Suds Gopaladesikan is the director of football intelligence for Italy's Atalanta BC. Mathieu Lacome is the head performance and analytics officer with the Parma Calcio football club in Italy, where he develops on-pitch and scouting strategies. Both teams are greatly outperforming their squad costs and operating in a sustainable manner. Together, Suds and Mathieu bring incredible perspective on how data analytics can successfully play out on the pitch.In this episode, they talk about the key components of that success, what they’ve learned about data roles in European soccer clubs, how to drive effective organizational change, and why touchpoints within the organization should be a key performance indicator.

Matthew Lynley has been a journalist covering the tech industry for more than a decade. Four years of this career have been spent covering analytics and data science - tools which he personally used. He is the founder of the Supervised newsletter that aims to help decision-makers sort through the hype and reality of AI tools and the future of big data analytics.In this episode, Matthew goes over security for proprietary data troves, how that data may be sold or rented in the near future, the challenges of unstructured data, how big data could play into drafting, and foundation models vs. tooling and fine tuning.

Seth Stephens-Davidowitz is a data scientist who put his Harvard PhD to work at Google, as well as consulting for numerous Fortune 500 companies.  His first book, Everybody Lies, was a New York Times bestseller and an Economist Book of the Year.  Almost the entirety of his new book, Who Makes the NBA, was written over the course of a single month by leveraging AI data tools.In this conversation, Seth, Jake and Alec discuss some of the incredible insights the book reveals, how AI is replacing coding with critical thought, and what the future looks like for sports data analytics.

Matt Ober is an extremely accomplished data leader turned venture capitalist. After leading Bloomberg's data operations for years, Matt served as chief data scientist for the $20 billion hedge fund Third Point, where he led development and implementation of data and analytics strategies for the entire firm.  He is currently general partner at Social Leverage, an early stage seed investment fund.In this conversation, Matt shares how data practices from the financial world can apply in the world of sports, why AI will become just another part of tech stacks, the key difference between a winning and losing data organization, and what the best analysts will be doing 15 years from now.

Miles Adkins has spent a decade in the data science world, from hedge fund investment models to his current position as A.I. and Machine Learning specialist at Snowflake cloud computing.  He has served in both administrative and customer-facing roles, and is intimately familiar with the successful implementation of data strategies.In this episode, Miles, Jake and Alec discuss what it was like at the beginning of the automation revolution, why speed can be more important than building custom models, why "on prem" data sacrifices too much, and what's causing all the mergers and acquisitions in big data warehousing companies.

Achille de Rauglaudre is a Sports investor and advisor.  Mathieu Lacome is author of the book "Football Intelligence" and the head performance and analytics officer with the Parma Calcio football club in Italy, where he develops on-pitch and scouting strategies.  Together, Achille and Mathieu bring a substantial body of knowledge and experience to the table.In this conversation, we discuss why a business strategy is necessary to effectively implement data strategy, what that looks like for successful teams, the importance of setting realistic expectations and goals, and why communication and visualization of data is so valuable for internal cohesion.

Self-proclaimed data nerd David Spezia served as one of the original Field CTO's at Tableau, was the Principal Sales Engineer at Snowflake during the largest IPO in software history, and is now a Distinguished Architect at Salesforce. His specialties include problem solving with technology, data visualization, and information system design and architecture.In this conversation, David, Jake and Alec discuss the ways successful businesses leverage data technology and platforms, how predictive analytics are evolving, the simple questions David asks to help clients design user experience, and what hiking can teach us about creating those systems.

David Hardoon is an executive with more than two decades of international data science experience in multiple fields.  In the financial sector, he headed up data and AI strategy for the central bank of Singapore and UnionBank of the Phillipines.  In academia, David has served as an Honorary Senior Research Associate with the University College of London for many years.  In industry, he currently serves as CEO of Aboitiz Data Innovation. In this conversation, David, Jake and Alec will discuss "centers of excellence", how they can go wrong, why identifying core needs comes before tech and data, how ownership and use of data insights within organizations might be best distributed, and more.

Jordan Morrow is the founder and owner of Bodhi Data. Since 2019, he’s won 7 awards for his work on data, analytics, and AI. Bodhi Data is aiming to transfer skills in these fields to individuals and organizations that will allow them to make data-driven decisions without becoming advanced data professionals themselves.In this conversation Jordan, Jake, and Alec discuss the incredible pressures that coaches and GMs are under to implement new data and AI solutions, why organizations should resist chasing all the new trends, and what we can learn from the changing fortunes of New Zealand and South African rugby.

