Can machine learning algorithms predict sports scores or plays?












38












$begingroup$


I have a variety of NFL datasets that I think might make a good side-project, but I haven't done anything with them just yet.



Coming to this site made me think of machine learning algorithms and I wondering how good they might be at either predicting the outcome of football games or even the next play.



It seems to me that there would be some trends that could be identified - on 3rd down and 1, a team with a strong running back theoretically should have a tendency to run the ball in that situation.



Scoring might be more difficult to predict, but the winning team might be.



My question is whether these are good questions to throw at a machine learning algorithm. It could be that a thousand people have tried it before, but the nature of sports makes it an unreliable topic.










share|improve this question











$endgroup$

















    38












    $begingroup$


    I have a variety of NFL datasets that I think might make a good side-project, but I haven't done anything with them just yet.



    Coming to this site made me think of machine learning algorithms and I wondering how good they might be at either predicting the outcome of football games or even the next play.



    It seems to me that there would be some trends that could be identified - on 3rd down and 1, a team with a strong running back theoretically should have a tendency to run the ball in that situation.



    Scoring might be more difficult to predict, but the winning team might be.



    My question is whether these are good questions to throw at a machine learning algorithm. It could be that a thousand people have tried it before, but the nature of sports makes it an unreliable topic.










    share|improve this question











    $endgroup$















      38












      38








      38


      29



      $begingroup$


      I have a variety of NFL datasets that I think might make a good side-project, but I haven't done anything with them just yet.



      Coming to this site made me think of machine learning algorithms and I wondering how good they might be at either predicting the outcome of football games or even the next play.



      It seems to me that there would be some trends that could be identified - on 3rd down and 1, a team with a strong running back theoretically should have a tendency to run the ball in that situation.



      Scoring might be more difficult to predict, but the winning team might be.



      My question is whether these are good questions to throw at a machine learning algorithm. It could be that a thousand people have tried it before, but the nature of sports makes it an unreliable topic.










      share|improve this question











      $endgroup$




      I have a variety of NFL datasets that I think might make a good side-project, but I haven't done anything with them just yet.



      Coming to this site made me think of machine learning algorithms and I wondering how good they might be at either predicting the outcome of football games or even the next play.



      It seems to me that there would be some trends that could be identified - on 3rd down and 1, a team with a strong running back theoretically should have a tendency to run the ball in that situation.



      Scoring might be more difficult to predict, but the winning team might be.



      My question is whether these are good questions to throw at a machine learning algorithm. It could be that a thousand people have tried it before, but the nature of sports makes it an unreliable topic.







      machine-learning sports






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Mar 2 '15 at 12:33









      lsdr

      33319




      33319










      asked Jun 10 '14 at 10:58









      Steve KallestadSteve Kallestad

      2,52131539




      2,52131539






















          10 Answers
          10






          active

          oldest

          votes


















          16












          $begingroup$

          There are a lot of good questions about Football (and sports, in general) that would be awesome to throw to an algorithm and see what comes out. The tricky part is to know what to throw to the algorithm.



          A team with a good RB could just pass on 3rd-and-short just because the opponents would probably expect run, for instance. So, in order to actually produce some worthy results, I'd break the problem in smaller pieces and analyse them statistically while throwing them to the machines.



          There are a few (good) websites that try to do the same, you should check'em out and use whatever they found to help you out:




          • Football Outsiders

          • Advanced Football Analytics


          And if you truly want to explore Sports Data Analysis, you should definitely check the Sloan Sports Conference videos. There's a lot of them spread on Youtube.






          share|improve this answer











          $endgroup$





















            12












            $begingroup$

            Yes. Why not?!
            With so much of data being recorded in each sport in each game, smart use of data could lead us to obtain important insights regarding player performance.



            Some examples:





            • Baseball: In the movie Moneyball (which is an adaptation of the Moneyball book), Brad Pitt plays a character who analyses player statistics to come up with a team that performs tremendously well! It was a depiction of the real-life story of Oakland Athletics baseball team. For more info, http://www.theatlantic.com/entertainment/archive/2013/09/forget-2002-this-years-oakland-as-are-the-real-em-moneyball-em-team/279927/


            • Cricket: SAP Labs has come up with an auction analytics tool that has given insights about impact players to buy in the 2014 Indian Premier League auction for the Kolkata Knight Riders team, which eventually went on to win the 2014 IPL Championship. For more info, http://scn.sap.com/community/hana-in-memory/blog/2014/06/10/sap-hana-academy-cricket-demo--how-sap-hana-powered-the-kolkata-knight-riders-to-ipl-championship


            So, yes, statistical analysis of the player records can give us insights about which players are more likely to perform but not which players will perform. So, machine learning, a close cousin of statistical analysis will be proving to be a game changer.






            share|improve this answer











            $endgroup$





















              8












              $begingroup$

              Definitely they can.
              I can target you to a nice paper. Once I used it for soccer league results prediction algorithm implementation, primarily aiming at having some value against bookmakers.



