Here are some interesting quotes:
- "The result is a data driven approach to training"
- "Players can log into their personal computers to check their own fitness profiles"
- "Last season Catapult helped on of its NFL clients compare practice data ... in weeks when the team won compared to those when it lost. A trend emerged: during Thursday practices before losses, offensive skill players were running a lot but not very quickly."
OK, so NFL teams are beginning to collect all of this data about their players. But who exactly is mining all of this data to find useful information? I can't believe that its the sports-science coordinator (he doesn't have a statistics degree). Plus, who can actually monitor and interpret all of this data in real-time (i.e. during practice)? It seems that Catapult, an IT consulting company focused on interpreting data, is doing some work after the season is over, but do any of these teams have the capacity to perform analysis in-house? Here are a few things to think about:
- I'm sure most of the companies selling the equipment have guidelines or suggestions for how to interpret the data. So maybe a bell goes off when a player's heart rate gets too high. But how accurate are these baselines, especially when the same guidelines are applied to 180lb running backs and 350lb linemen?
- What is the goal of collecting all of this data? Making real-time decisions about players' health during practice? Drawing team-wide conclusions about what does/doesn't work at the end of the season? These are 2 very different questions that could influence the most effective way to collect data.
- How much are teams investing into analyzing this data (either in-house or through ouside companies)? For current genomic sequencing projects, more money is spent on the analysis than the sequencing experiment itself. So are the Eagles planning to spend an additional $1 million on interpreting all of this data? Or will this data just go to waste?