Dear Phil Jackson:
It has been almost 20 years since you wrote "Sacred Hoops." In those early years as an NBA coach, leading Michael Jordan and the Chicago Bulls to championships, you put your unique stamp on those teams, teaching them to value selflessness and putting people in roles that served the greater good. Team above self.
You're on the other side of the management fence now
As a coach, you built a family that came to trust each other in their roles and value the bigger purpose. But -- and this is important for your new role with the Knicks -- you made it clear that management wasn't part of that family.
"The only people who really mattered," you wrote, "were the team's inner circle: the 12 players, the four coaches, the trainer, and the equipment manager. Everyone else was an outsider, even [Bulls GM] Jerry Krause."
Indeed, management is an outsider relative to a coaching staff. All those days eating breakfast with the team, all those shootarounds, all those quiet nights on the team flight -- those are bonding experiences that a coach has and management doesn't.
Now you are the outsider. Even if you do go on a few road trips with the Knicks, you just cannot know your own players as well as you did as when you were a coach. In fact, you have to keep your distance, just as you expected management to do when you coached.
That, frankly, is the nature of your new job.
You're in the knowledge business now
Instead of knowing your own players 100 percent, your job now is to know them 90 percent as well as your coaching staff and to know the rest of the basketball world -- other NBA teams, college players, international players, and the D-League -- 10 percent better than everyone else.
Your new job is less personal, without the daily contact and constructive action that goes into 82 games a year. Your new job is more detached, hypothetical, broad and analytical.
You have to ask questions like these:
• Should we change our personnel? What holes does the team need filled? Which players are we willing to give up, in some approximate order?
• Which players are available around the NBA? What teams need help or should make their players available?
• Which trades are out there that we can be part of, as a primary partner or as a secondary team? Are there trades that are easy for us because they are mutually beneficial?
• What do the salary cap and the tax line mean for our freedom to make deals? What do they mean for our owner?
• How much do we have to pay our people? How much are they actually worth in terms of on-court performance? How do we relate on-court performance to salary?
• Who are the top college, international and D-League players? Will they fit into our system?
These aren't easy questions. The Knicks have staff to help answer these questions. You have people you've known for years that you trust to help answer these questions.
You need to know the numbers
Numbers can help answer these questions.
Let's talk about "analytics." As you know, this buzzword has swept through the sports world and created division among NBA people.
But there is an important distinction between statistics and analytics.
Statistics have been part of professional sports since the mid-1800s, if not before. But stats can be used, misused and abused to support arguments that are flat-out wrong. You are correct when you state that you distrust stats that miss the value of role players, for instance.
Analytics, on the other hand, is about answering the same questions that management and coaches are already asking. Analytics is based on refined analysis of the numbers behind winning teams and the players that contribute.
To understand basketball analytics is to understand basketball, and both elements are essential in today's game. Done right, analytics provides an independent voice along with scouts and coaches. Done right, analytics should be constructive, not divisive. Done right, analytics contributes to good decisions.
You need to know how analytics can help
How exactly can analytics contribute to team management?
First of all, analytics is critical to player evaluation, projection and usage.
Analytics shouldn't just describe a player; it should project a player and suggest ways of getting the most out of a player. Describing players -- their ability to rebound or create shots -- is part of the decision process, but their value can be enhanced by system and surroundings.
Players are not machines. As you got the most out of John Paxson and Dennis Rodman, players with specific skills that enhanced their value, a value that needed to be projected forward with knowledge of your system.
Second, analytics can also help determine and project a player's market value.
When Golden State offered Andre Iguodala a four-year, $48 million contract last summer, it shouldn't have been a surprise to his previous team, Denver. What other teams would pay -- whether the amount was "rational" or not -- was something the Nuggets needed to know during negotiations. If it was going to be higher than his worth to Denver on the court, that would force a difficult decision. With tough decisions, you want to have as much advance warning as possible, and analytics can help give that.
You -- by being Phil Jackson -- have the potential to show players that value goes beyond money. But there will often be a gap between value to your team and value on the market. Ideally the value to your team is higher than the value to the market. A good coach can help accomplish this, something you did in that role by maximizing players' skills.
Analytics shouldn't just give a number value to a player; it should be able to fit into normal personnel discussions using phrases like "good players," "can't play defense," "has trouble getting his shot," or whatever language your team uses to describe a player and his role.
Player value is ultimately multidimensional -- not just a combined contribution to a team. Understanding why a player is "good" or "not a good fit" requires the why underneath any analytics.
Understanding how to resolve a conflict in player value -- whether between scouts and analytics or between different analytical systems -- is far more valuable than dismissing conflict, letting it fester, and choosing a side.
That is a big part of your role -- listening and trying to resolve conflict, which is something you did well as a coach. Maybe it will feel the same as president of the Knicks. At the same time, there is a key difference in your new role.
You once wrote this about evaluating players, "We show players how to quiet the judging mind and focus on what needs to be done at any moment." But the "judging mind" that you quieted then is a big part of front office work. You need the judgment of scouts, even if it's wrong.
More importantly, you need to get the rationale behind their judging minds. Sometimes it will take time to translate a scout's thoughts into reasons that you can understand. Similarly, sometimes it will take time to translate analytical numbers into words that you or a scout can understand.
Maybe you meant quick and irrational judgment, and that can be a problem. But judgment from the front office -- methodical, careful, rational judgment, in contrast to rash emotional judgment is what "needs to be done."
When I was in an NBA front office, my Denver Nuggets lost to your Lakers in the Western Conference finals while I was busy interviewing Ty Lawson, Darren Collison and other draft prospects. We had to put interview responses together with our other data and observations to make the best draft-day decision possible (it was Lawson). It was hard to not be watching the Nuggets coaches and players in the midst of their battle. But it was useful to the success of the organization, it was my role, and it was what made me feel valuable to the success of the organization.
That was what you wanted from your players -- selflessness, putting team first, finding their roles. Your challenge with the Knicks is to help an entire organization to value the same things, even if the role you play and the information coming from analytics are unfamiliar to you at first.
Dean Oliver is the ESPN Director of Production Analytics and the author of "Basketball on Paper." He was previously director of analytics for the Denver Nuggets.