              From paper's abstract:




              a Bayesian dynamic generalized model to estimate the time dependent skills of all teams in a league, and to predict next weekend's soccer matches.




              Keywords:




              Dynamic Models, Generalized Linear Models, Graphical Models, Markov
              Chain Monte Carlo Methods, Prediction of Soccer Matches




              Citation:




              Rue, Havard, and Oyvind Salvesen. "Prediction and retrospective analysis of soccer matches in a league." Journal of the Royal Statistical Society: Series D (The Statistician) 49.3 (2000): 399-418.







              share|improve this answer











              $endgroup$





















                6












                $begingroup$

                Machine learning and statistical techniques can improve the forecast, but nobody can predict the real result.



                There was a kaggle competition a few month ago about predicting the 2014 NCAA Tournament. You can read the Competition Forum to get a better idea on what people did and what results did they achieve.






                share|improve this answer









                $endgroup$





















                  6












                  $begingroup$

                  It has been shown before that machine learning techniques can be applied for predicting sport results. Simple google search should give you a bunch of results.



                  However, it has also been showed (for NFL btw) that very complex predictive models, simple predictive models, questioning people, or crowd knowledge by utilising betting info, they all perform more or less the same. Source: "Everything is obvious once you know the answer - How common sense Fails", Chapter 7, by Duncan Watts.






                  share|improve this answer









                  $endgroup$













                  • $begingroup$
                    Interesting. The reason I asked the question is that I wondered if something similar to the "gambler's fallacy" (or even gf itself). I thought there might be a chance it had already been proven to be a fruitless venture. Still - these other answers are intriguing.
                    $endgroup$
                    – Steve Kallestad
                    Jun 10 '14 at 11:56





















                  5












                  $begingroup$

                  Michael Maouboussin, in his book, "The Success Equation," looks at differentiating luck from skill in various endeavors, including sports. He actually ranks sports by the amount of luck that contributes to performance in the different sports (p. 23) and about 2/3 of performance in football is attributable to skill. By contrast, I used MM's technique to analyze performance in Formula 1 racing, and found that 60% is attributable to skill (less than I was expecting.)



                  That said, it seems this kind of analysis would imply that a sufficiently detailed and crafted feature set would allow ML algorithms to predict performance of NFL teams, perhaps even to the play level, with the caveat that significant variance will still exist because of the influence of luck in the game.






                  share|improve this answer









                  $endgroup$





















                    4












                    $begingroup$

                    I have read some about it and I had the following blog in mind:



                    http://fellgernon.tumblr.com/post/46117939292/predicting-who-will-win-a-nfl-match-at-half-time#.UtehM7TWtQg



                    This blog deals with the prediction of a NFL match after the half time is already over. The prediction is 80% accurate with simple GLM model.



                    I do not know if that is suitable for soccer.






                    share|improve this answer









                    $endgroup$





















                      4












                      $begingroup$

                      I've done some research in this area. I've found first order Markov chains work well for predicting within game scoring dynamics across a variety of sports.



                      You can read in more detail here:
                      http://www.epjdatascience.com/content/3/1/4






                      share|improve this answer









                      $endgroup$





















                        4












                        $begingroup$

                        They can't predict, but they can tell you the most likely result. There's an study about this kind of approach from Etienne - Predicting Who Will Win the World Cup with Wolfram Language. This is a very detailed study, so you can check all the methodology used to get the predictions.



                        Interesting enough, 11 from 15 matches were correct!




                        As one might expect, Brazil is the favorite, with a probability to win of 42.5%. This striking result is due to the fact that Brazil has both the highest Elo ranking and plays at home.




                        (Let's go Brazil!)






                        share|improve this answer









                        $endgroup$





















                          3












                          $begingroup$

                          A lot of people have stressed about what are the things that can be predicted in their answers. Now, with the fascination for deep learning, you could, for example, use RNN's(say LSTM) to predict outcomes for sports problems that are based on time. These are state of the art and beat traditional models hands down.






                          share|improve this answer









                          $endgroup$












                            protected by Community Nov 29 '16 at 10:59



                            Thank you for your interest in this question.
                            Because it has attracted low-quality or spam answers that had to be removed, posting an answer now requires 10 reputation on this site (the association bonus does not count).



                            Would you like to answer one of these unanswered questions instead?














                            10 Answers
                            10






                            active

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                            10 Answers
                            10






                            active

                            oldest

                            votes









                            active

                            oldest

                            votes






                            active

                            oldest

                            votes









                            16












                            $begingroup$

                            There are a lot of good questions about Football (and sports, in general) that would be awesome to throw to an algorithm and see what comes out. The tricky part is to know what to throw to the algorithm.



