Beyond Moneyball

This study provides an updated test of Billy Beane’s Moneyball hypothesis using a panel model over the years 1999-2013. We regressed winning percentage as a function of the original Moneyball variables, which included on-base percentage, slugging percentage, on-base percentage against and slugging percentage against. In turn we created our own model which replaced the “against” statistics with earned run average and fielding percentage. Within both models, we concluded that the coefficient of on-base percentage was significantly greater than slugging percentage, which supports Beane’s theory that in today’s game on-base percentage is more important than slugging in determining winning percentage. We extend this analysis using both models to test for the effects of the 2005 steroid ban and found that neither of the coefficients for on-base percentage or slugging percentage were significantly affected by the ban. These conclusions can be used by major league managers and owners to decide which players to trade for or to pick up in free agency

Stability analysis of slug flow control

The threat of slugging to production facilities has been known since the 1970s. This undesirable flow phenomenon continues to attract the attention of researchers and operators alike. The most common method for slug mitigation is by choking the valve at the exit of the riser which unfortunately could negatively affect production. The focus, therefore, is to satisfy the need for system stability and to maximize production simultaneously. Active feedback control is a promising way to achieve this. However, due to the complexity of multiphase flow systems, it is a challenge to develop a robust slug control system to achieve the desired performance using existing design tools. In this paper, a new general method for multiphase flow system stability analysis was proposed. Active feedback control was observed to optimize slug attenuation compared with manual choking. The use of soft sensors was believed to be desirable for the practical implementation of the proposed control technique

Severe slugging phenomenon and a novel method for its mitigation based on the Surface Jet Pump technology

Master's thesis in Offshore technology : industrial asset managementThe present thesis is focused on the problem of severe slugging and ways to mitigate it. Severe slugging is an oscillatory multiphase flow regime characterized by high variations in production rates occurring in offshore pipeline-riser systems. Chapter 1 provides basic notions related to multiphase flow, which are essential for understanding of the rest of the thesis. Chapter 2 gives a thorough description of the severe slugging occurrence mechanism and preconditions as well as introduces different types of the phenomenon. Special attention is given to the effect of mass transfer and how it alters the flow regime’s behavior. Detrimental effects of severe slugging are discussed and some examples are provided. Chapter 3, making a significant part of the thesis, provides its reader with carefully gathered data concerning severe slugging alleviation and mitigation methods published from 1973 to 2015, both conventional and purely speculative methods are discussed. Examples, where possible, are given. Chapter 4 considers modeling of severe slugging in a vertical riser with aids of the multiphase simulation program OLGA. A constructed study case is considered and described with some of the mitigation techniques implemented and tested. Chapter 5 evaluates a novel severe slugging mitigation method proposed by Caltec Ltd. UK. The method assumes pipeline system depressurization by installation of a Surface Jet Pump on the production platform. The chapter gives the method description and verifies its feasibility using a simulation model within OLGA. The thesis ends with Conclusions and Recommendations for further work and self-evaluation

Investigation of slug mitigation: self-lifting approach in a deepwater oil field

Slug flow is a flow assurance issue that staggers production and, in some cases, 'kills the flow' of the well. Severe slugging, a type of slugging which usually occurs at the base of the riser column, causes large amplitudes in the fluctuation of pressure within the riser column and consequently damages equipment placed topside. An adaptation of a novel concept to slug mitigation: the self-lifting model, is presented. This model presents variations to the internal diameter of the self-lift bypass to produce effective mitigation to severe slugging

Payroll Disparity Among Major League Baseball Teams: Building a Competitive Team Despite Limited Resources

There has been an inequality in payroll among Major League Baseball teams for many years that became increasingly evident in the late 1990s. Revenue disparities among teams cause a competitive imbalance for the league and make it harder for small-market teams to compete with large-market teams with much higher payrolls. MLB has attempted to alleviate this disparity, but the implementation of revenue sharing and the competitive balance tax alone is not enough for small-market clubs to build a competitive team. There are a number of ways that small-market clubs can build a competitive team despite limited resources, including employing the moneyball hypothesis, quantifying market inefficiencies, utilizing the team’s farm system, taking advantage of trade opportunities, and making intelligent contract decisions

A Machine Learning Approach for Virtual Flow Metering and Forecasting

We are concerned with robust and accurate forecasting of multiphase flow rates in wells and pipelines during oil and gas production. In practice, the possibility to physically measure the rates is often limited; besides, it is desirable to estimate future values of multiphase rates based on the previous behavior of the system. In this work, we demonstrate that a Long Short-Term Memory (LSTM) recurrent artificial network is able not only to accurately estimate the multiphase rates at current time (i.e., act as a virtual flow meter), but also to forecast the rates for a sequence of future time instants. For a synthetic severe slugging case, LSTM forecasts compare favorably with the results of hydrodynamical modeling. LSTM results for a realistic noizy dataset of a variable rate well test show that the model can also successfully forecast multiphase rates for a system with changing flow patterns

Significance of Handedness in Baseball

For my STAT 499 senior project, I looked at data regarding handedness in batting versus handedness in pitching within Major League Baseball (MLB). It has been traditional in baseball to have batters in your lineup that swing from the side of the plate that is opposite from the pitchers’ throwing hand. For example, if the starting pitcher is right-handed, it would be more beneficial for the team to start as many left-handed batters as possible. My goal for this project was to test if there is a significant difference in performance between batters facing a same-handed pitcher versus an opposite-handed pitcher by comparing batting averages and other hitting statistics. The 2017, 2018, and 2019 regular seasons of MLB hitting data were used. Using Two-Way ANOVA tests and interaction plots, there is evidence of a significant difference in performance between batters facing a same-handed pitcher versus an opposite-handed pitcher