Andrew Madson is the Senior Director of Data Analytics at Arizona State University, while also serving as professor at three other universities.  Andrew is a solutions-focused analyst, specializing in machine learning, statistical analysis, and data visualization. His team at ASU is working to bridge their academic research with industry for real-world impact.In 2023, Andrew founded Insights X Design, a data analytics firm that helps businesses with user adoption, machine learning, and targeted A.I. In this conversation, we discuss the failed promise of dashboards and self-serve analytics, why it's becoming more popular to think about data as a product in itself, the trap of over-optimization, and the proper role of LLMs.

Jesse Davis is a computer science professor at KU Leuven, Belgium, where he supervises teams of PhD students researching A.I., data science, and machine learning. Jesse is probably best known for co-developing Valuing Actions by Estimating Probabilities (VAEP) framework in soccer, now widely used throughout the game. He is also cofounder of RunEASI (runeasi.ai), a wearable tech company that integrates A.I to analyze the performance of athletes.In this episode, Jesse, Jake and Hugo dig into the framework that underpins the VAEP's framework, how it can be used to enhance team recruiting, the qualities that make for good models, and the connections between data analytics across different sports.

Day-Yi is a lecturer at Princeton's Center for Statistics & Machine Learning.  Yi has taught college-level math courses, trained corporate clients, and built his own consulting practice focused on data technologies. His client list includes companies such as New York Life, Unilever, Morgan Stanley, and Bank of China. He has also taught at Columbia, where he was selected as a finalist for Columbia’s Presidential Award for Outstanding Teaching in 2021.  Yi is passionate about three things: sports, data and education. In this episode, Yi discusses how he's creating unusual blends of all three. He'll explain why college students are lining up to take his Princeton class on Taylor Swift, and how that connects to a Monte Carlo simulation that has so far predicted playoffs with 100% accuracy. Yi has lots of valuable advice to share - from building a data analytics career to the best Korean restaurant in New York City.

Edem Spio, co-founder, co-host and senior producer of the Africa Business of Sport Podcast and co-founder and director of the Africa Sport Business Group. Spio is also the Media Relations Office at Toppem Sports, and the Public Relations Officer at Yong African Leaders in Sports. In this episode, Spio talks about the integration of AI and data analytics in the production of his podcast, strategies to harness data for enhancing decision-making in Lower League Management (LLMs), Wimbledon's innovative use of virtual reality (VR) and its potential to captivate a broad spectrum of sports fans and a dialogue on the greatest of all time (GOATs) in tennis, rugby, and soccer/football.

Eric Siegel, Ph.D., is a former Columbia University professor, founder of the Predictive Analytics World and Deep Learning World conference series. Siegel authored the bestselling book, "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die," which is a textbook at university courses worldwide.In this episode, Eric Siegel talks about his new book, The AI Playbook: Mastering the Rare Art of Machine Learning Deployment, and the core principles it lays out for ML implementation. This condensed discussion includes practical knowledge such as: Why most data scientists are too technical for their own good, how UPS saved millions with effective implementation of ML, the organization-wide onboarding required to make lasting changes through analytics and why hype about AGI is sometimes irrelevant in a world where most businesses haven't even learned the core lessons of ML and predictive analytics.

Nancy Hensley is a powerhouse in the sports industry and data-driven technology. After serving as the Chief Digital Officer for IBM's Data and AI division, she revolutionized the AI product offerings at Stats Perform, before going on to co-found women's soccer conglomerate Mercury 13.In this episode, Nancy talks about what it takes to be a part of a data company in the sports world and what makes that industry unique. Nancy also shares her thoughts on how to best integrate AI into product offerings and where the sports analytics world is heading in the near future.

Welcome back to the Winning with Data Podcast! Jepson Taylor has 18 years of experience in machine learning. His career journey began at Intel/Micron, and he later transitioned into a pivotal role at a hedge fund. Jepson then served as Chief Data Scientist at the Sequoia-backed HR startup, HireVue. In 2017, Taylor co-founded Zeff.ai with Gemini advisor David “Gonzo” Gonzalez, which was acquired by DataRobot, where he assumed the role of Chief AI Evangelist. Jepson moved from there to become the Chief AI Strategist at Dataiku in 2022 before leaving to launch his second (still stealth!) startup at the end of 2023. His significant impact in developing innovative solutions, such as video interview predictions and network design integration, demonstrates Taylor's commitment to leveraging AI for transformative outcomes in both professional and personal realms.In this episode, Jepson Taylor speaks about the democratization of data and how that can be achieved across organizations in a way that enables all employees to make better decisions through effective collaboration. They also discuss AI technology and its applications in and impact on business, and how sports teams can use such tech for modern, sustainable decision-making. Taylor also gives invaluable insight into storytelling, intellectual honesty and achieving success in business.

