimise the result. It should be up to the students to find a solution to the problem, although having the weakest 5! = 5∙4 ∙3 ∙2 ∙1 = 120 penalty taker first and ascending to the strongest last is in fact the possible line-ups. If the team that shoots first scores a goal... The next variable that plays a role here is the psychological effect if the team that shoots first scores a goal. This situation puts even more pressure on the next penalty taker. 26

How the penalty shoot-out can be optimised Volume 1, Issue 7 2nd General Lyceum of Kamatero TWO TEAMS OF EQUAL STRENGTH The students are asked to make a research, asking the handball players to compare two teams of equal strength regarding the probability of winning the penalty shoot-out when the one begins. They conclude that the team that begins has a higher chance of winning the penalty shoot-out. 27

How the penalty shoot-out can be optimised Volume 1, Issue 7 2nd General Lyceum of Kamatero DEBATE: A FAIR RULE The students should finally have a debate to determine a fair rule for a penalty shoot-out: Are five shots enough to reach a satisfactory outcome? The fairest sequence for Teams A and B, each one with eight players, would be AB BA BA AB. This is also known as the Thue Morse sequence. The sequence of the teams shooting has to be altered, and the alteration itself also has to be altered. Another idea could involve an attempt by the students to “improve” the rules of handball by changing the size and shape of the goal. What would happen to the penalty shoot-out if the goal were round or triangular? 28

Physical Science Research Volume 1, Issue 7 2nd General Lyceum of Kamatero PHYSICAL SCIENCE RESEARCH RESULTS A statistical view on team handball results: home advantage, team fitness and prediction of match outcomes Jens Smiatek and Andreas Heuer, July 4, 2012 We have analyzed the results of the German Handball Bundesliga for 10 seasons starting from 2001/2002. Our findings have shown a significant increase of the sum of goals per match in the last years. We are able to explain this increase by novel attack strategies which allow a rapid turnover and an acceleration of the game. Despite this increase, we have found a nearly constant home advantage represented by roughly two goals. It has to be noticed, that compared to the total sum of goals, the home advantage is nearly negligible. In contrast to soccer, we have found a binomial distribution function for the number of goals scored by a team in a match. A simple picture for the goal efficiency of an attacking team is given by the throwing of a coin. In the last years, the dominance of a few teams in the Bundesliga has lead to a larger discussion. It has been argued, that the disappearance of surprises like the winning of outsiders would lead to a minor public interest. In agreement to these arguments, we have clearly shown that the stochastic contributions to a handball match which represents the mentioned surprises are significantly smaller compared to soccer. However, by a direct transformation of the corresponding values, we were able to show that the intuitive dominance of these teams is exclusively related to the large number of total goals in a match. In contrast to soccer, our results indicate a decay of the team fitness values over a season while the long time correlation behavior over years is nearly comparable. We are able to explain the dominance of a few teams by the large value for the total number of goals in a match. A method for the prediction of match winners is presented in good accuracy with the real results. We analyze the properties of promoted teams and indicate drastic level changes between the Bundesliga and the second league. Our findings reflect in good agreement recent discussions on modern successful attack strategies. Keywords: Time series analysis of sports results, statistics, interdisciplinary applications of physics 29

Physical Science Research Volume 1, Issue 7 2nd General Lyceum of Kamatero PHYSICAL SCIENCE RESEARCH RESULTS Do the kinematic of the throwing action in handball influence goalkeeper’s judgement? Benoit BIDEAU, Nicolas VIGNAIS, Richard KULPA, Cathy CRAIG, Paul DELAMARCHE Movement, Sport and Health Science Laboratory, University Rennes 2, E.N.S. Cachan, France, 2011 The aim of this study is to evaluate the sources of visual information that a goalkeeper may use to anticipate where a ball is going. By using virtual reality, top national handball goalkeepers were presented with either the throwing action of an attacking player, the resulting ball trajectory or both of these conditions combined. Performance in the thrower only condition was significantly affected by the paucity of information concerning the direction of ball flight. By isolating the presentation of the thrower’s movement kinematics and the trajectory of the ball we were able to look at the contribution of each of these information sources individually and together. The results show that the kinematics of the throwing action alone do not provide sufficient information for goal-keepers to accurately anticipate where the ball is going to end up. To conclude the results presented in this study help clarify the role different sources of perceptual information may play when trying to intercept a ball. They reinforce the importance of being able to track at least part of the ball trajectory to correctly judge where the ball is going to end up. Keywords: Goalkeeper, anticipation skill, kinematic 30