                            A team with a good RB could just pass on 3rd-and-short just because the opponents would probably expect run, for instance. So, in order to actually produce some worthy results, I'd break the problem in smaller pieces and analyse them statistically while throwing them to the machines.



                            There are a few (good) websites that try to do the same, you should check'em out and use whatever they found to help you out:




                            • Football Outsiders

                            • Advanced Football Analytics


                            And if you truly want to explore Sports Data Analysis, you should definitely check the Sloan Sports Conference videos. There's a lot of them spread on Youtube.






                            share|improve this answer











                            $endgroup$


















                              16












                              $begingroup$

                              There are a lot of good questions about Football (and sports, in general) that would be awesome to throw to an algorithm and see what comes out. The tricky part is to know what to throw to the algorithm.



                              A team with a good RB could just pass on 3rd-and-short just because the opponents would probably expect run, for instance. So, in order to actually produce some worthy results, I'd break the problem in smaller pieces and analyse them statistically while throwing them to the machines.



                              There are a few (good) websites that try to do the same, you should check'em out and use whatever they found to help you out:




                              • Football Outsiders

                              • Advanced Football Analytics


                              And if you truly want to explore Sports Data Analysis, you should definitely check the Sloan Sports Conference videos. There's a lot of them spread on Youtube.






                              share|improve this answer











                              $endgroup$
















                                16












                                16








                                16





                                $begingroup$

                                There are a lot of good questions about Football (and sports, in general) that would be awesome to throw to an algorithm and see what comes out. The tricky part is to know what to throw to the algorithm.



                                A team with a good RB could just pass on 3rd-and-short just because the opponents would probably expect run, for instance. So, in order to actually produce some worthy results, I'd break the problem in smaller pieces and analyse them statistically while throwing them to the machines.



                                There are a few (good) websites that try to do the same, you should check'em out and use whatever they found to help you out:




                                • Football Outsiders

                                • Advanced Football Analytics


                                And if you truly want to explore Sports Data Analysis, you should definitely check the Sloan Sports Conference videos. There's a lot of them spread on Youtube.






                                share|improve this answer











                                $endgroup$



                                There are a lot of good questions about Football (and sports, in general) that would be awesome to throw to an algorithm and see what comes out. The tricky part is to know what to throw to the algorithm.



                                A team with a good RB could just pass on 3rd-and-short just because the opponents would probably expect run, for instance. So, in order to actually produce some worthy results, I'd break the problem in smaller pieces and analyse them statistically while throwing them to the machines.



                                There are a few (good) websites that try to do the same, you should check'em out and use whatever they found to help you out:




                                • Football Outsiders

                                • Advanced Football Analytics


                                And if you truly want to explore Sports Data Analysis, you should definitely check the Sloan Sports Conference videos. There's a lot of them spread on Youtube.







                                share|improve this answer














                                share|improve this answer



                                share|improve this answer








                                edited 42 mins ago

























                                answered Jun 10 '14 at 17:15









                                lsdrlsdr

                                33319




                                33319























                                    12












                                    $begingroup$

                                    Yes. Why not?!
                                    With so much of data being recorded in each sport in each game, smart use of data could lead us to obtain important insights regarding player performance.



                                    Some examples:





                                    • Baseball: In the movie Moneyball (which is an adaptation of the Moneyball book), Brad Pitt plays a character who analyses player statistics to come up with a team that performs tremendously well! It was a depiction of the real-life story of Oakland Athletics baseball team. For more info, http://www.theatlantic.com/entertainment/archive/2013/09/forget-2002-this-years-oakland-as-are-the-real-em-moneyball-em-team/279927/


                                    • Cricket: SAP Labs has come up with an auction analytics tool that has given insights about impact players to buy in the 2014 Indian Premier League auction for the Kolkata Knight Riders team, which eventually went on to win the 2014 IPL Championship. For more info, http://scn.sap.com/community/hana-in-memory/blog/2014/06/10/sap-hana-academy-cricket-demo--how-sap-hana-powered-the-kolkata-knight-riders-to-ipl-championship


                                    So, yes, statistical analysis of the player records can give us insights about which players are more likely to perform but not which players will perform. So, machine learning, a close cousin of statistical analysis will be proving to be a game changer.






                                    share|improve this answer











                                    $endgroup$


















                                      12












                                      $begingroup$

                                      Yes. Why not?!
                                      With so much of data being recorded in each sport in each game, smart use of data could lead us to obtain important insights regarding player performance.



