Sports (24, 7, 4 )

1. Sports (24, 7, 4)

2. Sports I • Advanced metric stats are at an all time high in use for selecting players that are best fit for a team. A prime example of this is dramatized in the film Moneyball, where advanced metric stats help a small market team turn into playoff contender • Most elite sports have now embraced big data analytics. We have the IBM SlamTracker tool for tennis tournaments; we use video analytics that track the performance of every player in a football or baseball game, and sensor technology in sports equipment such as basket balls or golf clubs allows us to get feedback (via smart phones and cloud servers) on our game and how to improve it • I think the big thing that made people aware of this was the movie Moneyball, which was about the system behind the MLB. Sports and statistics are two things that people associate with each other but I don't think people understand how they are used to enhance one another.  • movie we watched in INFO-I 101, Moneyball.  • the manager Billy decide which player they should trade in or out base on those data. And they finally boost the team's performance. • he use the big data management tech to analyze the every match and player, which leading him success in the final game. • Most people are probably going to comment about the movie Moneyball so I am going to discuss a lesser known application of big data. The Houston Rockets have been using big data and sports analytics to choose their players for the past 3 to 4 years. It appears to have worked because each year they keep getting better. 

3. Sports II • I believe from here on out, if a professional sports franchise wants to be successful, they will have to embrace big data to maximize their teams potential, if not that franchise will fall behind.  • Though you won't find many teams using data to the extent of the Oakland A's, as portrayed in Moneyball, it is still used in many ways by teams. Each trade and draft pick is influenced by big data. You can also consider sports betting, where the majority of "professionals" will make their picks based on data.  •  I feel Big data in sportsis under utilized. Now, I don't know a whole lot about the topic, but it occurs to me that big data could help us predict turnout of events, plan for future seasons, and what athletes are the best investments. • The St. Louis Cardinals log player statistics of the MLB for a long period of time to examine player trends, strengths, and cycles. As a result, the team has been very successful in the MLB over the past years and continues to compete to championships and the World Series.  • For example, the average NBA salary is $5.15 million per year. Therefore, an organization is going to exercise due diligence when drafting, signing, and paying players. A large amount of research goes into a player’s past statistics, character, durability, body composition, etc. • The first example I can think of is how many analysts and such are being paid to take in massive amounts of data and statistics and draw conclusions about it for that sport. 

4. Sports III • It can also really help the scouting and recruiting aspect of sports by allowing recruiters to compare players and make the best decision for their team based on the actual performance of the players.  • Big data has changed the way people view and play sports today.  • Relationship between sports and big data is the amount of data acquired and how quickly it can be accessed. Many sporting events are televised and numerous statistics on players, teams, coaches, etc. are displayed throughout the game/match.  • It also has a betting aspect that brings in a ton of revenue. • One such application is the use of a military grade sensor within the Houston Rockets basketball arena.  Using this sensor, the Rockets track every second of game time and the movement of each player on the court. • I think that there is a lot of things that could be done to further implement big data into sports such as heart sensors.   

5. Sports IV • One way that sports organizations can use big data is through analyzing players and teams stats to determine trends. These trends can allow the opponents to scheme against them or allow organizations to recruit and hire the players with the "best trends". • One last example that I thought was really interesting is sensor data from race car driving. Using this information from practices and previous races they can make adjustments to their cars to increase performance of specific tracks.  • One technique that is gaining popularity in nearly all sports to capture sports-related data is sensors.  Sensors can be placed in shoes, helmets, mouthpieces, or just about anywhere.  The data captured by these sensors is what is being analyzed to gain knowledge (e.g. fundamentals in sports to make one better, or possibly even predict what a team should do in a given situation etc.).   • it seems that this is one field that should not focus very closely on big data. If a company or team is looking solely at the numbers of a player they will lose focus of his current performance, health, and other important characteristics that constitute a successful player. This just does not seem to be an industry that will succeed through the use of big data. 

