Tag Archives: data analytics

Baseball Technology 2017

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With the 2017 baseball season approaching the midway point, I have been reading about the decline of fan interest, ticket sales, and athlete recognition. An article from my local newspaper reported that not one baseball player is among the 100 most famous athletes in the world, based on endorsements, social media following, and internet search popularity; those spots are taken by soccer, tennis, football, basketball, and even a few golf stars. I wonder what technology could do, if anything, to pull baseball out of this popularity slump.

Sensors

Technology is showing up in some unusual places, including wooden baseball bats. Sensor manufacturer Zepp has teamed up with the Old Hickory bats to create a smart bat. A device is built into the knob of the bat that records data points like swing speed, angle and motion and shares that information via Bluetooth to a connected device. A visualization shows the swing and connects to previous data to compare that swing with others, which allows the player to correct any issues in order to reach maximum performance. These sensors are available for tennis rackets, golf clubs and softball bats. While smart bats are meant for improving player performance I wonder if the visualization can be shared with fans as well, perhaps on the Jumbotron, to give tech-savvy fans something to do between pitches.

Of course, technology is also used for tracking statistics on pitches. For stadiums equipped with TrackMan, fans in the stadium and at home can track live information on pitch velocity, spin and exit speed among various radar tracked data points. This is sophisticated technology but I wonder if data driven fans even need to go to the ballpark any more or can they sit at their computer and analyze every pitch and swing as it happens? Is it more important to see the action or analyze? I foresee the day when machine learning enters into baseball and a computer directs players on their next move based on historical and real time statistics. Hackers could have a field day with that interaction.

Stadium Technology

We can now track every player and every swing but that still does not get people in seats, which is a real problem in baseball today. To try to overcome that problem, stadiums are being built and retrofitted with wireless access points for between inning entertainment and high definition cameras and displays so you won’t miss any action, even if you don’t have the best seat in the house. Various baseball franchises have developed fan apps that allow you to watch instant replays and view statistics on your smartphone or tablet while in the stadium. Apps also allow you to order up snacks and have them delivered to your seat, for a premium. The stadium experience today is a combination of live action and device interaction. There are virtual reality applications in development that will allow you to get a bird’s-eye view of the action or zoom into one particular area of the field using cameras positioned around the stadium. Reality meets virtual reality.

<h4Thoughts

There are a number of new technologies introduced or in development designed to bring fans back to baseball, either in the stadium or watching at home or on a mobile device. Time will tell if they are successful but with the price tag of new stadiums, there is a lot at stake. Have you been to a live baseball game recently? How was your experience? Let me know your thoughts.

Author Kelly BrownAbout Kelly Brown

Kelly Brown is an IT professional and assistant professor of practice for the UO Applied Information Management Master’s Degree Program. He writes about IT and business topics that keep him up at night.

Preventing Crime Using Predictive Analytics

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In the 2002 futuristic movie “Minority Report,” Tom Cruise heads up a police division called PreCrime. This unit uses predictive analysis collected from mutants to arrest the would-be criminal before the crime is committed. The movie is set in 2054 and while I don’t think we have crime fighting mutants among us, we do have computers that make predictive analysis in police work a reality in 2017.

Predictive Analysis

Predictive analysis uses data mining, statistics, computer modeling, and machine learning to predict future events. This can help companies or agencies to better position a product launch or develop a business continuity plan. It can also help them forecast demand for products or services. Retail stores have used this science for years to plan for resources based on a number of factors such as the day of the week, day of the year, weather, and other data points. Dunkin’ Donuts, for example, uses same day sales for the last year as a factor in deciding how many donuts to start on any given day. This helps to reduce waste from too much product and ensures that a customer can always get a French cruller at the end of a busy day.

PredPol

This same predictive analysis is being applied to crime prevention. Predpol is an advanced analytics application that police agencies in California, Maryland, Florida, Georgia, Washington and elsewhere are using. The software collects three historical data points: past type of crime, place of crime, and time of crime.

Through historical analysis, Predpol developers have discovered that there is a pattern to crime and criminals and by mining for those three data points the application can predict where crime is likely to occur in the future. There is no personally identifiable information collected or used so as to prevent biases or profiling. Once the predictive analysis is complete, police assign extra patrols to discourage crime where it is expected. Police report this application does indeed help reduce crime in their jurisdictions. This is a case of advanced analytics being used for positive results in communities.

Counterpoint

To be fair, the output is only as good as the data entered. Information analysts often refer to this as “garbage in, garbage out.” Software such as Predpol and other applications rely on clean, accurate data to predict future hotspots. In a recent blog post from the Council On Foreign Relations, the authors argue that not all crimes are reported so these tools are limited because they start with an incomplete data set, which results in inaccurate or limited information about future crimes. Police go back to the areas where crimes were reported but miss other obvious opportunities because they lack a full data picture. It is important to factor in other data points in order to understand the full picture.

Thoughts

There will most likely be some pushback from people concerned about profiling of a particular neighborhood or audience, but with reasonably clean and unbiased data collection tools such as these can aid law enforcement agencies in fighting crime and creating safer communities.

Do you have other examples of data analytics that is helping to solve real world problems? Let me know your thoughts.

Author Kelly BrownAbout Kelly Brown

Kelly Brown is an IT professional and assistant professor of practice for the UO Applied Information Management Master’s Degree Program. He writes about IT and business topics that keep him up at night.