Analytics Used in Tennessee Titans Decision-Making

In the modern NFL, analytics have evolved from a “nice-to-have” tool to a cornerstone of successful team operations—shaping everything from draft picks to play calls. For the Tennessee Titans, this shift has been deliberate, with the franchise investing in a dedicated analytics department over the past five years to complement traditional scouting and coaching intuition. Today, data isn’t just used to justify decisions; it’s used to inform them, creating a balance between numbers and human expertise. Analytics Used in Tennessee Titans Decision-Making isn’t just about listing metrics; it’s about exploring how the Titans turn raw data into actionable insights—whether it’s identifying undervalued draft prospects, optimizing in-game substitutions, or reducing player injury risk. This data-driven approach has helped the Titans stay competitive in the AFC South, even as salary caps and roster turnover create constant challenges.

Analytics Used in Tennessee Titans Decision-Making first shines a light on roster construction, where the Titans use advanced metrics to evaluate players beyond traditional stats like yards or sacks. The team’s analytics team focuses heavily on “value over replacement” (VORP) and “expected points added” (EPA)—metrics that measure how much a player contributes compared to an average replacement and how their plays impact the team’s chance of scoring, respectively. For example, when evaluating defensive ends in the 2025 draft, the Titans prioritized prospects with high “pressure rate” (percentage of snaps where they generate pressure on the quarterback) over raw sack totals. This led them to select rookie Mason Graham, who had a 19% pressure rate in college (top 5 among draft-eligible defensive tackles) but only 6 sacks—numbers the analytics team argued understated his impact. Graham went on to record 4 sacks and 12 pressures in his rookie season, validating the approach. “We don’t ignore traditional stats, but we dig deeper,” Titans director of analytics Sarah Johnson told The Tennessean. “A player’s ability to affect the game on every snap—not just the ones that show up in the box score—matters more in the long run.” This focus on predictive metrics has also guided the Titans’ free-agent signings, like defensive end Denico Autry, whose high “stop rate” (percentage of runs he halts at or behind the line of scrimmage) made him a priority despite being 33 years old.

Another key area of Analytics Used in Tennessee Titans Decision-Making is in-game strategy, where the Titans use real-time data to optimize play calls and substitutions. On offense, the team’s analytics team provides head coach Mike Vrabel and offensive coordinator Tim Kelly with “success rate” data—percentage of plays that gain 40% of needed yards on first down, 60% on second down, and 100% on third down—for different formations and personnel groupings. For example, in the Week 9 win over the Carolina Panthers, data showed the Titans had a 68% success rate with 11 personnel (1 running back, 1 tight end, 3 wide receivers) on third-and-short, leading Kelly to lean on that grouping for three critical conversions. On defense, the Titans use “coverage win rate” (percentage of time defensive backs stay with their receivers) to decide which cornerbacks to deploy against specific wide receivers. In the Week 14 win over the Indianapolis Colts, analytics revealed that cornerback Roger McCreary had a 72% coverage win rate against Colts wide receiver Michael Pittman Jr. in their previous matchups—leading Vrabel to have McCreary shadow Pittman, limiting him to 4 catches for 39 yards. “Analytics give us confidence in our choices,” Kelly said in a post-game press conference. “We’re not guessing—we’re using data to put our players in positions to succeed.”

Analytics Used in Tennessee Titans Decision-Making also plays a critical role in player health and load management, a priority for a team with veteran stars like running back Derrick Henry and safety Kevin Byard. The Titans use wearable technology to track players’ “player load” (a combination of distance covered, acceleration, and deceleration) during practices and games, ensuring they don’t exceed thresholds that increase injury risk. For Henry, who has a history of foot injuries, the analytics team has set a weekly load limit; if he approaches that limit in practice, the coaching staff adjusts his reps or gives him a rest day. In 2025, this approach helped Henry stay healthy for 15 games, rushing for 1,421 yards—his highest total since 2022. The Titans also use “recovery analytics” to monitor sleep quality and muscle recovery, providing players with personalized nutrition and rest plans. “Injuries are the biggest threat to a season, so we use every tool we can to prevent them,” Titans head athletic trainer Tom Kanavy said. For the Tennessee Titans, this focus on data-driven health management isn’t just about keeping players on the field—it’s about maximizing their performance when they’re there. By avoiding the “overwork” trap that plagues many running backs, Henry remained fresh late in the season, rushing for 428 yards in the final four games to help the Titans clinch a playoff spot.

Analytics Used in Tennessee Titans Decision-Making further extends to opponent scouting, where the Titans use advanced film analysis and data modeling to predict opposing teams’ tendencies. The analytics team builds “predictive playcall models” that use historical data—like how often a team runs vs. passes on first-and-10 in the red zone, or which formations they prefer on third-and-long—to forecast what the opponent will do in specific situations. For example, before the Week 12 game against the Houston Texans, the model predicted the Texans would run 62% of the time on first-and-10 in the first quarter—a tendency the Titans exploited by stacking the box, limiting the Texans to 2.3 yards per carry in that scenario. The Titans also use “ QB decision trees” to map out how opposing quarterbacks react to different blitz packages; before facing the Jaguars’ Trevor Lawrence, data showed he threw interceptions on 8% of plays when facing a five-man blitz—leading the Titans to use that package 12 times, resulting in one interception and three sacks. “Scouting used to be about watching film and taking notes,” Titans director of scouting Monti Ossenfort said. “Now, we’re using data to turn those notes into predictions. It’s like having a crystal ball for what the opponent will do.” For the Tennessee Titans, this analytical edge in scouting has been particularly valuable in the AFC South, where familiarity with division rivals can lead to predictable strategies—data helps the Titans stay one step ahead.

The final aspect of Analytics Used in Tennessee Titans Decision-Making is how the franchise balances data with human expertise—a balance that’s key to avoiding the “analytics trap” of over-reliance on numbers. Vrabel has repeatedly emphasized that analytics are a “tool, not a rule,” and he encourages his coaches and scouts to push back if data contradicts their on-field observations. For example, in the 2025 draft, the analytics team ranked a wide receiver prospect higher than the scouting department, who had concerns about his ability to catch in traffic. After further film study and a private workout, Vrabel sided with the scouts—passing on the receiver and selecting a tight end who fit better with the team’s culture and personnel. “Data tells you what has happened, but football is about what will happen—and that requires human judgment,” Vrabel said in an interview with NFL.com. For the Tennessee Titans, this balanced approach has been their greatest strength in using analytics. They don’t let numbers override intuition, but they also don’t ignore data that challenges long-held assumptions. This middle ground has allowed them to make smarter decisions in every area—from drafting rookies to calling plays—and has helped them remain competitive in a league where the margin for error is razor-thin. As the NFL becomes more data-driven, the Titans’ ability to blend analytics with human expertise will keep them at the forefront of smart team management—proving that success in football isn’t just about talent, but about how you use every tool at your disposal to put that talent in the best position to win.