                                      Some examples:





                                      • Baseball: In the movie Moneyball (which is an adaptation of the Moneyball book), Brad Pitt plays a character who analyses player statistics to come up with a team that performs tremendously well! It was a depiction of the real-life story of Oakland Athletics baseball team. For more info, http://www.theatlantic.com/entertainment/archive/2013/09/forget-2002-this-years-oakland-as-are-the-real-em-moneyball-em-team/279927/


                                      • Cricket: SAP Labs has come up with an auction analytics tool that has given insights about impact players to buy in the 2014 Indian Premier League auction for the Kolkata Knight Riders team, which eventually went on to win the 2014 IPL Championship. For more info, http://scn.sap.com/community/hana-in-memory/blog/2014/06/10/sap-hana-academy-cricket-demo--how-sap-hana-powered-the-kolkata-knight-riders-to-ipl-championship


                                      So, yes, statistical analysis of the player records can give us insights about which players are more likely to perform but not which players will perform. So, machine learning, a close cousin of statistical analysis will be proving to be a game changer.






                                      share|improve this answer











                                      $endgroup$
















                                        12












                                        12








                                        12





                                        $begingroup$

                                        Yes. Why not?!
                                        With so much of data being recorded in each sport in each game, smart use of data could lead us to obtain important insights regarding player performance.



                                        Some examples:





                                        • Baseball: In the movie Moneyball (which is an adaptation of the Moneyball book), Brad Pitt plays a character who analyses player statistics to come up with a team that performs tremendously well! It was a depiction of the real-life story of Oakland Athletics baseball team. For more info, http://www.theatlantic.com/entertainment/archive/2013/09/forget-2002-this-years-oakland-as-are-the-real-em-moneyball-em-team/279927/


                                        • Cricket: SAP Labs has come up with an auction analytics tool that has given insights about impact players to buy in the 2014 Indian Premier League auction for the Kolkata Knight Riders team, which eventually went on to win the 2014 IPL Championship. For more info, http://scn.sap.com/community/hana-in-memory/blog/2014/06/10/sap-hana-academy-cricket-demo--how-sap-hana-powered-the-kolkata-knight-riders-to-ipl-championship


                                        So, yes, statistical analysis of the player records can give us insights about which players are more likely to perform but not which players will perform. So, machine learning, a close cousin of statistical analysis will be proving to be a game changer.






                                        share|improve this answer











                                        $endgroup$



                                        Yes. Why not?!
                                        With so much of data being recorded in each sport in each game, smart use of data could lead us to obtain important insights regarding player performance.



                                        Some examples:





                                        • Baseball: In the movie Moneyball (which is an adaptation of the Moneyball book), Brad Pitt plays a character who analyses player statistics to come up with a team that performs tremendously well! It was a depiction of the real-life story of Oakland Athletics baseball team. For more info, http://www.theatlantic.com/entertainment/archive/2013/09/forget-2002-this-years-oakland-as-are-the-real-em-moneyball-em-team/279927/


                                        • Cricket: SAP Labs has come up with an auction analytics tool that has given insights about impact players to buy in the 2014 Indian Premier League auction for the Kolkata Knight Riders team, which eventually went on to win the 2014 IPL Championship. For more info, http://scn.sap.com/community/hana-in-memory/blog/2014/06/10/sap-hana-academy-cricket-demo--how-sap-hana-powered-the-kolkata-knight-riders-to-ipl-championship


                                        So, yes, statistical analysis of the player records can give us insights about which players are more likely to perform but not which players will perform. So, machine learning, a close cousin of statistical analysis will be proving to be a game changer.







                                        share|improve this answer














                                        share|improve this answer



                                        share|improve this answer








                                        edited Nov 30 '16 at 23:07









                                        Society of Data Scientists

                                        504513




                                        504513










                                        answered Jun 10 '14 at 16:25









                                        bingabinga

                                        64447




                                        64447























                                            8












                                            $begingroup$

                                            Definitely they can.
                                            I can target you to a nice paper. Once I used it for soccer league results prediction algorithm implementation, primarily aiming at having some value against bookmakers.



                                            From paper's abstract:




                                            a Bayesian dynamic generalized model to estimate the time dependent skills of all teams in a league, and to predict next weekend's soccer matches.




                                            Keywords:




                                            Dynamic Models, Generalized Linear Models, Graphical Models, Markov
                                            Chain Monte Carlo Methods, Prediction of Soccer Matches




                                            Citation:




                                            Rue, Havard, and Oyvind Salvesen. "Prediction and retrospective analysis of soccer matches in a league." Journal of the Royal Statistical Society: Series D (The Statistician) 49.3 (2000): 399-418.







                                            share|improve this answer











                                            $endgroup$


















                                              8












                                              $begingroup$

                                              Definitely they can.
                                              I can target you to a nice paper. Once I used it for soccer league results prediction algorithm implementation, primarily aiming at having some value against bookmakers.



                                              From paper's abstract:




                                              a Bayesian dynamic generalized model to estimate the time dependent skills of all teams in a league, and to predict next weekend's soccer matches.




