Automated Detection of Complex Tactical Patterns in Football—Using Machine Learning Techniques to Identify Tactical Behavior

Football tactics is a topic of public interest, where decisions are predominantly made based on gut instincts from domain-experts. Sport science literature often highlights the need for evidence-based research on football tactics, however the limited capabilities in modeling the dynamics of football has prevented researchers from gaining usable insights. Recent technological advances have made high quality football data more available and affordable. Particularly, positional data providing player and ball coordinates at every instance of a match can be combined with event data containing spatio-temporal information on any event taking place on the pitch (e.g. passes, shots, fouls). On the other hand, the application of machine learning methods to domain-specific problems yields a paradigm shift in many industries including sports. The need for more informed decisions as well as automating time consuming processes—accelerated by the availability of data—has motivated many scientific investigations in football analytics. This thesis is part of a research program combining methodologies from sports and data science to address the following problems: the synchronization of positional and event data, objectively quantifying offensive actions, as well as the detection of tactical patterns. Although various basic insights from the overall research program are integrated, this thesis focuses primarily on the latter one. Specifically, positional and event data are used to apply machine learning techniques to identify eight established tactical patterns in football: namely high-/mid-/low-block defending, build-up/attacking play in the offense, counterpressing and counterattacks during transitions, and patterns when defending corner-kicks, e.g. player-/zonal- or post-marking. For each pattern, we consolidate definitions with football experts and label large amounts of data manually using video recordings. The inter-labeler reliability is used to ensure that each pattern is well-defined. Unsupervised techniques are used for the purpose of exploration, and supervised machine learning methods based on expert-labeled data for the final detection. As an outlook, semi-supervised methods were used to reduce the labeling effort. This thesis proves that the detection of tactical patterns can optimize everyday processes in professional clubs, and leverage the domain of tactical analysis in sport science by gaining unseen insights. Additionally, we add value to the machine learning domain by evaluating recent methods in supervised and semi supervised machine learning on challenging, real-world problems

Attacking Key Performance Indicators in Soccer: Current Practice and Perceptions from the Elite to Youth Academy Level

Key Performance Indicators (KPIs) are used to evaluate the offensive success of a soccer team (e.g. penalty box entries) or player (e.g. pass completion rate). However, knowledge transfer from research to applied practice is understudied. The current study queried practitioners (n = 145, mean ± SD age: 36 ± 9 years) from 42 countries across different roles and levels of competition (National Team Federation to Youth Academy levels) on various forms of data collection, including an explicit assessment of twelve attacking KPIs. 64.3% of practitioners use data tools and applications weekly (predominately) to gather KPIs during matches. 83% of practitioners use event data compared to only 52% of practitioners using positional data, with a preference for shooting related KPIs. Differences in the use and value of metrics derived from positional tracking data (including Ball Possession Metrics) were evident between job role and level of competition. These findings demonstrate that practitioners implement KPIs and gather tactical information in a variety of ways with a preference for simpler metrics related to shots. The low perceived value of newer KPIs afforded by positional data could be explained by low buy-in, a lack of education across practitioners, or insufficient translation of findings by experts towards practice

Equations of state implementation for 1-D modelling of performance in ram accelerator thermally choked propulsion mode

© 2015 Inderscience Enterprises Ltd. This paper presents advancement on one-dimensional (1-D) unsteady modelling of a ram accelerator (RAMAC) in the sub-detonative velocity regime by including real-gas equations of state (EoS) in order to account for the compressibility effects of the combustion products. Several equations of state based on generalised empirical and theoretical considerations are incorporated into a 1-D computer code TARAM. The objective of this work is to provide the best available formulations in order to improve the unsteady 1-D model and make the TARAM code a useful tool to predict the performance of the RAMAC in the sub-detonative velocity regime, without having to resort to more complicated 2-D or 3-D computational schemes. The calculations are validated against experimental data from 38-mm and 90-mm-bore facilities and good agreements have been achieved. Yet, the results demonstrate the need for further CFD studies involving the scale effect

