Measuring skill via player dynamics in football dribbling.

Although a myriad of studies have been conducted on player behavior in football, in-depth studies with structured theory are rare due to the difficulty in quantifying individual player skills and team strategies. We propose a physics-based mathematical model that describes football players' movements during dribbling situations, parameterized by the attacker aggressiveness, the defender hesitance and the top speed of both players. These player- and situation-specific parameters are extracted by fitting the model to real player trajectories from Major League Soccer games, and enable the quantification of player dribbling attributes and decisions beyond classical statistics. We show that the model captures the essential dribbling dynamics, and analyze how differences between parameters in varying game situations provide valuable insights into players' behavior. Lastly, we quantitatively study how changes in the player's parameters impact dribbling performance, enabling the model to provide scientific guidance to player training, scouting and game strategy development.

Public health implications of opening National Football League stadiums during the COVID-19 pandemic.

SignificanceUsing data from 2020, we measure the public health impact of allowing fans into sports stadiums during the COVID-19 pandemic; these results may inform future policy decisions regarding large outdoor gatherings during public health crises. Second, we demonstrate the utility of robust synthetic control in this context. Synthetic control and other statistical approaches may be used to exploit the underlying low-dimensional structure of the COVID-19 data and serve as useful instruments in analyzing the impact of mitigation strategies adopted by different communities. As with all statistical methods, reliable outcomes depend on proper implementation strategies and well-established robustness tests; in the absence of these safeguards, these statistical methods are likely to produce specious or misleading conclusions.

Nonlinear viscoelastic biomaterials: meaningful characterization and engineering inspiration.

Nonlinear mechanical properties play an important role in numerous biological functions, for instance the locomotion strategy used by terrestrial gastropods. We discuss the progress made toward bioinspired snail-like locomotion and the pursuit of an engineered fluid that imitates the nonlinear viscoelastic properties of native gastropod pedal mucus. The rheological behavior of native pedal mucus is characterized using an oscillatory deformation protocol known as large amplitude oscillatory shear, and we review recently developed techniques for appropriately describing nonlinear viscoelastic behavior. Although materials that exhibit purely elastic and purely viscous nonlinearities are amenable to standard techniques for characterization, pedal mucus samples (and biomaterials in general) are viscoelastic, exhibiting both elastic and viscous nonlinear responses simultaneously and requiring advanced techniques for characterization. We reveal the utility of these new methods by examining trail mucus from the terrestrial slug Limax maximus using oscillatory shear rheology. Material responses which previously could only be described mathematically, with little physical insight, can now be interpreted with familiar language such as strain-stiffening/softening and shear-thickening/thinning. The new methodology is applicable to any complex material that can be tested using imposed oscillatory deformations. We have developed data-analysis software to enable wider use of this framework within and beyond the biomaterials community. The functionality of this software is outlined here.