                                              Keywords:




                                              Dynamic Models, Generalized Linear Models, Graphical Models, Markov
                                              Chain Monte Carlo Methods, Prediction of Soccer Matches




                                              Citation:




                                              Rue, Havard, and Oyvind Salvesen. "Prediction and retrospective analysis of soccer matches in a league." Journal of the Royal Statistical Society: Series D (The Statistician) 49.3 (2000): 399-418.







                                              share|improve this answer











                                              $endgroup$
















                                                8












                                                8








                                                8





                                                $begingroup$

                                                Definitely they can.
                                                I can target you to a nice paper. Once I used it for soccer league results prediction algorithm implementation, primarily aiming at having some value against bookmakers.



                                                From paper's abstract:




                                                a Bayesian dynamic generalized model to estimate the time dependent skills of all teams in a league, and to predict next weekend's soccer matches.




                                                Keywords:




                                                Dynamic Models, Generalized Linear Models, Graphical Models, Markov
                                                Chain Monte Carlo Methods, Prediction of Soccer Matches




                                                Citation:




                                                Rue, Havard, and Oyvind Salvesen. "Prediction and retrospective analysis of soccer matches in a league." Journal of the Royal Statistical Society: Series D (The Statistician) 49.3 (2000): 399-418.







                                                share|improve this answer











                                                $endgroup$



                                                Definitely they can.
                                                I can target you to a nice paper. Once I used it for soccer league results prediction algorithm implementation, primarily aiming at having some value against bookmakers.



                                                From paper's abstract:




                                                a Bayesian dynamic generalized model to estimate the time dependent skills of all teams in a league, and to predict next weekend's soccer matches.




                                                Keywords:




                                                Dynamic Models, Generalized Linear Models, Graphical Models, Markov
                                                Chain Monte Carlo Methods, Prediction of Soccer Matches




                                                Citation:




                                                Rue, Havard, and Oyvind Salvesen. "Prediction and retrospective analysis of soccer matches in a league." Journal of the Royal Statistical Society: Series D (The Statistician) 49.3 (2000): 399-418.








                                                share|improve this answer














                                                share|improve this answer



                                                share|improve this answer








                                                edited Jun 25 '14 at 16:03









                                                Air

                                                582619




                                                582619










                                                answered Jun 10 '14 at 11:37









                                                IharSIharS

                                                2,48352241




                                                2,48352241























                                                    6












                                                    $begingroup$

                                                    Machine learning and statistical techniques can improve the forecast, but nobody can predict the real result.



                                                    There was a kaggle competition a few month ago about predicting the 2014 NCAA Tournament. You can read the Competition Forum to get a better idea on what people did and what results did they achieve.






                                                    share|improve this answer









                                                    $endgroup$


















                                                      6












                                                      $begingroup$

                                                      Machine learning and statistical techniques can improve the forecast, but nobody can predict the real result.



                                                      There was a kaggle competition a few month ago about predicting the 2014 NCAA Tournament. You can read the Competition Forum to get a better idea on what people did and what results did they achieve.






                                                      share|improve this answer









                                                      $endgroup$
















                                                        6












                                                        6








                                                        6





                                                        $begingroup$

                                                        Machine learning and statistical techniques can improve the forecast, but nobody can predict the real result.



                                                        There was a kaggle competition a few month ago about predicting the 2014 NCAA Tournament. You can read the Competition Forum to get a better idea on what people did and what results did they achieve.






                                                        share|improve this answer









                                                        $endgroup$



                                                        Machine learning and statistical techniques can improve the forecast, but nobody can predict the real result.



                                                        There was a kaggle competition a few month ago about predicting the 2014 NCAA Tournament. You can read the Competition Forum to get a better idea on what people did and what results did they achieve.







                                                        share|improve this answer












                                                        share|improve this answer



                                                        share|improve this answer










                                                        answered Jun 10 '14 at 11:39









                                                        StanpolStanpol

                                                        55226




                                                        55226























                                                            6












                                                            $begingroup$

                                                            It has been shown before that machine learning techniques can be applied for predicting sport results. Simple google search should give you a bunch of results.



                                                            However, it has also been showed (for NFL btw) that very complex predictive models, simple predictive models, questioning people, or crowd knowledge by utilising betting info, they all perform more or less the same. Source: "Everything is obvious once you know the answer - How common sense Fails", Chapter 7, by Duncan Watts.






                                                            share|improve this answer









                                                            $endgroup$













                                                            • $begingroup$
                                                              Interesting. The reason I asked the question is that I wondered if something similar to the "gambler's fallacy" (or even gf itself). I thought there might be a chance it had already been proven to be a fruitless venture. Still - these other answers are intriguing.
                                                              $endgroup$
                                                              – Steve Kallestad
                                                              Jun 10 '14 at 11:56


















                                                            6












                                                            $begingroup$

                                                            It has been shown before that machine learning techniques can be applied for predicting sport results. Simple google search should give you a bunch of results.



