Before the 2021 NHL season started we used the principles and equations used in the film and book Moneyball while we attempted to apply similar practices to the sport of hockey. More specifically, we applied it to the Los Angeles Kings roster. The results were shocking. The equations we used were right on. We were able to predict the Los Angeles Kings exact spot in the standings.
Los Angeles Kings Moneyball: What were the results?
Constructing this whole experiment was not just plug in one equation and sit back and watch. It was a lot of trial and error and lots of failing. We were able to construct multiple equations like goal differential, shooting percentage, expected goals model, and an expected goals against model. All to help evaluate and predict where the Kings would finish.
After constructing the actual rebuild and using these equations on the team, we were able to see there are players who actually create more scoring chances than someone who receives double the amount of ice time. That’s what we were looking for, the island of misfit toys, of players.
We predicted the Kings to score 145 goals (GF) and allow 169 goals against (GA) in the 56 game season. In this case, it would give them a win percentage of .424 and likely finish 25th-31st in the NHL with 52 points.
The actual 2021 Kings finished with 143 goals, 170 goals against, 49 points in the 56 game season, and finished 25th in NHL.
With all the equations we used and tracking analytics through player data, we were able to predict exactly where the Kings would finish. Sure we were 2 goals off on the goals for and 1 goal off on the goals against, but we can see the power of hockey analytics and how it should truly be applied in the NHL.
I put together a Twitter poll and the results are in, we will be doing a 2022 Moneyball test run with the Columbus Blue Jackets roster.
Gonna give this a whirl again. What team would you want to see next? https://t.co/pcR6EcXPVR
— Dylan Loucks (@DylanLoucks4) July 20, 2021
What Would We Change?
We were greatly amazed by the actual outcome of the Moneyball kings rebuild. With that, we are very excited to continue the trend with the Columbus Blue Jackets. There are a few things we would like to add to the next one though.
We would not change the actual team equations or the full analysis on the actual team, those are two aspects to be left the same. But we would change up some of the trades and focus more of our thinking and player analysis on acquiring players that would fit the coaching staff and management more. Some of the trades we made were possibly unrealistic. The actual trading aspect will be something we change in the next article with the Blue Jackets.
Lastly, coming up with a power play and penalty kill model for the Blue Jackets is number one. Using data from coaching and actual player-driven stats to construct a shutdown PK or build a lethal PP. The PP metrics would be used through shot location metrics and passing accuracy on players.
The point of this article was exactly what the film and book Moneyball were all about. After watching Moneyball, I came up with my own equations similar to Bill James’ equations, based on inspiration. This was an attempt to find value in players, which NHL teams did not see. While plugging them onto our team and see how they would perform.
We had a lot of fun with this. As it’s safe to say we could very well see something similar to this in the NHL someday. Especially with the growing knowledge of analytics in NHL front offices.
Kings Moneyball Main Photo: ST. LOUIS, MO – FEBRUARY 24: Los Angeles Kings goaltender Cal Petersen (40) watches as a shot on goal just misses during a NHL game between the Los Angeles Kings and the St. Louis Blues on February 24, 2021, at Enterprise Center, St. Louis, Mo. (Photo by Keith Gillett/Icon Sportswire via Getty Images),