6. Sports V • For example in cricket, there are a lot of statistics associated with every ball of  every match and real-time management of this statistics may prove to be cumbersome. Big data can be used not only to manage these statistics but help one to gain knowledge from these statistics. A team or a player can use this knowledge to gain an upper hand over the opposition.  • What began in baseball (see the book/movie 'Moneyball') is now spreading to all commercial professional sports - players and teams can be broken down into quantifiable pieces of data and areas to look at. If one team can find an advantage from a novel computational process, that can turn into a tangible advantage on the field of play, and that in turn can turn into more wins or success or ticket sales from a more exciting product for the fans.  • Statistics can be collected and analysed to better understand what are the critical factors for success and optimum performance, in all facets of elite sport. Preparation, competition, injury prevention and rehabilitation can all benefit by applying this approach. Scouting and recruitment and retention can also be enhanced by these powerful principles. • Technological advances will fuel exponential growth in this area for the foreseeable future, as athletes are continuously monitored by tools as diverse as sports GPS systems, heart rate monitors and daily saliva tests. These statistics and many more like them are high performance sport’s Big Data. • Fans tweet and post about these matches which is used as feedback by football shows. Underlying all this is big money which is an attraction to software and analytics providers. On a whole I feel that sports is an ever growing field which will always depend on big data.

7. Sports VI • But the analysis done or the results inferred will be based on the data from the recent past. Because to decide on the tactics to use against an opponent, it will be foolish to look into a ten year old statistics or videos of that team. • Detailed analysis of the opponent can certainly give you an upper hand in the actual game. This is possible through Big Data. Getting the past results and tactics of the opposition in the last few games or identifying the best player in the opposition and his movements using past match videos will allow the team to plan better and develop a strategy accordingly.Also, identifying the performances of the team members, the moments where the game was lost can be useful to help the team to perform better in upcoming matches. • The opportunities Big Data creates here is splendid. Coaches can find the winning edge. Players can know what is required of them during games, their strategy and sports medics can know what effects the treatments are having. A sport is a business and Big data will help drive it with the number crunching by the administrators.

8. Sports VII • Of the major sports, there is probably more data in baseball than any other sport. This includes basic statistics such as balls, strikes, and runs as well as more obscure statistics such as intentional base on balls and plate appearances per strikeout. The movie Moneyball is the true story of how the Oakland A's baseball team successfully implemented big data-driven management techniques long before Big Data was even a recognized term. They used big data to give themselves a competitive advantage. The statistician and writer, Nate Silver also made a name for himself by crunching numbers for baseball. • Big Data is being used extremely often in the sports field. One way is in with gathering statistics on players and games to track trends. Many elite players are monitored outside of the game on their nutrition, their sleep patterns, and their social media accounts. Sensors have also been used in sports equipment to provide feedback on ways too improve

9. Sports VIII • In the NBA, for example, the introduction of a tracking system (SportVU) in all 30 major arenas has facilitated the gathering of information on athlete and ball movement on the court. • Big Data analytics in sports is affirming many coaching, recruiting and training practices, and showing that many others need reevaluating. It can however only augment or be used to improve more traditional methods and should not be taken as a replacement. • Big Data will obviously have a huge impact on Sports teams as the managers and coaches begin to treat the players more as resources and the decisions become more analytical.  However, I think the biggest benefit for the average person will be in improved visualizations, both at a team level, and down to individual players.  Consider this graphic:http://www.stats.com/sportvu/images_sportvu/SVbk_PlayerTeamEval.jpg • As these visualizations trickle down, I also believe they will have a huge impact on fantasy sports.  The money in fantasy sports is quite large at the moment and there is no doubt in my mind that people will pay extra to get these types of charts, graphs, and other graphics if they believe it will help them in their fantasy leagues. • "Fantasy Football is Glorified Dungeons and Dragons"http://thejockitch.com/2009/10/fantasy-football-is-dungeons-and-dragons/

10. Criminal Justice (10, 6, 3)

11. Criminal Justice I • Agencies like the FBI and CIA probably use big data on the internet to find people who may have been searching for things like bombs and then they keep watch for them.  Also I think big data in criminal justice can help stop the spread of crime by finding the highest crime areas and allocating the most resources to them.  •  I came across a crime fighting technology developed at Rutgers University that recognizes this problem and is using the cyber world to fight problems. The software they developed takes in big data and then uses that crime data to identify and map environmental attractors of crime, calling it "Risk Terrain Modeling." This is interesting and worth investing for because law enforcement agencies all around the world have millions of pieces of crime data sitting in databases with no valuable solution of how to automate where, when, or how the next crime will happen. • Police officers have described the feeling of playing whack-a-mole,"saidCaplan, assistant professor of Criminal Justice and associate director of Rutgers' Center on Public Security. "They identify crime hotspots and deploy resources there to deter illegal activity, only to have it pop up somewhere else or return to the same place once police leave. Hotspots tend to be quite resilient, not because police aren't effective, but because the environments that make certain places suitable for crimes don't change much over time. They remain attractive illegal behavior settings, so illegal behavior returns.Therefore, big data can be used in criminal justice by helping in detecting crime areas.