                                                            However, it has also been showed (for NFL btw) that very complex predictive models, simple predictive models, questioning people, or crowd knowledge by utilising betting info, they all perform more or less the same. Source: "Everything is obvious once you know the answer - How common sense Fails", Chapter 7, by Duncan Watts.






                                                            share|improve this answer









                                                            $endgroup$













                                                            • $begingroup$
                                                              Interesting. The reason I asked the question is that I wondered if something similar to the "gambler's fallacy" (or even gf itself). I thought there might be a chance it had already been proven to be a fruitless venture. Still - these other answers are intriguing.
                                                              $endgroup$
                                                              – Steve Kallestad
                                                              Jun 10 '14 at 11:56
















                                                            6












                                                            6








                                                            6





                                                            $begingroup$

                                                            It has been shown before that machine learning techniques can be applied for predicting sport results. Simple google search should give you a bunch of results.



                                                            However, it has also been showed (for NFL btw) that very complex predictive models, simple predictive models, questioning people, or crowd knowledge by utilising betting info, they all perform more or less the same. Source: "Everything is obvious once you know the answer - How common sense Fails", Chapter 7, by Duncan Watts.






                                                            share|improve this answer









                                                            $endgroup$



                                                            It has been shown before that machine learning techniques can be applied for predicting sport results. Simple google search should give you a bunch of results.



                                                            However, it has also been showed (for NFL btw) that very complex predictive models, simple predictive models, questioning people, or crowd knowledge by utilising betting info, they all perform more or less the same. Source: "Everything is obvious once you know the answer - How common sense Fails", Chapter 7, by Duncan Watts.







                                                            share|improve this answer












                                                            share|improve this answer



                                                            share|improve this answer










                                                            answered Jun 10 '14 at 11:49









                                                            iliasfliliasfl

                                                            526416




                                                            526416












                                                            • $begingroup$
                                                              Interesting. The reason I asked the question is that I wondered if something similar to the "gambler's fallacy" (or even gf itself). I thought there might be a chance it had already been proven to be a fruitless venture. Still - these other answers are intriguing.
                                                              $endgroup$
                                                              – Steve Kallestad
                                                              Jun 10 '14 at 11:56




















                                                            • $begingroup$
                                                              Interesting. The reason I asked the question is that I wondered if something similar to the "gambler's fallacy" (or even gf itself). I thought there might be a chance it had already been proven to be a fruitless venture. Still - these other answers are intriguing.
                                                              $endgroup$
                                                              – Steve Kallestad
                                                              Jun 10 '14 at 11:56


















                                                            $begingroup$
                                                            Interesting. The reason I asked the question is that I wondered if something similar to the "gambler's fallacy" (or even gf itself). I thought there might be a chance it had already been proven to be a fruitless venture. Still - these other answers are intriguing.
                                                            $endgroup$
                                                            – Steve Kallestad
                                                            Jun 10 '14 at 11:56






                                                            $begingroup$
                                                            Interesting. The reason I asked the question is that I wondered if something similar to the "gambler's fallacy" (or even gf itself). I thought there might be a chance it had already been proven to be a fruitless venture. Still - these other answers are intriguing.
                                                            $endgroup$
                                                            – Steve Kallestad
                                                            Jun 10 '14 at 11:56













                                                            5












                                                            $begingroup$

                                                            Michael Maouboussin, in his book, "The Success Equation," looks at differentiating luck from skill in various endeavors, including sports. He actually ranks sports by the amount of luck that contributes to performance in the different sports (p. 23) and about 2/3 of performance in football is attributable to skill. By contrast, I used MM's technique to analyze performance in Formula 1 racing, and found that 60% is attributable to skill (less than I was expecting.)



                                                            That said, it seems this kind of analysis would imply that a sufficiently detailed and crafted feature set would allow ML algorithms to predict performance of NFL teams, perhaps even to the play level, with the caveat that significant variance will still exist because of the influence of luck in the game.






                                                            share|improve this answer









                                                            $endgroup$


















                                                              5












                                                              $begingroup$

                                                              Michael Maouboussin, in his book, "The Success Equation," looks at differentiating luck from skill in various endeavors, including sports. He actually ranks sports by the amount of luck that contributes to performance in the different sports (p. 23) and about 2/3 of performance in football is attributable to skill. By contrast, I used MM's technique to analyze performance in Formula 1 racing, and found that 60% is attributable to skill (less than I was expecting.)



                                                              That said, it seems this kind of analysis would imply that a sufficiently detailed and crafted feature set would allow ML algorithms to predict performance of NFL teams, perhaps even to the play level, with the caveat that significant variance will still exist because of the influence of luck in the game.