Body Fat of Basketball Players: A Systematic Review and Meta-Analysis

Background: This study aimed to provide reference values for body fat (BF) of basketball players considering sex, measurement method, and competitive level. Methods: A systematic literature research was conducted using five electronic databases (PubMed, Web of Science, SPORTDiscus, CINAHL, Scopus). BF values were extracted, with analyses conducted using random-effects models and data reported as percentages with 95% confidence intervals (CI). Results: After screening, 80 articles representing 4335 basketball players were selected. Pooled mean BF was 13.1% (95% CI 12.4–13.8%) for male players and 20.7% (95% CI 19.9–21.5%) for female players. Pooled mean BF was 21.4% (95% CI 18.4–24.3%) measured by dual-energy X-ray absorptiometry (DXA), 15.2% (95% CI 12.8–17.6%) via bioelectrical impedance analysis (BIA), 12.4% (95% CI 10.6–14.2%) via skinfolds and 20.0% (95% CI 13.4–26.6%) via air displacement plethysmography. Pooled mean BF across competitive levels were 13.5% (95% CI 11.6–15.3%) for international, 15.7% (95% CI 14.2–17.2%) for national and 15.1% (95% CI 13.5–16.7%) for regional-level players. As the meta-regression revealed significant effects of sex, measurement method and competitive level on BF, the meta-analysis was adjusted for these moderators. The final model revealed significant differences in BF between male and female players (p < 0.001). BF measured by DXA was significantly higher than that measured by BIA or skinfolds (p < 0.001). International-level players had significantly lower BF than national and regional-level players (p < 0.05). Conclusions: Despite the limitations of published data, this meta-analysis provides reference values for BF of basketball players. Sex, measurement method and competitive level influence BF values, and therefore must be taken into account when interpreting results.This article was supported by the Open Access Publishing Fund of the University of Vienna

Single cell analysis in native tissue: Quantification of the retinoid content of hepatic stellate cells

Hepatic stellate cells (HSCs) are retinoid storing cells in the liver: The retinoid content of those cells changes depending on nutrition and stress level. There are also differences with regard to a HSC’s anatomical position in the liver. Up to now, retinoid levels were only accessible from bulk measurements of tissue homogenates or cell extracts. Unfortunately, they do not account for the intercellular variability. Herein, Raman spectroscopy relying on excitation by the minimally destructive wavelength 785 nm is introduced for the assessment of the retinoid state of single HSCs in freshly isolated, unprocessed murine liver lobes. A quantitative estimation of the cellular retinoid content is derived. Implications of the retinoid content on hepatic health state are reported. The Raman-based results are integrated with histological assessments of the tissue samples. This spectroscopic approach enables single cell analysis regarding an important cellular feature in unharmed tissue

Transient conditions for biogenesis on low-mass exoplanets with escaping hydrogen atmospheres

Exoplanets with lower equilibrium temperatures than Earth and primordial hydrogen atmospheres that evaporate after formation should pass through transient periods where oceans can form on their surfaces, as liquid water can form below a few thousand bar pressure and H2-H2 collision-induced absorption provides significant greenhouse warming. The duration of the transient period depends on the planet size, starting H2 inventory and star type, with the longest periods typically occurring for planets around M-class stars. As pre-biotic compounds readily form in the reducing chemistry of hydrogen-rich atmospheres, conditions on these planets could be favourable to the emergence of life. The ultimate fate of any emergent organisms under such conditions would depend on their ability to adapt to (or modify) their gradually cooling environment.Comment: 19 pages, 5 figures, accepted for publication in Icaru

The biological activities of roots and aerial parts of Alchemilla vulgaris L

The phytochemical composition, in vitro antioxidant and antimicrobial activities, cytotoxicity and antigenotoxicity of fruit extracts of Opuntia dillenii were studied. The phytochemical composition was evaluated using HPLC, GC-MS and UV–Vis spectrophotometry. Spectrophotometrical methods were used to estimate the antioxidant potential. Antimicrobial activity was determined using a microdilution method. The cytotoxic effects of the extracts were evaluated using the MTT assay. In vitro DNA-protective activity against hydroxyl radicalinduced DNA damage was also determined. The results showed that polar extracts of O. dillenii had a significant amount of phenolic compounds, including flavonoids, whereas non-polar extracts had mostly terpenoids and fatty acid derivatives. Moreover, several extracts showed good antioxidant and antimicrobial activities, with low cytotoxicity and significant DNA-protective effects. These results showed that the extracts of O. dillenii have promising bioactivity and further studies on the potential application in different areas of food and health might be beneficial