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|a Kissell, Robert,
|d 1967-
|e author.
|0 http://id.loc.gov/authorities/names/n2002117429
|1 http://isni.org/isni/000000003434999X.
|
| 245 |
1 |
0 |
|a Optimal sports math, statistics, and fantasy /
|c Robert Kissell and Jim Poserina.
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| 264 |
|
1 |
|a London :
|b Academic Press,
|c [2017]
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| 264 |
|
4 |
|c ©2017.
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| 300 |
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|a 1 online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent.
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|a computer
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|2 rdamedia.
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| 338 |
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|a online resource
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| 504 |
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|a Includes bibliographical references and index.
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| 505 |
0 |
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|6 880-01
|a Front Cover; Optimal Sports Math, Statistics, and Fantasy; Copyright Page; Contents; Biographical Information; 1 How They Play the Game; Bibliography; 2 Regression Models; 2.1 Introduction; 2.2 Mathematical Models; 2.3 Linear Regression; Estimating Parameters; Estimated Parameters; Se(bk): Standard Error of the Parameter; Regression Error; R-Square (R2); t-Stat; F-Value; Regression Model Requirements; 2.4 Regression Metrics; Regression Analysis Statistics; t-Test; R2 Goodness of Fit; F-Test; Probability Home Team Wins; Matrix Algebra Techniques; Estimate Parameters.
|
| 505 |
8 |
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|a Standard Normal DistributionStudent's t-Distribution; Log-Normal Distribution; Uniform Distribution; Exponential Distribution; Chi-Square Distribution; Logistic Distribution; Triangular Distribution; Discrete Distributions; Binomial Distribution; Poisson Distribution; 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; Endnote; References; 5 Sports Prediction Models; 5.1 Introduction; 5.2 Game Scores Model; Description.
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| 505 |
8 |
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|a Model FormSolving the Model; Estimating Home Team Winning Spread; Estimating Probability; Calculating Probability That the Home Team Wins; Calculating Probability That the Home Team Wins by a Specified Score; 5.3 Team Statistics Model; Description; Model Form; Solving the Model; Estimating Home Team Winning Spread; Estimating Probability; Calculating Probability That the Home Team Wins; Calculating Probability That the Home Team Wins by a Specified Score; 5.4 Logistic Probability Model; Description; Model Form; Solving the Model; Estimating Home Team Winning Probability.
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| 505 |
8 |
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|a Estimating Home Team Winning Spread5.5 Team Ratings Model; Description; Model Form; Estimating Home Team Winning Spread; Estimating Probability; Calculating Probability That the Home Team Wins; Calculating Probability That the Home Team Wins by a Specified Score; 5.6 Logit Spread Model; Description; Model Form; Solving the Model; Estimating Home Team Winning Spread; Estimating Probability; 5.7 Logit Points Model; Description; Model Form; 5.8 Estimating Parameters; Estimating Home Team Points; Estimating Away Team Points; Estimating Home Team Winning Spread.
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| 588 |
0 |
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|a Vendor-supplied metadata.
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| 650 |
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|a Sports
|x Statistical methods.
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| 650 |
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0 |
|a Sports
|x Mathematical models.
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| 650 |
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0 |
|a Sports
|v Statistics.
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| 650 |
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0 |
|a Sports
|x Mathematics.
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| 650 |
|
7 |
|a Sports.
|2 fast
|0 (OCoLC)fst01130432.
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| 650 |
|
7 |
|a Sports
|x Mathematical models.
|2 fast
|0 (OCoLC)fst01130477.
|
| 650 |
|
7 |
|a Sports
|x Mathematics.
|2 fast
|0 (OCoLC)fst01130478.
|
| 650 |
|
7 |
|a Sports
|x Statistical methods.
|2 fast
|0 (OCoLC)fst01130536.
|
| 655 |
|
7 |
|a Statistics.
|2 fast
|0 (OCoLC)fst01423727.
|
| 700 |
1 |
|
|a Poserina, Jim,
|e author.
|
| 776 |
0 |
8 |
|i Print version:
|a Kissell, Robert, 1967-
|t Optimal sports math, statistics, and fantasy.
|d London : Academic Press, [2017]
|z 0128051639
|z 9780128051634
|w (OCoLC)959880101.
|
| 856 |
4 |
0 |
|u https://colorado.idm.oclc.org/login?url=https://www.sciencedirect.com/science/book/9780128051634
|z Full Text (via ScienceDirect)
|
| 880 |
0 |
|
|6 505-01/(S
|a Compute Standard Errors of βR2 Statistic; F-Statistic; Probability Home Team Wins; 2.5 Log-Regression Model; Example: Log-Transformation; 2.6 Nonlinear Regression Model; 2.7 Conclusions; References; 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; References; 4 Advanced Math and Statistics; 4.1 Introduction; 4.2 Probability and Statistics; Probability Distributions; Descriptive Statistics; Probability Distribution Functions; Continuous Distribution Functions; Normal Distribution.
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