                                                              share|improve this answer









                                                              $endgroup$
















                                                                5












                                                                5








                                                                5





                                                                $begingroup$

                                                                Michael Maouboussin, in his book, "The Success Equation," looks at differentiating luck from skill in various endeavors, including sports. He actually ranks sports by the amount of luck that contributes to performance in the different sports (p. 23) and about 2/3 of performance in football is attributable to skill. By contrast, I used MM's technique to analyze performance in Formula 1 racing, and found that 60% is attributable to skill (less than I was expecting.)



                                                                That said, it seems this kind of analysis would imply that a sufficiently detailed and crafted feature set would allow ML algorithms to predict performance of NFL teams, perhaps even to the play level, with the caveat that significant variance will still exist because of the influence of luck in the game.






                                                                share|improve this answer









                                                                $endgroup$



                                                                Michael Maouboussin, in his book, "The Success Equation," looks at differentiating luck from skill in various endeavors, including sports. He actually ranks sports by the amount of luck that contributes to performance in the different sports (p. 23) and about 2/3 of performance in football is attributable to skill. By contrast, I used MM's technique to analyze performance in Formula 1 racing, and found that 60% is attributable to skill (less than I was expecting.)



                                                                That said, it seems this kind of analysis would imply that a sufficiently detailed and crafted feature set would allow ML algorithms to predict performance of NFL teams, perhaps even to the play level, with the caveat that significant variance will still exist because of the influence of luck in the game.







                                                                share|improve this answer












                                                                share|improve this answer



                                                                share|improve this answer










                                                                answered Jul 6 '14 at 14:01









                                                                user44202user44202

                                                                512




                                                                512























                                                                    4












                                                                    $begingroup$

                                                                    I have read some about it and I had the following blog in mind:



                                                                    http://fellgernon.tumblr.com/post/46117939292/predicting-who-will-win-a-nfl-match-at-half-time#.UtehM7TWtQg



                                                                    This blog deals with the prediction of a NFL match after the half time is already over. The prediction is 80% accurate with simple GLM model.



                                                                    I do not know if that is suitable for soccer.






                                                                    share|improve this answer









                                                                    $endgroup$


















                                                                      4












                                                                      $begingroup$

                                                                      I have read some about it and I had the following blog in mind:



                                                                      http://fellgernon.tumblr.com/post/46117939292/predicting-who-will-win-a-nfl-match-at-half-time#.UtehM7TWtQg



                                                                      This blog deals with the prediction of a NFL match after the half time is already over. The prediction is 80% accurate with simple GLM model.



                                                                      I do not know if that is suitable for soccer.






                                                                      share|improve this answer









                                                                      $endgroup$
















                                                                        4












                                                                        4








                                                                        4





                                                                        $begingroup$

                                                                        I have read some about it and I had the following blog in mind:



                                                                        http://fellgernon.tumblr.com/post/46117939292/predicting-who-will-win-a-nfl-match-at-half-time#.UtehM7TWtQg



                                                                        This blog deals with the prediction of a NFL match after the half time is already over. The prediction is 80% accurate with simple GLM model.



                                                                        I do not know if that is suitable for soccer.






                                                                        share|improve this answer









                                                                        $endgroup$



                                                                        I have read some about it and I had the following blog in mind:



                                                                        http://fellgernon.tumblr.com/post/46117939292/predicting-who-will-win-a-nfl-match-at-half-time#.UtehM7TWtQg



                                                                        This blog deals with the prediction of a NFL match after the half time is already over. The prediction is 80% accurate with simple GLM model.



                                                                        I do not know if that is suitable for soccer.







                                                                        share|improve this answer












                                                                        share|improve this answer



                                                                        share|improve this answer










                                                                        answered Jun 25 '14 at 14:30









                                                                        adesantosadesantos

                                                                        46328




                                                                        46328























                                                                            4












                                                                            $begingroup$

                                                                            I've done some research in this area. I've found first order Markov chains work well for predicting within game scoring dynamics across a variety of sports.



                                                                            You can read in more detail here:
                                                                            http://www.epjdatascience.com/content/3/1/4






                                                                            share|improve this answer









                                                                            $endgroup$


















                                                                              4












                                                                              $begingroup$

                                                                              I've done some research in this area. I've found first order Markov chains work well for predicting within game scoring dynamics across a variety of sports.



                                                                              You can read in more detail here:
                                                                              http://www.epjdatascience.com/content/3/1/4






                                                                              share|improve this answer









                                                                              $endgroup$
















                                                                                4












                                                                                4








                                                                                4





                                                                                $begingroup$

                                                                                I've done some research in this area. I've found first order Markov chains work well for predicting within game scoring dynamics across a variety of sports.



                                                                                You can read in more detail here:
                                                                                http://www.epjdatascience.com/content/3/1/4






                                                                                share|improve this answer









                                                                                $endgroup$



                                                                                I've done some research in this area. I've found first order Markov chains work well for predicting within game scoring dynamics across a variety of sports.



