Be Lego: High performing teams and the search for “no stats All Stars”
Excellence starts at recruitment. In high sports arenas this is often called talent identification. If we want therefore to develop great teams and produce excellence, talent ID is key. Typically, it may not be as simple as one may think. As England’s greatest ever bowler laces his boots up for one final Test Match, and England’s male football team head into an all-important semi final clash, it is timely to consider how we understand individual performance in complex systems.
The greatest instinct is to identify who is ‘best’. Who has passed the test with 100% and accumulated a variety of A*’s? Who is the person with most goals in their career or this season? Who comes with the greatest reputation, even if that is one that is self-projected? Where are the elite in the field? For sure, skill mastery is crucial for excellence in teams. Skill mastery and talent are not synonymous, however. There is not a direct correlation between the team output and the sum of its parts, a fact that irks a proportion of those watching the England football team during the Euros. To create the best teams, we need to consider talent hidden by statistics and reputations.
Imagine that you’re a basketball coach. You have two players that played half the game each in the same position. This is their game data:
Players - Points - Rebounds - Assists
Player A - 13 - 05 - 03
Player B - 04 - 01 - 02
It is not unreasonable that you observe Player A is outperforming Player B. You may choose the give Player A more game time next match and work out strategies to improve Player B to fix what is clearly going wrong. Perhaps Player B does not feel sufficiently safe to take inter-personal risks?
What if the data showed the following for the time spent on court together?
Players - Points - Rebounds - Assists
Player A - 13 - 05 - 03
Player C - 09 - 04 - 02
Player D - 10 - 01 - 03
Players - Points - Rebounds - Assists
Player B - 04 - 01 - 02
Player C - 21 - 07 - 04
Player D - 16 - 04 - 07
The team performed better with Player B than Player A, despite the gulf in their individual performance. Why?
Shane Battier was a Player B. Battier has been described as a “marginal NBA athlete”, by his coach, but also recognised that “we have been a championship team with him and a bubble playoff team without him.” Apparently, his game is a combination of “obvious weaknesses and nearly invisible strengths.”1 When he is on court all the pieces begin to slot together. His moniker is Lego as a result. He is an All Star, even if the stats don’t back up the fact.
During the 1980’s, Norwegian Sports Psychologist, Willi Railo, coined the term “cultural architect”. These were people “who possess the ability to change the mind-set of others and they are able to implement the coach’s strategic plan in the team.”2 The challenge is to identify the who they are.
Battier created the “Catalyst Effect”. This is where the “team effectiveness is improved, members raise the performance of others and ultimately higher level results.”3 He is a true Cultural Architect. One that is typically invisible and under-valued in the competition of more storied and celebrated colleagues.
In the run up to the 1966 Men’s World Cup, manager Alf Ramsey gave a debut to unheralded Jack Charlton at the grand old age of 30. The less talented and glamorous of the Charlton brothers asked his new manager why he had been selected. “I am not picking the best players, I am picking the best team”, was the response. Jack Charlton was a catalyst for the team performance. He was a Lego player.
The perspective of Alf Ramsey is still unusual. Most understand teams as complicated systems. If we want the best team, we maximise each persons’ potential and therefore performance, to squeeze each ounce of performance from the team components. The outputs of this we measure. There is a litany of spreadsheets capturing seductive, but largely meaningless data. The performance as measured is valued and rewarded accordingly. Alas, work as measured is not work as done.
As we begin to embrace and understand systemic complexity, we may find alternative routes to high performing teams and complimentary ideas. Complex Adaptive Systems understand the system as the sum of its parts and its interactions. In our ever increasingly intricate ecosystem, it is the inter-personal synergies that drive team performance 4 (A fact that Portugal manager may wish to reflect upon as he supported the iconic Cristiano Ronaldo petulantly strop like a spoilt toddler at each imperfect pass, but would be just as applicable in other healthcare domains too).
Such a perspective would reduce the focus on specialist silos, as they would be enhanced with multi-disciplinary perspectives. Performance is not considered discrete. Data obsession of who scored, who assisted, how far someone ran gives a sense of understanding. It is limited at best. Performance is contextual. The observed data point is the manifestation of millions of actions, inactions, constraints and affordances that ebb and flow throughout the work. The true performance output of an individual is the combination of both visible actions and translucent interactions.
Leaders need to strive harder to gain sight of the near invisible strengths present in teams and value their no stat All Stars. The catalysts for change may not be who or where they immediately seem to be. We will need more Lego.
1. Lewis, M. The No-Stats Allstar. NY Times. 2009
2. Collins, D., and J. Collins. "Putting them together: Skill packages to optimize team/group performance." Performance psychology: A practitioner’s guide (2011): 361-380.
3. Toomer, Jerry, Craig Caldwell, Steve Weitzenkorn, and Chelsea Clark. The catalyst effect: 12 skills and behaviors to boost your impact and elevate team performance. Emerald Group Publishing, 2018.
4. Krabben, Kai, Dominic Orth, and John van der Kamp. "Combat as an interpersonal synergy: An ecological dynamics approach to combat sports." Sports Medicine 49 (2019): 1825-1836.