Money Puck: The Effectiveness of Statistical Analysis in Building an NHL Team

The 2013 Collective Bargaining Agreement in the National Hockey League limits contracts offered to free agents in terms of length and variance in yearly salary. These changes have made finding undervalued free agents even more important to teams’ general managers. The purpose of this study is to evaluate players and teams with both traditional and advanced metrics to determine how players are valued in comparison to their impact on their team’s performance. A team’s winning percentage is hypothesized to be a function of shooting percentage and save percentage, as well as proxies for puck possession time, such as shots on goal per game, shots against per game, blocked shots, missed shots, and face-off percentage. It is also hypothesized that players with higher puck possession attributes will impact a team’s winning percentage to a greater extent than those with lower metrics, and so should be a key factor in determining how general managers use available salary money to improve their team. Based on data from NHL.com and stats.hockeyanalysis.com, we estimate team performance of all 30 NHL teams for each of the six previous seasons of play (2007-2013) as a function of puck possession proxies. We find that puck possession proxies significantly impact a team’s winning percentage and that free agents with higher performance metrics have a significantly greater impact on team performance as much as several less expensive players in cases that a team lacks depth

Improvement of image quality of time-domain diffuse optical tomography with lp sparsity regularization

An lp (0 < p ≤ 1) sparsity regularization is applied to time-domain diffuse optical tomography with a gradient-based nonlinear optimization scheme to improve the spatial resolution and the robustness to noise. The expression of the lp sparsity regularization is reformulated as a differentiable function of a parameter to avoid the difficulty in calculating its gradient in the optimization process. The regularization parameter is selected by the L-curve method. Numerical experiments show that the lp sparsity regularization improves the spatial resolution and recovers the difference in the absorption coefficients between two targets, although a target with a small absorption coefficient may disappear due to the strong effect of the lp sparsity regularization when the value of p is too small. The lp sparsity regularization with small p values strongly localizes the target, and the reconstructed region of the target becomes smaller as the value of p decreases. A phantom experiment validates the numerical simulations

Review of optical breast imaging and spectroscopy

Diffuse optical imaging and spectroscopy of the female breast is an area of active research. We review the present status of this field and discuss the broad range of methodologies and applications. Starting with a brief overview on breast physiology, the remodeling of vasculature and extracellular matrix caused by solid tumors is highlighted that is relevant for contrast in optical imaging. Then, the various instrumental techniques and the related methods of data analysis and image generation are described and compared including multimodality instrumentation, fluorescence mammography, broadband spectroscopy, and diffuse correlation spectroscopy. We review the clinical results on functional properties of malignant and benign breast lesions compared to host tissue and discuss the various methods to improve contrast between healthy and diseased tissue, such as enhanced spectroscopic information, dynamic variations of functional properties, pharmacokinetics of extrinsic contrast agents, including the enhanced permeability and retention effect. We discuss research on monitoring neoadjuvant chemotherapy and on breast cancer risk assessment as potential clinical applications of optical breast imaging and spectroscopy. Moreover, we consider new experimental approaches, such as photoacoustic imaging and long-wavelength tissue spectroscopy

GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction

In voxel-based neuroimage analysis, lesion features have been the main focus in disease prediction due to their interpretability with respect to the related diseases. However, we observe that there exists another type of features introduced during the preprocessing steps and we call them "\textbf{Procedural Bias}". Besides, such bias can be leveraged to improve classification accuracy. Nevertheless, most existing models suffer from either under-fit without considering procedural bias or poor interpretability without differentiating such bias from lesion ones. In this paper, a novel dual-task algorithm namely \emph{GSplit LBI} is proposed to resolve this problem. By introducing an augmented variable enforced to be structural sparsity with a variable splitting term, the estimators for prediction and selecting lesion features can be optimized separately and mutually monitored by each other following an iterative scheme. Empirical experiments have been evaluated on the Alzheimer's Disease Neuroimaging Initiative\thinspace(ADNI) database. The advantage of proposed model is verified by improved stability of selected lesion features and better classification results.Comment: Conditional Accepted by Miccai,201

Evaluation of higher-order time-domain perturbation theory of photon diffusion on breast-equivalent phantoms and optical mammograms

Time-domain perturbation theory of photon diffusion up to third order was evaluated for its accuracy in deducing optical properties of breast tumors using simulated and physical phantoms and by analyzing 141 projection mammograms of 87 patients with histology-validated tumors that had been recorded by scanning time-domain optical mammography. The slightly compressed breast was modeled as (partially) homogeneous diffusely scattering infinite slab containing a scattering and absorbing spherical heterogeneity representing the tumor. Photon flux densities were calculated from densities of transmitted photons, assuming extended boundary conditions. Explicit formulas are provided for second-order changes in transmitted photon density due to the presence of absorbers or scatterers. The results on phantoms obtained by perturbation theory carried up to third order were compared with measured temporal point spread functions, with numerical finite-element method (FEM) simulations of transmitted photon flux density, with results obtained from the diffraction of diffuse photon density waves, and from Pade approximants. The breakdown of first-, second-, and third-order perturbation theory is discussed for absorbers and a general expression was derived for the convergence of the Born series in this case. Taking tumor optical properties derived by the diffraction model as reference we conclude that estimates of tumor absorption coefficients by perturbation theory agree with reference values within +/-25% in only 65% (first order), 66% (second order), and 77% (third order) of all mammograms analyzed. In the remaining cases tumor absorption is generally underestimated due to the breakdown of perturbation theory. On average the empirical Pade approximants yield tumor absorption coefficients similar to third-order perturbation theory, yet at noticeable lower computational efforts

Implementation of the extended Kalman filter for determining the optical and geometrical properties of turbid layered media by time-resolved single distance measurements

In this article we propose an implementation of the extended Kalman filter (EKF) for the retrieval of optical and geometrical properties in two-layered turbid media assuming a dynamic setting, where absorption of each layer was changed in different steps. Prior works implemented the EKF in frequency-domain with several pairs of light sources and detectors and for static parameters estimation problems. Here we explore the use of the EKF in single distance, time-domain measurements, together with a corresponding forward model. Results show good agreement between retrieved and nominal values, with rather narrow analytical credibility intervals, indicating that the recovery process has low uncertainty, especially for the absorption coefficients.Fil: Baez, Guido Rodrigo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; ArgentinaFil: García, Héctor Alfredo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; ArgentinaFil: Grosenick, Dirk. Physikalisch-technische Bundesanstalt; AlemaniaFil: Wabnitz, Heidrun. Physikalisch-technische Bundesanstalt; Alemani