                                                                                You can read in more detail here:
                                                                                http://www.epjdatascience.com/content/3/1/4







                                                                                share|improve this answer












                                                                                share|improve this answer



                                                                                share|improve this answer










                                                                                answered Jul 3 '14 at 20:51









                                                                                merrittsmerritts

                                                                                611




                                                                                611























                                                                                    4












                                                                                    $begingroup$

                                                                                    They can't predict, but they can tell you the most likely result. There's an study about this kind of approach from Etienne - Predicting Who Will Win the World Cup with Wolfram Language. This is a very detailed study, so you can check all the methodology used to get the predictions.



                                                                                    Interesting enough, 11 from 15 matches were correct!




                                                                                    As one might expect, Brazil is the favorite, with a probability to win of 42.5%. This striking result is due to the fact that Brazil has both the highest Elo ranking and plays at home.




                                                                                    (Let's go Brazil!)






                                                                                    share|improve this answer









                                                                                    $endgroup$


















                                                                                      4












                                                                                      $begingroup$

                                                                                      They can't predict, but they can tell you the most likely result. There's an study about this kind of approach from Etienne - Predicting Who Will Win the World Cup with Wolfram Language. This is a very detailed study, so you can check all the methodology used to get the predictions.



                                                                                      Interesting enough, 11 from 15 matches were correct!




                                                                                      As one might expect, Brazil is the favorite, with a probability to win of 42.5%. This striking result is due to the fact that Brazil has both the highest Elo ranking and plays at home.




                                                                                      (Let's go Brazil!)






                                                                                      share|improve this answer









                                                                                      $endgroup$
















                                                                                        4












                                                                                        4








                                                                                        4





                                                                                        $begingroup$

                                                                                        They can't predict, but they can tell you the most likely result. There's an study about this kind of approach from Etienne - Predicting Who Will Win the World Cup with Wolfram Language. This is a very detailed study, so you can check all the methodology used to get the predictions.



                                                                                        Interesting enough, 11 from 15 matches were correct!




                                                                                        As one might expect, Brazil is the favorite, with a probability to win of 42.5%. This striking result is due to the fact that Brazil has both the highest Elo ranking and plays at home.




                                                                                        (Let's go Brazil!)






                                                                                        share|improve this answer









                                                                                        $endgroup$



                                                                                        They can't predict, but they can tell you the most likely result. There's an study about this kind of approach from Etienne - Predicting Who Will Win the World Cup with Wolfram Language. This is a very detailed study, so you can check all the methodology used to get the predictions.



                                                                                        Interesting enough, 11 from 15 matches were correct!




                                                                                        As one might expect, Brazil is the favorite, with a probability to win of 42.5%. This striking result is due to the fact that Brazil has both the highest Elo ranking and plays at home.




                                                                                        (Let's go Brazil!)







                                                                                        share|improve this answer












                                                                                        share|improve this answer



                                                                                        share|improve this answer










                                                                                        answered Jul 8 '14 at 2:08









                                                                                        mrtorturemrtorture

                                                                                        411




                                                                                        411























                                                                                            3












                                                                                            $begingroup$

                                                                                            A lot of people have stressed about what are the things that can be predicted in their answers. Now, with the fascination for deep learning, you could, for example, use RNN's(say LSTM) to predict outcomes for sports problems that are based on time. These are state of the art and beat traditional models hands down.






                                                                                            share|improve this answer









                                                                                            $endgroup$


















                                                                                              3












                                                                                              $begingroup$

                                                                                              A lot of people have stressed about what are the things that can be predicted in their answers. Now, with the fascination for deep learning, you could, for example, use RNN's(say LSTM) to predict outcomes for sports problems that are based on time. These are state of the art and beat traditional models hands down.






                                                                                              share|improve this answer









                                                                                              $endgroup$
















                                                                                                3












                                                                                                3








                                                                                                3





                                                                                                $begingroup$

                                                                                                A lot of people have stressed about what are the things that can be predicted in their answers. Now, with the fascination for deep learning, you could, for example, use RNN's(say LSTM) to predict outcomes for sports problems that are based on time. These are state of the art and beat traditional models hands down.






                                                                                                share|improve this answer









                                                                                                $endgroup$



                                                                                                A lot of people have stressed about what are the things that can be predicted in their answers. Now, with the fascination for deep learning, you could, for example, use RNN's(say LSTM) to predict outcomes for sports problems that are based on time. These are state of the art and beat traditional models hands down.







                                                                                                share|improve this answer












                                                                                                share|improve this answer



                                                                                                share|improve this answer










                                                                                                answered Jul 22 '16 at 21:19









                                                                                                RamRam

                                                                                                30122




                                                                                                30122

















                                                                                                    protected by Community Nov 29 '16 at 10:59



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