Analyzing Pro Athletes' Physiological Dashboard

I recently came across an article about the "sports science" changes that Chip Kelly has implemented since becoming head coach of the Philadelphia Eagles.  Basically, the Eagles spent more than $1 million investing in new technology that measures physiological details (heart rate, amount of time spent running during practice, 3d views of how players are lifting weights, etc) in the hopes of creating a "physiological dashboard" for each player.  They want to monitor the performance of each player during practice to increase training efficiency, such as ending practice early for players reaching their endurance limits or ensuring that players receive the correct amount of hydration based on what was lost during practice.  A large portion of the article is dedicated to describing the Eagles sports-science coordinator, who has previously served as a strength coach and nutritionist for colleges and the Navy SEALs.

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:

1. 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?
2. 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.
3. 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?

College Basketball Commitments

I came across a very nice article describing the college commitment habits of 700 top basketball recruits.  The author does a great job of delving through the data and concisely summarizing the main findings.  A few of my favorite highlights:

1. First, just obtaining all of this data (all high schools and colleges attended for all 700 athletes) must have been a Herculean task.  
2. I like that he also displays the data with several bar charts and a very colorful cumulative density plot showing how early in their high school career that recruits commit to a college.
3. Of the players who spent at least 2 seasons playing in college, over a third didn't end up where they started.
4. Think that these top recruits only bounce around universities to get the most exposure?  4 of the recruits attended 6 different high schools, including current NBA player Michael Beasley.  Plus, over 50% of the 2013 recruiting class attended at least 2 high schools.

Statistics Playing Major Role in College Football Playoffs

The potential impact of stats on the playoff selection committee

In the above article, Sports Illustrated sought the recommendations of 5 college football and basketball "stats gurus" to get a better feel for how the college football playoff committee should go about choosing the four teams to compete in the 2014 national championship playoffs.  They discussed three primary themes:


1. The need for accountability and transparency. Although the BCS releases their rankings and scoring/point totals every week, the actual formula used in these calculations is proprietary.  I am in agreement with the 5 experts in calling for full transparency in the system.  However, this makes it difficult to include an "eye test" in the decision (whether this should be included is another debate).  My favorite quote:

"I doubt this will happen, but I think they need to have a non-voting data person in the room as well. Someone to help the members interpret ratings and other data sources, answer questions that are posed and hold the group accountable to information that is shared."

2.  Its about more than wins and losses.  Should other factors like injuries and margin of victory/defeat play into account?

"Of course, the danger of using advanced stats or ignoring head-to-head results is the committee might wind up producing a bracket that the majority of the public -- accustomed to seeing rankings ordered largely by team records -- rejects."

3.  Strength of schedule isn't what it seems.

"There are many ways to measure schedule strength, and many of them are valid. I like to use this example. Imagine two schedules. Schedule A consists of the six best teams in the country and the six worst. Schedule B consists of the 12 most average teams in the country. Which is tougher? Ask Alabama, and they'll obviously say Schedule A. Alabama would have a much easier time running the table against Schedule B. But ask the worst team in the country which one is easier, and they'll say the opposite. The worst team in the country would have a hell of a time winning a single game against Schedule B. ... So depending on who you are, you can perceive the exact same schedule of teams very differently."