Batting lineup against any one particular team - Research Paper Example

Real Life Issues Using Statistical Analysis Outline A. Introduction 1. Statistics are useful in a multitude of ways 2. Statistical analysis and sports B. Problem Statement 1. Baseball managers rely on data to determine their batting lineup 2. It is important to understand a hitter’s performance against a particular pitcher C. Research Question D. Data Collection 1. Computer analysis 2. Personal insight and record keeping E. Data Analysis 1. Which hitters do well against particular pitchers? 2. What is the optimal batting lineup to pit against any one particular pitcher F. Results and Conclusions Real Life Issues Using Statistical Analysis Introduction Statistics are useful in almost any area of life. Consider the workplace, home, social organization, or sports arena. Statistical analysis enables us to consider where we have been, where we are going, and how effective we have been at both stages. It is a process that allows us to consider and realize trends, either positive or negative, and lead us to conclusions about what to do next. Owing to this reality, it is therefore important to consider the myriad of uses that statistics brings to everyday life. To accomplish this, this paper will examine a hypothetical problem and propose a research question that can be solved through statistical analysis. Consider the sport of baseball. Each team has a manager who bases many of his decisions on various pieces of statistics that are given to him. A team’s batting lineup, for example, often is a critical piece to the number of runs a team scores, and their ability to win games. It can be said, therefore, that a team’s batting lineup depends upon statistical analysis and affects their ability to score runs, hit off certain pitchers, and avoid putting hitters in situations where they are likely to fail. Identification of the Problem The problem in baseball, like many of life’s situations, is that basing a decision on wrong assumptions can be disastrous. The batting lineup in baseball is a critical component. All aspects of the hitter, and the opposing team’s pitcher, must be considered when making out the lineup. The effective resolution to this problem will provide the team with a more enhanced opportunity to win. Research Question The research question for this problem would be: What batting lineup will prove the most effective against any one particular team? Data Collection To answer this question, there is a plethora of data the collected in order to assist in the statistical analysis that will lead to the formation of an effective batting order. To begin, the manager would need to collect various components of a player’s batting average. This includes, but is certainly not limited to, the following items: 1) A hitters overall batting average, 2) A hitters average with runners in scoring position, 3) A hitters average against right handed pitchers, 4) A hitters average against left handed pitchers, and 5) A hitters average against the specific opposing pitcher assigned to any one particular game (Albright, 1993, p. 1178). The data to be collected can be gathered by taking a look at a player’s combined batting averages over the course of a season. In today’s day and age, this is usually simplified with the use of technology. It is important to collect the data from one season only, as a hitters performance tends to fluctuate season by season, so their performance in previous years may not reflect on this current ability, or inability, to hit well against a particular pitcher this year (Talsma, 1999, p. 738). When thinking about much how much data is needed to solve this problem, more is definitely better. The more data that can be covered, in as many relevant areas as possible, the more benefit the statistical analysis can be to provide a manager with the accurate picture they need to assess player performance as the season progresses. Data Analysis It is not enough to simply collect a bunch of data related to hitting in baseball. The data must then be analyzed effectively to determine the best course of action to take. This is done trough careful consideration by the managerial staff, based on their knowledge of the sport, the player’s psyche, and the statistics in front of them. For every game, the batting lineup is subject to change based upon the data analysis conducted in such a manner as explained in this hypothetical paper. Managers will begin by considering the opposing pitcher that their team will face. They will then looking at the data to determine which order their hitters should be arranged in the lineup in order to give them maximum opportunity to score runs, based on the current statistics that they have collected (Koban & McNelis, 2008, p. 266). An example of this would be to consider who should bat first in tomorrow’s game. HO: Player C will bat first in tomorrow’s game. H1: Player C will not bat first in tomorrow’s game. One approach that can be used to arrive at an eventual conclusion for this issue is to employ the use of multiple regression analysis. The goal here would be to determine if Player C can effectively hit in the opening spot on a teams lineup against one particular opposing pitcher based on his past performance in terms of on base percentage, home run, strikeouts, or walks against that pitcher. All of these factors can be combine into a multiple regression equation to determine the feasibility of choosing Player C to lead off the lineup against one particular opposing pitcher. Results and Conclusions While the statistical analysis explained in this paper will go a long way in determining a teams batting lineup, there are other factors at play. In the end, however, the hypothesis presented will likely be proven or disproven based on the statistics provided. It has been said that numbers to not lie. In baseball, this is often even truer. If one particular player on a team, for example, is known to hit particularly well against a particular pitcher when compared to the rest of the team, that player is likely to bat either first or fourth, even if that is not their normal position in the lineup. Likewise, if the data reveals that one particular hitter does particularly poor against the pitcher in question, then the lineup would be adjusted accordingly as well, depending on the managers philosophy relating to the importance of the data and the positioning of their players. In the end, the data collected will lead and guide the manager towards making sound and effective decisions affecting the outcome of the game. They depend, therefore, on sound data in order to ensure that they are basing their decisions on the most accurate information available. This leads them to either supporting or rejecting any of their initial hypothesis, eventually arriving at a batting lineup that they feel provides them with the best opportunity to perform well on any given game day. References Albright, C. (1993). A statistical analysis of hitting streaks in baseball. Journal of the American Statistical Association, 88(424), 1175-1183. Koban, L., & McNelis, E. (2008). Fantasy baseball with a statistical twist. Mathematics Teacher, 102(4), 264-271. Talsma, G. (1999). Data analysis and baseball. The Mathematics Teacher, 92(8), 738. Read More