12. Criminal Justice II • Currently it allows law enforcement agencies to track and monitor crime patterns to predict future crimes and stop them before they are committed.  • A variety of factors impact criminality including socio-cultural background, family, mental illness, etc. With Big Data processing we can improve our understanding of this complex issue and the efficacy of proposed solutions like rehabilitation and deterrence. • Crimes can actually be predicted using Big Data. It can be used an essential tool for figuring out the patterns between crime and potential future locations of crime. This can lead to a safer environment for all.  • Big Data allows for companies to document and share both exploits and fixes to these exploits so the overall security of cyber space can improve.  • Big data is huge when it comes to criminal justice because big data plays a part in solving many crimes. People get caught based on security cameras, their DNA, phone records, cellular towers, text and voice messages, and etc. All of these are forms of big data and big data play a huge role in carrying out justice. • Recently, the US government was able to catch a notorious Russian hacker named Sasha Panin. With the help from big data, the FBI was able to track and arrest Panin, after he left Russia. 

13. Criminal Justice III • After watching a TED talk about Big Data and fighting crime, it gave me a better understanding of just how important this data can be in the coming years. • A new universal risk assessment tool was created for judges with 9 aspects that they found to be the most important. Once answered, they will get feedback on things such as the new criminal activity score, the likelihood that the person will come back to court and the recommendation it has produced for the judge.  • So it is necessary to manage crime in a way that produces long-term positive outcomes. This is where big data comes to picture. Risk terrain modeling, a technique using big data examines the factors that contribute to this process and helps police officers predict where new hot spots could arise Court data could be cross-referenced against public databases that provide information from outside the justice system including demographics and travel time to get to and from courts, thus revealing interesting insights concerning access to justice standards.  • IBM coming out with its first iteration of the analytics software package that it  expects will help law enforcement, government agencies and private businesses wade through the massive amounts of data they collect to help them predict, disrupt and prevent criminal, terrorist and fraudulent activities.

14. Criminal Justice IV • A lot of data about individuals is being captured in contemporary times through social media, blogs and much more. This humongous amount of data is known as Big Data. Researchers think that Big Data can be used in the field of Criminal Justice to provide public safety and justice.  • Big data in this field is of vast importance because it may help in convicting the criminals and in some cases acquitting innocent ones. The data analyzing algorithms have to be carefully designed. Such data can also be used for academic purposes so that the students can learn from cases which took in the real world. • Big Data in this field can be used to solve crime cases, find links to past similar crimes etc. Important because is gives you completely alternate angle to approach a case, based on facts.Delicate because the results inferred after applying certain algorithms on the data should be accurate. An innocent person can be framed or involved in a case even though he may not have any relation to it. Big Data can be useful in academic background in law schools,police training etc.

15. Criminal Justice V • One interesting question that will need to be answered is how Big Data will be used as evidence in a court of law.  The standard for determining guilt in the United States is that a person must be proved guilty "beyond a reasonable doubt."  It will be interesting to see how courts integrate Big Data techniques, such as machine learning, as evidence in courts in light of this standard.  Will courts decide that "reasonable doubt" corresponds to a particular p-value from a statistic test?  • The basic idea is that past crime patterns can predict future crime patterns. Future rises in crime are predicted from data points such as location, time of year, area business pay periods, and weather. There are some concerns that this could impact privacy and civil liberties. It seems to have been effective at lowering crime where it has been instituted – http://ubm.io/1jkfiv8

16. Criminal Justice VI • Big Data in Criminal Justice could be used a number of ways.  It certainly could be used to track crimes, incarceration, jail programs, and recidivism in an attempt to understand how and when rehabilitation works (or fails).  But, a more interesting case may be to look at family and social traits that could help predict the likelihood of being incarcerated.  Law enforcement and judges use a lot of personal discretion in deciding whether someone caught committing a crime is punished at all or the means of punishment.  Early diversion programs for minor offenses (rather then being let off with no punishment) could help deter those with a high likelihood for severe crimes from going down that path.

