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Football Analytics with Python & R
Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data. Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to: Apply basic statistical concepts to football datasets Describe football data with quantitative methods Create efficient workflows that offer reproducible results Use data science skills such as web scraping, manipulating data, and plotting data Implement statistical models for football data Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny And more
Football Analytics with Python and R
Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data. Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to: Apply basic statistical concepts to football datasets Describe football data with quantitative methods Create efficient workflows that offer reproducible results Use data science skills such as web scraping, manipulating data, and plotting data Implement statistical models for football data Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny And more
Football Analytics with Python & R
Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data. Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to: Apply basic statistical concepts to football datasets Describe football data with quantitative methods Create efficient workflows that offer reproducible results Use data science skills such as web scraping, manipulating data, and plotting data Implement statistical models for football data Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny And more
The Gus Van Sant Touch
Beloved, controversial, influential, the creator of such fascinating and award-winning films as My Own Private Idaho, Good Will Hunting, Elephant, and Milk, Gus Van Sant stands among the great international directors, equally at home in Hollywood and the avant-garde. Examining his films thematically, this book finds consistency of vision in Van Sant's unique approach to cinema, which deploys postmodernist techniques such as appropriation, nonlinear narrative, and queering--not in the service of the chic but to apply an all-inclusive viewpoint to ageless tales of life, love and death. Van Sant's films are viewed through a multi-genre prism, including the work of Bruce Weber and Derek Jarman, the westerns of Sam Peckinpah, the music of the Velvet Underground and Nirvana, the fiction of Sam D'Allesandro, and especially the "cut-up"/collage practice of intertextual authorship pioneered by William Burroughs.
The Springdale Stories Eric
Reprint of the original, first published in 1871.
The Criminology of Boxing, Violence and Desistance
This perceptive study explores the extent to which boxing has the potential to reduce violent attitudes among young offenders. Jump assesses conflicting evidence and presents in-depth case studies of fighters to ask whether boxing’s values of discipline and respect can create a support network that helps young men refrain from reoffending.
Chivalric Stories as Children's Literature
Knights and ladies, giants and dragons, tournaments, battles, quests and crusades are commonplace in stories for children. This book examines how late Victorians and Edwardians retold medieval narratives of chivalry--epics, romances, sagas, legends and ballads. Stories of Beowulf, Arthur, Gawain, St. George, Roland, Robin Hood and many more thrilled and instructed children, and encouraged adult reading. Lavish volumes and schoolbooks of the era featured illustrated texts, many by major artists. Children's books, an essential part of Edwardian publishing, were disseminated throughout the English-speaking world. Many are being reprinted today. This book examines related contexts of Medievalism expressed in painting, architecture, music and public celebrations, and the works of major authors, including Sir Walter Scott, Tennyson, Longfellow and William Morris. The book explores national identity expressed through literature, ideals of honor and valor in the years before World War I, and how childhood reading influenced 20th-century writers as diverse as C. S. Lewis, J. R. R. Tolkien, Siegfried Sassoon, David Jones, Graham Greene, Ian Fleming and John Le Carre.
Getting Life
"On August 13, 1986 ... Michael Morton went to work at his usual time. By the end of the day, his wife Christine had been savagely bludgeoned to death in the couple's bed--and the Williamson County Sheriff's office in Texas wasted no time in pinning her murder on [him] ... Michael was swiftly sentenced to life in prison for a crime he had not committed ... It would take twenty-five years--and thousands of hours of effort on the part of Michael's lawyers, including the team at the New York-based Innocence Project--before DNA evidence was brought to light that would ultimately set Michael free"--
