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The Resource Optimal sports math, statistics, and fantasy, Robert Kissell and James Poserina

Optimal sports math, statistics, and fantasy, Robert Kissell and James Poserina

Label
Optimal sports math, statistics, and fantasy
Title
Optimal sports math, statistics, and fantasy
Statement of responsibility
Robert Kissell and James Poserina
Creator
Contributor
Author
Subject
Genre
Language
eng
Cataloging source
CDX
http://library.link/vocab/creatorDate
1967-
http://library.link/vocab/creatorName
Kissell, Robert
Dewey number
796.02/1
Illustrations
illustrations
Index
index present
LC call number
GV741
LC item number
.K577 2017
Literary form
non fiction
Nature of contents
bibliography
http://library.link/vocab/relatedWorkOrContributorName
Poserina, James
http://library.link/vocab/subjectName
  • Sports
  • Sports
  • Sports
Label
Optimal sports math, statistics, and fantasy, Robert Kissell and James Poserina
Instantiates
Publication
Copyright
Bibliography note
Includes bibliographical references and index
Carrier category
volume
Carrier category code
nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • 1. How They Play the Game; Bibliography -- 2. Regression Models -- 2.1 Introduction -- 2.2 Mathematical Models -- 2.3 Linear Regression -- 2.4 Regression Metrics --2.5 Log-Regression Model -- 2.6 Nonlinear Regression Model -- 2.7 Conclusions -- 3. Probability models -- 3.1 Introduction -- 3.2 Data Statistics -- 3.3 Forecasting Models -- 3.4 Probability Models -- 3.5 Logit Model Regression Models -- 3.6 Conclusions -- 4. Advanced Math and Statistics -- 4.1 Introduction -- 4.2 Probability and Statistics -- 4.3 Sampling Techniques -- 4.4 Random Sampling -- 4.5 Sampling With Replacement -- 4.6 Sampling Without Replacement -- 4.7 Bootstrapping Techniques -- 4.8 Jackknife Sampling Techniques -- 4.9 Monte Carlo Simulation -- 4.10 Conclusion -- 5. Sports Prediction Models -- 5.1 Introduction -- 5.2 Game Scores Model -- 5.3 Team Statistics Model -- 5.4 Logistic Probability Model -- 5.5 Team Ratings Model -- 5.6 Logit Spread Model --5.7 Logit Points Model -- 5.8 Estimating Parameters -- 5.9 Conclusions
  • 6. Football-NFL -- 6.1 Game Scores Model -- 6.2 Team Statistics Model -- 6.3 Logistic Probability Model -- 6.4 Team Ratings Model -- 6.5 Logit Spread Model -- 6.6 Logit Points Model -- 6.7 Example -- 6.8 Out-sample Results -- 6.9 Conclusion -- 7. Basketball-NBA -- 7.1 Game Scores Model -- 7.2 Team Statistics Model -- 7.3 Logistic Probability Model -- 7.4 Team Ratings Model -- 7.5 Logit Spread Model -- 7.6 Logit Points Model -- 7.7 Example -- 7.8 Out-Sample Results -- 7.9 Conclusion -- 8.Hockey-NHL --8.1 Game Scores Model -- 8.2 Team Statistics Model -- 8.3 Logistic Probability Model -- 8.4 Team Ratings Model -- 8.5 Logit Spread Model -- 8.6 Logit Points Model -- 8.7 Example -- 8.8 Out-sample Results -- 8.9 Conclusion -- 9. Soccer-MLS -- 9.1 Game Scores Model -- 9.2 Team Statistics Model -- 9.3 Logistic Probability Model -- 9.4 Team Ratings Model -- 9.5 Logit Spread Model -- 9.6 Logit Points Model -- 9.7 Example -- 9.8 Out-sample Results -- 9.9 Conclusion -- 10. Baseball-MLB -- 10.1 Game Scores Model -- 10.2 Team Statistics Model -- 10.3 Logistic Probability Model -- 10.4 Team Ratings Model -- 10.5 Logit Spread Model -- 10.6 Logit Points Model -- 10.7 Example -- 10.8 Out-sample Results -- 10.9 Conclusion -- 11. Statistics in Baseball -- 11.1 Run Creation -- 11.2 Win Probability Added -- 11.3 Conclusion -- 12. Fantasy Sports Models -- 12.1 Introduction -- 12.2 Data Sets -- 12.3 Fantasy Sports Model -- 12.4 Regression Results -- 12.5 Model Results -- 12.6 Conclusion -- 13. Advanced Modeling Techniques -- 13.1 Introduction -- 13.2 Principal Component Analysis -- 13.3 Neural Network -- 13.4 Adaptive Regression Analysis -- 13.5 Conclusion