17. Commerce(15, 3, 3)

18. Commerce I • There are so many different uses for Big Data within Commerce that any large company not using the information or not using it correctly would be missing out on ways to improve sales, reduce cost, improve work quality, etc.  • Big Data can be used to predict certain trends for the future through analytics, thus allowing the opportunity to make necessary business decisions. More importantly, fraud can be more easily detected. • Big Data in Commerce can help companies see certain trends and make decisions based on those trends such as price changes and customers attitude towards company policies.  • I think Big Data is the sole reason that e-commerce has gotten to where it is today. • Companies and businesses online are able to take Big Data and make decisions off of what they analyze. Some of the areas involved include marketing, advertising and sales.

19. Commerce II • Small startups now have the access to many databases to help them do better marketing and user analysis with a cheap fee.  • The involvement of Big Data in the area of commerce has set a bar that almost requires it's use to work competitively. It started as a convenient feature, but now with so much attention and use, it has set up the companies that use it to continue to be more and more productive and the companies that don't, or don't have access to it, to fall behind and miss out on a very important source to boost sales. • big data is used in recommender engines on many eCommerce sites like eBay or Amazon. Big data and the recommender engine will use user purchase data to recommend other items the user may be interested in. This can increase sales by showing the user possibilities it didn't know it could previously purchase.

20. Commerce III • Amazon is a very obvious example but I think eBay and similar Chinese website Taobao are good examples too. •  If you engage customers with information they WANT, they're happy, and when they're happy, they're more likely to purchase. If you bombard them with unwanted, irrelevant information, they'll run as fast as they can the other way.” It is important to give users what they want when they want it and how they want it, beyond that it is crucial to know where the limit is.  • Big data is providing crucial insights on how certain products are likely to generate tremendous sales   • On the internet, big data is very commonly used to show users targeted information and products, which not only increases the overall experience of the user on the website but all increases the amount of sales the website generates.

21. Commerce IV • Another even more beneficial application of commerce based big data is through the facilitation of predictive analytics; knowing not just how the market is behaving currently, but how it will behave in the future as well. •  After having interned at a coffee company last summer I was able to see first hand its importance and value within the workplace. • I am kind of amazed at the way that big data has impacted the e-commerce field. Websites use big data to predict trends and suggest items, among other features, some of which might not even be noticeable to the average consumer. Big data is ever customizing the online shopping experience, and making it fit the needs of the consumer on a personal level. •  Companies are cropping up that fit into the information value chain. Prices on the web constantly change throughout the day, dynamically updating based on countless, intricate factors. So companies following big data need to collect pricing data at all times. 

22. Commerce V • This data may include demographics about the existing customer base compared to the number of times the product is mentioned within social media systems. Users may compare sales trends with weather patterns that may affect the use of the product (say, a down coat in a very cold winter). The idea is to provide retailers who make critical decisions with the means to slice and dice all the relevant data to determine where to place the product bets. • 1) Personalization:One of the most significant uses of big data in commerce is the fact that big data enables personalization. Ecommerce giants like Amazon are currently using this because of which each of our amazon home pages are customized according to our searches and buying patterns.2) Rating:Big data can also look at reviews from customers and help rate a product. For example, a laptop may have reviews such as "good battery but cheap plastic body", "excellent screen but cover seems flimsy". Now big data analysis can use this information and make a pros and cons list for future customers.3) Pricing:Big data can help collect pricing information from various competitors and help retailers decide their product pricing accordingly.4) Predictive Analysis:Big data can look at buying habits of one customer, compare them to other customers and suggest purchases

23. Commerce VI • Sentiment analysis is becoming more common in business.  It attempts to answer questions like "who is buying our brand" and "what are they saying about us online"?   • Today's (March 22 2014) Wall Street Journal introduces a new term: Thick Data where Successful companies work to understand the emotional, even visceral context in which people encounter their product • I no longer have to search the web for bands that I like. I have found more bands that I like through Pandora than what I possibly could have done through web searching. Amazon also gives me great recommendations when it comes to books as well.