Physical Science Research Volume 1, Issue 7 2nd General Lyceum of Kamatero PHYSICAL SCIENCE RESEARCH RESULTS Skill differences in visual anticipation of type of throw in team-handball penalties Florian Loffing, Norbert Hagemann Institute of Sports and Sports Science, University of Kassel, Kassel, Germany, 2014 Visual identification and anticipation of an opponent’s action intentions is crucial for successful performance in interactive situations such as team-handball penalties. We conducted two experiments to examine experienced and novice team-handball goalkeepers’ ability to predict the type of throw in handball penalties and to identify the observers’ reliance on local versus globally distributed spatial cues. Our research is in line with previous findings on perceptual-cognitive expertise in sports and suggests that experienced team-handball goalkeepers rely on multiple, globally distributed cues when making anticipatory judgments. Our findings suggest that novice team-handball goalkeepers might benefit from learning how multiple, globally distributed spatial cues contribute to different action outcomes in 7 m penalties. 31

Physical Science Research Volume 1, Issue 7 2nd General Lyceum of Kamatero PHYSICAL SCIENCE RESEARCH RESULTS Training programs used by French professional coaches to increase ball throwing velocity of elite handball players. Guillaume LAFFAYE & Thierry DEBANNE Department of Sport Sciences, Université Paris-Sud, Orsay, France, 2011 The goal of this study is to understand through a survey how professional French handball players build their training program (TP). Results show that: 1) the time allotted to ball throwing velocity is a large part of the TP, 2) they based their TP on an accurate analysis of the ball throwing technique and 3) without academic background, coaches used beliefs rather than scientific knowledge to build their TP. Keywords: academic, workout, beliefs, knowledge. 32

Physical Science Research Volume 1, Issue 7 2nd General Lyceum of Kamatero PHYSICAL SCIENCE RESEARCH RESULTS A Virtual Reality Handball Goalkeeper Analysis System 1 2 1 1 1 B. Bolte , F. Zeidler , G. Bruder , F. Steinicke , K. Hinrichs , L. Fischer and J. Schorer 2 1 1 Department of Computer Science, University of Münster, Germany 2 Department of Sport Science, University of Münster, Germany Understanding how professional handball goalkeepers acquire skills to combine decision-making and complex motor tasks is a multidisciplinary challenge. In order to improve a goalkeeper’s training by allowing insights into their complex perception, learning and action processes, virtual reality (VR) technologies provide a way to standardize experimental sport situations. In this poster we describe a VR-based handball system, which supports the evaluation of perceptual- motor skills of handball goalkeepers during shots. In order to allow reliable analyses it is essential that goalkeepers can move naturally like they would do in a real game situation, which is often inhibited by wires or markers that are usually used in VR systems. To address this challenge, we developed a camera- based goalkeeper analysis system, which allows to detect and measure motions of goalkeepers in real- time. Categories and Subject Descriptors (according to ACM CCS): Computer Graphics [I.3.7]: Three- Dimensional Graphics and Realism—Virtual reality Information Interfaces and Presentation [H.5.1]: Multimedia Information Systems—Artificial, augmented, and virtual realities 33

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Handball — We Are Invincible Volume 1, Issue 7 Supervising teachers: Alexandros Markoulakis Eugenia Potiriadou 2nd General Lyceum of Kamatero School Handball Team: THE INTERVIEW The e-Twinning Group: Sport Science Stories 2017-18 48