Simba Khadder has a decorated history in tech; founding and acting as CEO of Featureform, formerly known as StreamSQL, founded in 2020. Working up from base level engineering roles Khadder has seen tech at every level, giving him a unique perspective and credibility when it comes to speaking on machine learning, data pipelines, and the business processes surrounding projects in that space. A champion of new era tech startups leveraging data and predictive analysis as a service, Khadder has a keen mind for recognizing what spaces or industries that data scientists can benefit from assistance in breaking down the often overwhelming tidal wave of raw data faced.In this episode of the Winning With Data podcast, Simba Khadder speaks on the importance of feature engineering in the world of machine learning and how it is oftentimes the most important portion of any data science project pipeline. Leveraging his own experience and time spent around the industry, Khadder delves into the emergence of data as a product. Stressing the importance of seeing data as more than something that adds to existing teams but as something that adds value by way of generating insights and optimizing processes. Validating this stance through an explanation on how to quantify how important any given data-centered team is to a company, Khadder doubles down on the importance of end-user experience and how a well resourced data science team can drive that bottom line.

David “Gonzo” González has well over a decade of experience putting AI and ML into production in mission-critical systems. Currently working on a stealth startup in the psychedelics space, he previously co-founded Zeff.ai, acquired in 2020 by DataRobot where then served in an executive role bringing a jobs-to-be-done perspective to focus product strategy. Known as a pioneer of deep-learning-as-a-service and transactionally authored training and inference on multi-modal datasets, Gonzo authored The AI Manifesto for Applied Artificial Intelligence Development and has multiple ML patents.In this episode of the Winning With Data podcast, David “Gonzo” Gonzalez talks about how AI, specifically the release of ChatGPT, is not well-designed for casual users at the moment. He remarks that it's better to think of it as an external data source and find value with it. He also stresses the importance of building an understanding of your book of business to not waste resources. A good organization has a strong data- and insights-driven staff and builds its models based on their unique understanding of the field, without room for people or systems that don't focus on the productization data. Gonzo talks about avoiding and working through mistakes in the analytics field, such as avoiding falling into the trap of starting a project all over when a small mistake is made.

Sergio Santamaria, Director of Business Innovation and Data Solutions at Sports Info Solutions, has experience as a data analyst for the Detroit Pistons, the Phoneix Suns, and the Houston Rockets. He also spent time at Stats Perform and founded his own company, 3D Sport, which focuses on providing equal inclusion for all in the sports industry.In this episode of the Winning With Data podcast, Sergio Santamaria talks with Jake about the challenges of working with qualitative data and the importance of having clean datasets. He discusses how everyone in an organization should build some technical skills to increase overall efficiency and help free up analysts' workflows. Sergio talks about how alignment and consistency from organizational leadership  and true adoption of the principles laid out by each team as important markers success. He remarks that all analytics teams should challenge themselves to make systems and frameworks that incorporate both qualitative and quantitative data and build these systems to last.

Benjamin Alamar has had a long career of success building and leading data and analytics teams across multiple industries. He served as the Director of Basketball Analytics and Research at the Oklahoma City Thunder for five years before moving to become the Senior Analytics and Data Consultant for the Cleveland Cavaliers. He spent four years as the Director of Sports Analytics at ESPN, then StubHub as Head of Business Analytics. Ben has been helping to run the MIT Sloan Sports Analytics Conference since its inception.In this episode of the Winning With Data podcast, Jake talks with Benjamin Alamar about how data can empower organizations when they can ask the right questions and organize it efficiently. Benjamin remarks that getting to know how the data will be used, what the stakeholders of an organization need, and what kind of data aggregates to pull for each team vastly increases its usefulness. With the increase of data loads from new tracking data sources, understanding exactly what kind of information stakeholders need is paramount. He stresses the importance of embracing debate, ideas, iteration, and innovation by having humans create hypotheses and using analytics to test those hypotheses to find the best solutions.