Control code
ocn987271181
Dimensions
23 cm
Extent
x, 342 pages
Isbn
9780128051634
Media category
unmediated
Media MARC source
rdamedia
Media type code
n
Other physical details
illustrations (some color)
System control number
(OCoLC)987271181
Label
Optimal sports math, statistics, and fantasy, Robert Kissell and James Poserina
Publication
Copyright
Bibliography note
Includes bibliographical references and index
Carrier category
volume
Carrier category code
nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • 1. How They Play the Game; Bibliography -- 2. Regression Models -- 2.1 Introduction -- 2.2 Mathematical Models -- 2.3 Linear Regression -- 2.4 Regression Metrics --2.5 Log-Regression Model -- 2.6 Nonlinear Regression Model -- 2.7 Conclusions -- 3. Probability models -- 3.1 Introduction -- 3.2 Data Statistics -- 3.3 Forecasting Models -- 3.4 Probability Models -- 3.5 Logit Model Regression Models -- 3.6 Conclusions -- 4. Advanced Math and Statistics -- 4.1 Introduction -- 4.2 Probability and Statistics -- 4.3 Sampling Techniques -- 4.4 Random Sampling -- 4.5 Sampling With Replacement -- 4.6 Sampling Without Replacement -- 4.7 Bootstrapping Techniques -- 4.8 Jackknife Sampling Techniques -- 4.9 Monte Carlo Simulation -- 4.10 Conclusion -- 5. Sports Prediction Models -- 5.1 Introduction -- 5.2 Game Scores Model -- 5.3 Team Statistics Model -- 5.4 Logistic Probability Model -- 5.5 Team Ratings Model -- 5.6 Logit Spread Model --5.7 Logit Points Model -- 5.8 Estimating Parameters -- 5.9 Conclusions
  • 6. Football-NFL -- 6.1 Game Scores Model -- 6.2 Team Statistics Model -- 6.3 Logistic Probability Model -- 6.4 Team Ratings Model -- 6.5 Logit Spread Model -- 6.6 Logit Points Model -- 6.7 Example -- 6.8 Out-sample Results -- 6.9 Conclusion -- 7. Basketball-NBA -- 7.1 Game Scores Model -- 7.2 Team Statistics Model -- 7.3 Logistic Probability Model -- 7.4 Team Ratings Model -- 7.5 Logit Spread Model -- 7.6 Logit Points Model -- 7.7 Example -- 7.8 Out-Sample Results -- 7.9 Conclusion -- 8.Hockey-NHL --8.1 Game Scores Model -- 8.2 Team Statistics Model -- 8.3 Logistic Probability Model -- 8.4 Team Ratings Model -- 8.5 Logit Spread Model -- 8.6 Logit Points Model -- 8.7 Example -- 8.8 Out-sample Results -- 8.9 Conclusion -- 9. Soccer-MLS -- 9.1 Game Scores Model -- 9.2 Team Statistics Model -- 9.3 Logistic Probability Model -- 9.4 Team Ratings Model -- 9.5 Logit Spread Model -- 9.6 Logit Points Model -- 9.7 Example -- 9.8 Out-sample Results -- 9.9 Conclusion -- 10. Baseball-MLB -- 10.1 Game Scores Model -- 10.2 Team Statistics Model -- 10.3 Logistic Probability Model -- 10.4 Team Ratings Model -- 10.5 Logit Spread Model -- 10.6 Logit Points Model -- 10.7 Example -- 10.8 Out-sample Results -- 10.9 Conclusion -- 11. Statistics in Baseball -- 11.1 Run Creation -- 11.2 Win Probability Added -- 11.3 Conclusion -- 12. Fantasy Sports Models -- 12.1 Introduction -- 12.2 Data Sets -- 12.3 Fantasy Sports Model -- 12.4 Regression Results -- 12.5 Model Results -- 12.6 Conclusion -- 13. Advanced Modeling Techniques -- 13.1 Introduction -- 13.2 Principal Component Analysis -- 13.3 Neural Network -- 13.4 Adaptive Regression Analysis -- 13.5 Conclusion
Control code
ocn987271181
Dimensions
23 cm
Extent
x, 342 pages
Isbn
9780128051634
Media category
unmediated
Media MARC source
rdamedia
Media type code
n
Other physical details
illustrations (some color)
System control number
(OCoLC)987271181

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