Commercial property investors could learn a lot from the data-led revolution that has taken place in basketball in recent years, as Chris Urwin explains.
2 minute read
Netflix has added twice as many new subscribers as it expected during lockdown. I am one of them, signing up to watch “The Last Dance”, a documentary based on Michael Jordan’s final season with the Chicago Bulls.
I loved the series, reacquainting myself with childhood heroes. But there is something strange about watching basketball from an earlier era. Even when watching the greatest player of all time, you can’t help thinking, “you are playing the game wrong”.
Basketball has been through a revolution over the last decade, transformed by data analytics
Basketball has been through a revolution over the last decade, transformed by data analytics. Perhaps the one element of gameplay that has changed most is shot selection. Each season, around 200,000 shots are taken in the NBA. That provides a wealth of data to assess the probability of a shot being successful from different locations on the court.
A key feature of basketball is the three-point line. Shots from behind this line – “from downtown” as the commentators say - yield three points. From within it, they earn two points. Combining the probability of a shot being successful with the points up for grabs allows estimates of a shot’s value, or points per shot. The probability of a shot succeeding when taken from close to the basket is high at 60 per cent, so the points per shot is 1.20.
The probability of shot success declines rapidly when shooters are more than six feet from the basket. For a mid-range two-point shot, the probability of success is around 40-45 per cent, so the points per shot might be 0.85. Three-point shots are harder still, but better rewarded. Only 35 per cent of three-point shots go in. But the big reveal of the data is that three-pointer offers 1.05 points per shot, far more than a mid-range two-point shot.
This has led to the proliferation of the three-point shot. Meanwhile, mid-range two-point shots are becoming a novelty. The difference with Micheal Jordan’s highlight reel from the 1990s is jarring.
There are strong similarities between the work of sports analysts and investment researchers in private markets
There are strong similarities between the work of sports analysts and investment researchers in private markets. Both are trying to identify an edge they can turn into a strategic advantage. There are three key learnings for real estate investors from sports analytics.
Firstly, intuition failed while data revealed. The three-point line was introduced in 1979. But it is only in the last 10 years that teams began to adapt their strategies appropriately. For three decades, players used gut feeling to guide shot selection. Their gut was guided by hours and hours on the court day after day, year after year. And it was wrong.
In some fields, experience can count for a lot and inform a gut feel. But, to be valuable, experience needs to be accompanied with clear feedback. For basketball players it is difficult to keep track of the percentage of their shots that went in from different locations. For investors, luck and randomness play such a large role in outcomes that the quality of feedback is poor. In both fields, well deployed analytics can add great value.
Secondly, data analysts were only able to add value when focused on the right metrics. Statisticians have talked about basketball data for decades but focused on data that was easiest to collect, like points scored and rebounds made.
Property researchers need a better understanding of factors driving performance, like connectivity, amenity and income security
The breakthrough in basketball analytics came with the collection of new, more relevant data. Property researchers should take note. Property data is largely categorised by sector and geography. It is easy to split data that way, but it may not be the best approach. We need a better understanding of factors driving performance, like connectivity, amenity and income security.
Thirdly, it is worth assessing the reasons behind players’ preference for lower risk/lower reward shots. Missing doesn’t feel good. Players don’t like to fail, particularly in front of a crowd.
When real estate investments don’t work out, it feels bad too. Explaining this to clients is tough. Some investors may therefore overpay for low risk assets to reduce incidents of downside risk. Quality bias can creep into decision making.
Implementing a rigorous investment process focused on price, risk and value may allow disciplined investors to capitalise on mispricing generated by the wider market’s willingness to overpay for low risk assets. In basketball terms, this should enable them to land a few more three pointers rather than settle for the easy two.
This article was originally published by The Property Chronicle.