Score Of A Single Game In Badminton
The Following Is A Score Of A Single Game In Badminton The Top Row Is
The given task involves creating a Java class called BadmintonScoring to model and analyze scores from a single badminton game, including associating each point with a specific stroke type. The assignment requires implementing several functionalities: representing the scores in an array list, calculating maximum points scored by each player, identifying the maximum continuous sequence of points, linking each point to a stroke type using association lists, storing a specific game score sequence, and determining which stroke earned the most points for each player.
Paper For Above instruction
In the sport of badminton, detailed analysis of scoring data provides insights into player performance and strategic tendencies. This paper details the design and implementation of a Java class, BadmintonScoring, to handle such data comprehensively. The class models a single game’s scoring, associates each point with the stroke used to earn it, and performs various statistical computations to assess players' performances.
Design of the BadmintonScoring Class
The core data structure to be used is an ArrayList to store scores for two players across the duration of a game. Each score in the list is represented as an object that encapsulates the player number, the numeric score at a given point, and the stroke type responsible for that point. To facilitate this, an inner class called Point is introduced, encapsulating these three pieces of information. This design enables associating each point with metadata, facilitating detailed analysis.
Step I: Computing Maximum Points
Using the score lists, we can iterate through all points scored by each player to identify the maximum total points achieved at any point during the game. This involves maintaining running totals as the game progresses and updating maximums when higher totals are encountered. These computations help understand each player's peak scoring performance within the game context.
Step II: Identifying Maximum Continuous Sequence of Points
The maximum continuous sequence refers to the longest streak where a player scores points consecutively without interruption from the opponent. For example, if Player 1 scores three consecutive points, their maximum sequence increases accordingly. To compute this, we traverse the score list chronologically, tracking current streaks and updating maximum streaks when streaks break or are extended.
Step III: Associating Points with Stroke Types
This extension involves augmenting each score object with a stroke type, represented as an enumeration or string from a predefined list: slice, drive, smash, drop, net-shot. When a point is scored, we assign the appropriate stroke type, such as Point(player=1, score=1, stroke='drive'). This association enables analysis of stroke effectiveness and preferences for each player.
Step IV: Storing a Specific Game Score Sequence
The detailed score sequence provided is stored in the BadmintonScoring class, using the augmented Point objects. Each point in the sequence is added to the ArrayList with its associated stroke type, replicating the scoring events exactly as given. This data serves as the basis for subsequent analysis, including stroke efficacy and point distribution.
Step V: Analyzing Most Effective Stroke
Using the stored data, we evaluate which stroke contributed most points for each player. This involves aggregating points by stroke type for each player and identifying the stroke with the highest count. Such analysis informs player strategies and highlights preferred or most effective stroke types during the game.
Implementation Details
The implementation involves defining the Point class with fields for player, score, and stroke type. The BadmintonScoring class maintains an ArrayList
- computeMaxPoints: Calculates maximum cumulative points for each player.
- computeMaxStreaks: Determines the longest sequence of consecutive points scored by each player.
- associateStrokeTypes: Links each point with a specific stroke from the predefined list.
- storeGameScore: Inputs and stores the sequence of scores and strokes as per the given data.
- mostEffectiveStroke: Finds the stroke type with the highest points contribution for each player.
Conclusion
The constructed BadmintonScoring class provides a robust framework for modeling, analyzing, and interpreting badminton game scores with detailed stroke associations. Such a system supports strategic insights and performance assessment, showcasing the importance of detailed data analysis in sports analytics.
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