Local Positioning Systems in (Game) Sports

Position data of players and athletes are widely used in sports performance analysis for measuring the amounts of physical activities as well as for tactical assessments in game sports. However, positioning sensing systems are applied in sports as tools to gain objective information of sports behavior rather than as components of intelligent spaces (IS). The paper outlines the idea of IS for the sports context with special focus to game sports and how intelligent sports feedback systems can benefit from IS. Henceforth, the most common location sensing techniques used in sports and their practical application are reviewed, as location is among the most important enabling techniques for IS. Furthermore, the article exemplifies the idea of IS in sports on two applications

Training load quantification in professional Australian basketball and the use of the reactive strength index as a monitoring tool

Study 1: The intraday reliability of the reactive strength index (RSI) calculated from a drop jump in professional men’s basketball. Purpose: To evaluate the reliability of the reactive strength index (RSI) and jump height (JH) performance from multiple drop heights with elite basketball players. Methods: Thirteen professional basketball players (mean ±SD: age 25.8 ± 3.5 y, height 1.96 ± 0.07 m, mass 94.8 ± 8.2 kg) completed 3 maximal drop jump attempts on to a jump mat at 4 randomly assigned box heights and 3 counter movement jump (CMJ) trials. Results: No statistical difference was observed between three trials for both the RSI and JH variable at all the tested drop heights. The RSI for drop jump heights from 20 cm resulted in a coefficient of variation (CV) = 3.1% and an intraclass correlation (ICCα) =0.96, 40 cm resulted in a CV = 3.0% and an ICCα = 0.95, 50 cm resulted in a CV = 2.1% and an ICCα = 0.99. The JH variable at the 40 cm drop jump height resulted in the highest reliability CV = 2.8% and an ICCα = 0.98. Conclusion: When assessing the RSI the 20, 40 and 50 cm drop heights are recommended with this population. When assessing large groups it appears that only one tria Study 2: Does session RPE relate with reactive strength qualities? A case study investigation within the National Basketball League This investigation aimed to establish the relationship between training loads derived from the sessional rating of perceived exertion (sRPE) and the reactive strength index (RSI) over a 27-week competitive season in elite basketball players. Fourteen professional male basketball players (26 ± 3.6 years; 95.8 ± 9.0 kg; 197.3 ± 7.3 cm) participated in this study. Training load data were modeled against the RSI over a 27-week competitive season with the use of a linear mixed model. The relationship between RSI and training load was only significantly different from baseline (Week 1) at Week 24 (p \u3c 0.05) and Week 26 (p \u3c 0.01). These primarily findings suggest that sRPE and RSI have a weak relationship, whilst the RSI does not appear to accurately reflect the changes in training load that occur during an in-season periodized training program in professional male basketball

Proceedings of Mathsport international 2017 conference

Proceedings of MathSport International 2017 Conference, held in the Botanical Garden of the University of Padua, June 26-28, 2017. MathSport International organizes biennial conferences dedicated to all topics where mathematics and sport meet. Topics include: performance measures, optimization of sports performance, statistics and probability models, mathematical and physical models in sports, competitive strategies, statistics and probability match outcome models, optimal tournament design and scheduling, decision support systems, analysis of rules and adjudication, econometrics in sport, analysis of sporting technologies, financial valuation in sport, e-sports (gaming), betting and sports

Development of an algorithm and a system for deductive prediction and analysis of movment of basketball referees

Докторска дисертација припада области информационих система, са јасним акцентом на употребу неуронских мрежа за решавање проблема вишеструких зависних временских серија  који је у  овом докторату дефинисан.Основни циљ дисертације је креирање система у форми едукативног софтвера путем којег ће се обучавати младе кошаркашке судије Један од кључих елемената овог  доктората јесте симулација хоризонталног видног поља на основу којег се  утврђује да ли је резоновано кретање кошаркашких судија било адекватно  или није. Стога развијени софтвер поседује споменуту едукативну примену. Како би се реализовао споменути софтвер спроведено је истраживање које је обухватило обучавање великог броја традиционалних вишеслојних перцептрона као и формирање посебне  LTR  –  MDTS структуре неуронске мреже за коју се сматра да је погодна за решавање постојећег проблема. За реализацију симулације хоризонталног видног поља разматрано је више алгоритама из области рачунарске графике  а  Sweep and Prune  алгоритам је парцијално пружио основу за развијени и тренутно  имплементирани алгоритам.Doktorska disertacija pripada oblasti informacionih sistema, sa jasnim akcentom na upotrebu neuronskih mreža za rešavanje problema višestrukih zavisnih vremenskih serija  koji je u  ovom doktoratu definisan.Osnovni cilj disertacije je kreiranje sistema u formi edukativnog softvera putem kojeg će se obučavati mlade košarkaške sudije Jedan od ključih elemenata ovog  doktorata jeste simulacija horizontalnog vidnog polja na osnovu kojeg se  utvrđuje da li je rezonovano kretanje košarkaških sudija bilo adekvatno  ili nije. Stoga razvijeni softver poseduje spomenutu edukativnu primenu. Kako bi se realizovao spomenuti softver sprovedeno je istraživanje koje je obuhvatilo obučavanje velikog broja tradicionalnih višeslojnih perceptrona kao i formiranje posebne  LTR  –  MDTS strukture neuronske mreže za koju se smatra da je pogodna za rešavanje postojećeg problema. Za realizaciju simulacije horizontalnog vidnog polja razmatrano je više algoritama iz oblasti računarske grafike  a  Sweep and Prune  algoritam je parcijalno pružio osnovu za razvijeni i trenutno  implementirani algoritam.Doctoral dissertation belongs to the field of information systems, with a clear  emphasis on the use of neural networks for solving the problem of multiple dependent time series, which is defined in this doctorate. The main objective of the  thesis is to create a system in the form of educational software that will be used druring the training of young basketball referees.One of the key elements of this doctorate is a simulation of a horizontal field of  vision  on the basis of which it is determined whether the movement of  reasoned  basketball referees was adequate   or not.  Therefore developed software has  aforementioned educational use. In order  to realize the aforementioned software, a  research  was conducted that included training of a large number of traditional multilayer perceptron neural networks and the  formation of special LTR  -  MDTS  neural network  structure which is considered to be  suitable  for solving the presented problem. For the realization of the simulation  of the horizontal field of vision a large number of algorithms in the field of computer graphis was considered  and Sweep and Prune algorithm partially provided the basis for the developed and  currently implemented algorithm

A Statistical Investigation into Factors Affecting Results of One Day International Cricket Matches

The effect of playing “home” or “away” and many other factors, such as batting first or second, winning or losing the toss, have been hypothesised as influencing the outcome of major cricket matches. Anecdotally, it has often been noted that Subcontinental sides (India, Pakistan, Sri Lanka and Bangladesh) tend to perform much better on the Subcontinent than away from it, whilst England do better in Australia during cooler, damper Australian Summers than during hotter, drier ones. In this paper, focusing on results of men’s One Day International (ODI) matches involving England, we investigate the extent to which a number of factors – including playing home or away (or the continent of the venue), batting or fielding first, winning or losing the toss, the weather conditions during the game, the condition of the pitch, and the strength of each team’s top batting and bowling resources – influence the outcome of matches. By employing a variety of Statistical techniques, we find that the continent of the venue does appear to be a major factor affecting the result, but winning the toss does not. We then use the factors identified as significant in an attempt to build a Binary Logistic Regression Model that will estimate the probability of England winning at various stages of a game. Finally, we use this model to predict the results of some England ODI games not used in training the model