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Super Mega Baseball: Extra Innings Steam CD Key

Super Mega Baseball: Extra Innings Steam CD Key

Hilarious. Hardcore. Hardball. Super Mega Baseball packs ultra-tight batting/pitching mechanics, a novel difficulty system dubbed “Ego”, and a deep baseball simulation with accurate physics and comprehensive statistics tracking.FeaturesRealistic Simulation and Physics: Don’t be fooled by the light-hearted/comical presentation; the fundamentals of baseball are well represented and if someone isn’t familiar with the rules, they will be after playing Super Mega Baseball.Groundbreaking Difficulty System: Super Mega Baseball boasts an innovative difficulty control scheme called the Ego system. The Ego system offers a fine-grained control of difficulty on a per-user basis, which has been widely praised for leveling the playing field in cooperative and competitive modes. This system will push seasoned gamers to their limits while simultaneously providing a gentle introduction for beginners.Up-to Four Player Local Co-op Play: In addition to solo play, players can try their hand at head-to-head, 2v1, 2v2 and co-op against the CPU. In co-op mode, teammates alternate batting/running each time at-bat, and alternate pitching/fielding each inning, meaning ballplayers need to be on their toes every play. To even games, players can use the Ego system to set up a competitive game between friends of any skill level.Ultra Responsive and Blazing Fast Gameplay: Controls are easy to learn, but players will need to master jumping, diving, wall-catches, power-swings and cut-off plays to properly dominate friends. Short load times and a streamlined interface means most of the time is spent in the action, with nine-inning games taking around 20 minutes to play.Full Batting and Pitching Statistics: Most baseball statistics imaginable are available and ballplayers can use these to show off their MVP-quality skills.Leveling System: Players tally up Starpoints for hits, strikeouts and catches during each game and Level Up once they collect enough points. Players can hire staff to train and coach their squad, improving skill attributes such as Power and Speed. Use that jacked up team to win at higher difficulties (and post higher leaderboard scores than friends)!Player Customization: Customize the look and names of a team’s players to create a ragtag crew of family and friends. Make as many aesthetic adjustments as you can imagine!

GBP 7.45
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Analyzing Baseball Data with R Second Edition

Analyzing Baseball Data with R Second Edition

Analyzing Baseball Data with R Second Edition introduces R to sabermetricians baseball enthusiasts and students interested in exploring the richness of baseball data. It equips you with the necessary skills and software tools to perform all the analysis steps from importing the data to transforming them into an appropriate format to visualizing the data via graphs to performing a statistical analysis. The authors first present an overview of publicly available baseball datasets and a gentle introduction to the type of data structures and exploratory and data management capabilities of R. They also cover the ggplot2 graphics functions and employ a tidyverse-friendly workflow throughout. Much of the book illustrates the use of R through popular sabermetrics topics including the Pythagorean formula runs expectancy catcher framing career trajectories simulation of games and seasons patterns of streaky behavior of players and launch angles and exit velocities. All the datasets and R code used in the text are available online. New to the second edition are a systematic adoption of the tidyverse and incorporation of Statcast player tracking data (made available by Baseball Savant). All code from the first edition has been revised according to the principles of the tidyverse. Tidyverse packages including dplyr ggplot2 tidyr purrr and broom are emphasized throughout the book. Two entirely new chapters are made possible by the availability of Statcast data: one explores the notion of catcher framing ability and the other uses launch angle and exit velocity to estimate the probability of a home run. Through the book’s various examples you will learn about modern sabermetrics and how to conduct your own baseball analyses. Max Marchi is a Baseball Analytics Analyst for the Cleveland Indians. He was a regular contributor to The Hardball Times and Baseball Prospectus websites and previously consulted for other MLB clubs. Jim Albert is a Distinguished University Professor of statistics at Bowling Green State University. He has authored or coauthored several books including Curve Ball and Visualizing Baseball and was the editor of the Journal of Quantitative Analysis of Sports. Ben Baumer is an assistant professor of statistical & data sciences at Smith College. Previously a statistical analyst for the New York Mets he is a co-author of The Sabermetric Revolution and Modern Data Science with R.

GBP 52.99
1