Beyond the Box Score: How NFL Teams are Using Next Gen Stats to Redefine Player Evaluation

In the electrifying world of the NFL, where games are often decided by mere inches and split-second decisions, teams are constantly seeking an edge. The old days of relying solely on traditional scouting methods and “gut feelings” are fading fast. Today, a data revolution is underway, with NFL teams increasingly turning to Next Gen Stats (NGS) to redefine player evaluation and gain a deeper understanding of the game. This transformation is not just about crunching numbers; it’s about unlocking hidden potential and making smarter, more informed decisions that can ultimately lead to victory.

The Evolution of NFL Analytics

The journey of analytics in the NFL has been a fascinating one. Back in the mid-1990s, the Philadelphia Eagles were among the first to dip their toes into the world of data analysis. However, in those early days, the use of analytics was basic, and its impact was limited. Fast forward to today, and the landscape has changed dramatically. Teams like the Cleveland Browns, under the guidance of Paul DePodesta, have embraced an analytics-based approach to overhaul their draft strategy and improve team performance. The New England Patriots and Baltimore Ravens have also successfully integrated data analytics into their game planning, using detailed analyses to inform in-game decisions.

Next Gen Stats: A New Era of Player Tracking

At the heart of this data revolution lies Next Gen Stats, a comprehensive system that tracks every player’s movement on the field. Since 2014, NFL players have worn computer chips in their shoulder pads, recording their location, direction, velocity, and acceleration ten times per second. Since 2017, a similar chip has been in the ball. This wealth of data provides coaches and analysts with invaluable insights into player performance, allowing them to evaluate talent in ways never before possible.

Mike Lopez, the NFL’s Senior Director of Football Data and Analytics, aptly describes Next Gen Stats as “player tracking.” But it’s not just about tracking; it’s about understanding why things happen on the field. Why did a particular run gain only three yards, while another went for 88 yards and a touchdown? Next Gen Stats help answer these questions by quantifying the contributions of every player on the field, even those who don’t touch the ball.

Key Metrics and Their Impact

Next Gen Stats have given rise to a plethora of advanced metrics that are transforming player evaluation. Some of the most impactful include:

Tackle Probability: This AI-driven metric evaluates the likelihood of a successful tackle in real-time, considering 20 different features for each of the 11 defenders every tenth of a second. It helps quantify tackling efficiency by estimating tackle opportunities, missed tackles, and group tackles.
Offensive Shift and Motion Classification: This metric uses pre-snap tracking data to analyze variables like speed, acceleration, and distance traveled by players. Movements are categorized into shifts, motions, and motions at the snap, providing deeper insights into pre-snap actions.
Expected Points Added (EPA) and Win Probability Added (WPA): These metrics quantify the impact of each play on the game’s outcome, giving coaches a clearer picture of how specific plays contribute to overall success.
Draft Score: Developed by the NFL Next Gen Stats team and built on Amazon Web Services (AWS), Draft Score incorporates real-time football performance data, historical comparisons, and position-specific benchmarks to create player ratings ranging from 50 to 99. These ratings specifically measure player athleticism and analyze how those attributes will contribute to their potential success in the NFL, providing a sophisticated complement to traditional prospect evaluation methods.

How Teams are Using Next Gen Stats

NFL teams are leveraging Next Gen Stats in various ways to gain a competitive advantage:

Player Evaluation: Teams are now relying less on traditional scouting and more on analytics to determine a player’s impact and value. Metrics like Player Efficiency Rating (PER) help teams identify undervalued talents who may not shine through traditional stats but contribute significantly to the team’s dynamics.
Game Planning: Advanced metrics help teams refine their defensive and offensive strategies by analyzing players’ pre-snap movements and post-snap efficiency. Coaches can tailor their game plans more precisely, adapting to both the strengths of their roster and the vulnerabilities of their opponents.
Injury Prevention: By analyzing data points related to injuries and tackling efficiency, teams can develop safer practices and reduce injury risks.
Draft Strategy: Teams are using Next Gen Stats to identify players who may not have been highly regarded by other teams but possess unique skills that translate well into the NFL. For example, Brad Holmes, the Detroit Lions’ General Manager, has made draft picks with the highest average athleticism score from NGS since he took over in 2021.

The NFL Combine IQ: A Quantum Leap in Data Sharing

The NFL has also made strides in making Next Gen Stats accessible to fans and analysts alike. The Combine IQ dashboard, powered by AWS technology, transforms raw Combine data into intuitive, interactive visualizations. This allows fans to analyze player performance and evaluate the next generation of NFL talent. According to Mike Band, Senior Manager at NFL Next Gen Stats, the Combine IQ dashboard “represents a quantum leap in how we share NFL Combine data with fans and analysts.”

The Future of Player Evaluation

As technology continues to advance, the role of Next Gen Stats in player evaluation will only grow. Teams will likely find new ways to harness analytics for competitive advantage, from identifying hidden talent to optimizing game strategies and preventing injuries. The rise of machine learning and artificial intelligence will further enhance the power of Next Gen Stats, allowing teams to uncover even deeper insights into player performance.

The Los Angeles Rams, for example, are looking solely at tracking data to evaluate players, rather than relying on traditional Combine events like the 40-yard dash. They want to know how quickly a player gets off the ball and their closing speed and reaction time when the ball is in the air – football-specific skills that Next Gen Stats can quantify.

The integration of data analytics into the NFL is not just a passing fad; it’s a fundamental shift in how the game is understood and played. As teams continue to embrace Next Gen Stats, the days of relying solely on the “eye test” are numbered. The future of player evaluation is data-driven, and the teams that can best harness the power of analytics will be the ones that ultimately rise to the top.