The Cleveland Browns have done a remarkable thing in the National Football League. It’s not a good thing, mind you, but it is remarkable.

In the last two seasons, the Cleveland Browns have won exactly one game. They’ve compiled a 1-31 record since the beginning of the 2016-2017 season, a notable achievement in bad football. That includes a 0-16 record in 2017.

The one victory in 32 attempts came on Dec. 24, 2016, with a 20-17 win over the San Diego Chargers. In its own way, the Browns’ failure is as fascinating as other teams’ success. It takes a lot to lose that much.

For those with an interest in data science and analytics, the Browns’ woeful past two seasons are even more interesting. That’s because the Cleveland Browns had turned to a data-driven approach to run the team, a method that has worked well for baseball teams such as the Chicago Cubs and Houston Astros.

The Fallout

The Cleveland Browns have already fired Sashi Brown, the analytics-driven executive vice-president of football operations and, essentially, general manager for the team since January 2016. They have replaced him with John Dorsey, a much more old-school type football executive.

He’s already blamed Brown for not getting “real players” for head coach Hue Jackson.

Many have reported that the Browns’ terrible performance on the field has led to an end of the analytics era in Cleveland. However, it’s worth noting that the team still has Paul DePodesta as a chief strategy officer. DePodesta is an analytics guru who got his start in baseball, working with Billy Beane in Oakland. That’s him played by Jonah Hill in the movie, “Moneyball.”

But, as The Sporting News (and many others) pointed out, Brown’s firing signaled “the demise of their analytics-based approach, aka the football version of ‘Moneyball.’”

But did analytics really fail the Cleveland Browns?

How It Went Wrong for the Cleveland Browns

The short answer to the above question is: “No.”

Much of the problem in Cleveland has been focus and commitment. Contrast the Browns’ approach with that of three baseball teams committed to analytics: the Oakland Athletics, Houston Astros and Chicago Cubs.

The A’s use of “moneyball” – as documented in the book by Michael Lewis and the film starring Brad Pitt – kept the team competitive for many years despite a much lower payroll than other teams.

The Astros and Cubs present an even better “apples to apples” comparison. Both teams committed to a data-driven approach, from the front office to the coaches on the field. Both teams also suffered through many losing seasons before the strategy paid off.

In the Astros case, they had four straight losing seasons – three of them with more than 100 loses – before turning it around in 2015 and eventually winning a championship in 2017. The Cubs also had three straight losing seasons once the data-driven Theo Epstein took over as president of baseball operations before the 2012 season. They made the playoffs in 2015 and winning a championship in 2016.

In all these cases, it took patience and commitment. Those are not characteristics the Browns have shown.

As the months have worn on since the end of the Browns’ winless season, there’s been time for everyone to digest what happened. Those with some familiarity with analytics know that Brown, in many ways, took the blame for something that was not entirely his fault.

Here are some of the reasons analytics can’t be blamed for the Browns’ failure. There are some lessons here for anyone who plans to work in analytics – especially if it’s new to an organization.

Hue Jackson

For reasons that surpass the ability of anyone to explain logically, the Browns’ owner Jimmy Haslam decided to hire the data-driven Brown at the same time he hired the far more traditional coach Hue Jackson.

As pointed out by Sports Illustrated, that might work if you are in a “win now” mode. But the Browns, clearly, were not. Differences between the front office (building for tomorrow) and the coaching staff (let’s win now) were bound to happen. Many speculate a clash between Jackson and Brown led to Brown getting let go, which means ownership sided with the traditional rather than the analytical.

As the movie “Moneyball” shows, differences between the front office and the field manager can lead to trouble.

It Takes Time

It’s remarkable how short the memory of sports fans can be – or, perhaps, what they (and the Browns’ ownership) decided to ignore. The Chicago Cubs suffered five straight losing seasons while the club used a data-driven approach to build a team that eventually won the World Series in 2016. The Houston Astros had three straight seasons of more than 100 losses – and a fourth with 92 losses – before winning it all in 2017.

Even players thought Brown did an excellent job accumulating talent. Late last season, Detroit Lions’ cornerback Glover Quin said that the Browns have more young talent than 25 of the NFL’s 32 teams.

Clearly, Brown had a plan. It’s worth noting that the Browns’ teams that preceded Brown’s tenure in Cleveland didn’t win more than 7 games per season (and that only happened once) since 2007, and hadn’t made the playoffs since 2002. So, while one win in two seasons is spectacular in a horrible way, is it that much worse than winning 3 to 4 games a year with no plan for the future?

Commitment to Analytics

This combines the two issues listed above. The Cubs’ ownership, running a team that hadn’t won a championship in 108 years, went hard into analytics and stuck to it through terrible seasons. The Astros, who had never won a championship, did the same.

The Browns, on the other hand, have once again changed strategies and now face their fourth “rebuild” in the past half dozen seasons.

The lesson? Brown’s plan might have worked, or it might have failed. But we will never know now. If you go into a job with analytics as a focus, make sure the organization has the right mix of talent, a long time frame for success and a commitment for ownership to see it through.