As Devin Booker and Trae Young lead their respective teams in the 2021 NBA Conference Finals, it’s time to remove the phrase âgood stats, bad teamâ.
Booker and Young were both tagged with the unflattering tag early in their careers, when they racked up impressive per-game stats for lottery-related teams. The idea might even have helped keep Young away from this year’s All-Star squad when the Atlanta Hawks started the season 13-18 while also dealing with injuries from key starters ahead of the announcement. reserves. (The Hawks were only 28-13 the rest of the way.)
Now, with Young propelling Atlanta’s upset pair of wins as an inferior seed, and Booker carrying the Phoenix Suns to the top of the Western Conference Finals – minus star goalie Chris Paul – before Game 2 on Tuesday. (9 p.m. ET on ESPN), we should learn from their examples and forget about a concept that has always made more sense in theory than in practice.
The awkward relationship between individual success and collective success
I can understand where the concept of “good stats, bad team” comes from. Back in the days when players were rated primarily by their per-game stats, and in particular points per game, it was easy to confuse volume score with performance that resulted in a win.
Without the evaluation framework provided by advanced statistics, the team’s registration was a shortcut to distinguishing imposters from the genuine article.
Consider the squad of nearly 1,000 since individual turnovers were first recorded in 1977-78 to average at least 20 points per game while playing at least two-thirds of their team’s games. Of those, just over a third came from teams with records below 0.500. Conventional wisdom is right, to a certain extent. The is a relationship between a top scorer’s team record and their own performance, as measured by my player’s net score per possession.
On average, my net score for players on teams that finished at 0.500 or better (plus-4.5 points per 100 possessions) is more than twice as good as for those on teams below 0.500 (plus-2.1 ). Yet the individual performance of a top scorer still explains only about 20% of the variation in the team record.
Essentially, judging a player’s ability by his team’s performance is a brutal measure. Modern statistical analysis gives us more surgical tools that can better separate individual performance. And while these tools indicate that most of the top scorers on lottery teams are in fact less valuable than those on playoff teams, this is not always the case.
After all, there are always four other players on the pitch, not counting the minutes a player is on the bench. So that’s the lowest-rated player by my metric in that 20-point scorer group (Jeff Malone with the Utah Jazz 1991-92) could play in a team that went 55-27 and made it to the final. of the conference thanks to stars Karl Malone and John Stockton.
At the other extreme, Anthony Davis’ performance in 2018-19 ranked in the top 25 of that group, the highest for any player on a team under 0.500. (Granted, Davis played sparingly after publicly asking for a trade, but that only happened after the New Orleans Pelicans fell out of the playoff race.) A year later, after Davis was traded to the Los Angeles Lakers, he helped them win the championship. It turns out that he was certainly not an example of “good stats, bad team”.
Better support surrounds Booker and Young
There was no need to ask for a trade in order for Booker and Young to be in a better position to succeed. Their own teams achieved this by ultimately turning a series of lottery picks into a core of young talent and making skillful additions to those coins through free agency exchanges.
Weighted by minutes played, the Hawks have the third youngest rotation among teams in the playoffs, while the Suns are the sixth youngest. This contrasts sharply with their opponents in the conference finals, the Milwaukee Bucks (third oldest) and LA Clippers (oldest). In addition to Young, Atlanta’s core includes recent first-round picks John Collins, Kevin Huerter and injured De’Andre Hunter, while Phoenix has two third-year starters in No. 1 overall pick Deandre Ayton. and Mikal Bridges.
For these groups, the two teams collected keys during the last offseason. For the Suns, it was All-NBA playmaker Chris Paul, whose veteran example helped Booker and the other young Phoenix players translate an unbeaten streak in last year’s standings into one. full season of success, as well as forward Jae Crowder. The Hawks have cocked their cap space to add starter Bogdan Bogdanovic and top reserve Danilo Gallinari, having already added Clint Capela in trade by the 2020 trade deadline.
Due to the new arrivals, Booker and Young have seen their scoring averages drop this season. Young’s 4.3 PPG drop is particularly notable. Young was one of 28 players in the league to see his score drop so dramatically at an age when most players’ stats are on the rise. This happened in part because Atlanta’s pace slowed down considerably, but Young’s assist rate also increased by 10% per possession as his use declined. It’s no surprise that Young is more willing to trust a better set of teammates.
Given that Paul took over the main ball handling duties and the Suns generally had a point guard on the pitch after using Booker in that role at times in previous seasons, his assist rate actually went up. decreased while its use increased. But the improved depth allowed Phoenix to rest Booker more, his minutes per game dropping from 35.9 to 33.9. His score dropped as a result.
How the two stars developed their games
While the change in perspective for the Hawks and Suns has more to do with the quality of their lineups, they have also benefited from the inevitable improvement from Young (22) and Booker (24). This was particularly evident in defense, a more legitimate criticism of the two players earlier in their careers.
In 2019-2020, Young’s minus-1.8 defensive RAPM (regularized adjusted plus-minus via NBAshotcharts.com) ranked in the bottom 10 of the league taking into account teammates and opponents who were on the field with him. At minus-1.3, Booker was also in the bottom 25. While defense remains a weakness, Booker (minus-0.7) and Young (minus-0.9) have improved outside of that range.
We’ve also seen Booker reach a new level of shooting during this playoff run. The Second Spectrum’s qSI (Quantized Shooter Impact) metric measures how well players surpass the effective field goal percentage expected for an average player on the same shot attempts based on location, type and shot. distance from nearby defenders. Booker also excelled in this category, ranking 59th in the league (minimum 100 field goal attempts) with a qSI of plus-7.1 during the regular season. In the playoffs, that jumped to plus-12.0, sixth best in the same group.
In Young’s case, game creation came to the fore. He has assisted nearly half of his teammates’ goals scored on the field in the playoffs, according to data from Basketball-Reference.com, the highest estimated rate in a streak of more than 10 games since Russell Westbrook in 2016. According to Stathead.com, Young is set to join Westbrook (twice), James Harden, LeBron James (four times) and John Wall as the fifth player since 1977-78 with an attendance rate of over 40% and a utilization rate. greater than 30% in the same playoffs.
By this point, Booker and Young have more than proven that their statistical results can translate into team success. For the next generation of like-minded players, we shouldn’t wait for those kind of playoffs to assess individual performances on their own merits rather than their teams’ records.
Let’s stop using the phrase âgood stats, bad teamâ and instead use stats that better reflect contributions to victory than points per game.