I noted in an earlier post that one of my particular interests in monitoring European football leagues is the identification of dominant game winning performances. I that post I used the example of Liverpool v Norwich in the opening day of the EPL season (link).
I look for the same dominant behaviours in NRL rugby league games. Last night, in the first week of the Finals, the Roosters demonstrated this behaviour in their game against the Rabbitohs (link) in front of a crowd of 30,000 at the Sydney Cricket Ground. The Roosters led 26v0 at half time and scored six tries to one. The NRL record is:
My visualisation of the scoring pattern is:
The NRL report of the game notes the Roosters produced “arguably their most clinical performance of the season” (link). It added “The Roosters … produced a masterclass”.
My recent posts have looked at changes in roles in sporting organisations. I am struck by the diversity of roles in these organisations. What is becoming evident to me is the role leaders will play in the flourishing of these organisations and their transformations that will occur as they deal with change.
I do think recent discussions about the roles of technical and sporting directors (link) has focused this conversation as have debates about investing in learning opportunities (link). After reading my account of Graham Taylor’s coaching journey (link), a friend involved in coaching football noted “Graham wrote that he lost his opening 12 games of the season at Lincoln and was fortunate to still be in the job”. It was interesting to me that someone at Lincoln saw Graham’s potential as a coach and dealt with the local political issues about his appointment and supported him through to become Lincoln’s youngest and most successful coach. I believe that was a great example of leadership.
I am indebted to Jo Gibson for her encouragement as my PhD student to explore leadership and followership. She has helped me think about how entangled these two are and in the process has introduced me to Karen Barad and her sense of “individuals emerging through and as part of their entangled intra-relating” (link). Jo has led me to Emma Uprichard and Leila Dawney‘s (2016) discussion of data diffraction as well (link). Emma and Leila consider how we respond when the data we collect, through a variety of mixed methods, diffract rather than become integrated. These data “provide an explicit way of empirically capturing the mess and complexity” that is intrinsic to “the social entity being studied”.
Many of these issues came together when I discovered the work of Julien Clement, an assistant professor of organisational behavior at Stanford Graduate School of Business. He has been considering How to Stay Ahead When the Rules Change (link). Lee Simmons (2019) (link) introduced us to Julien in a review of his work.
Julien is the author of Sensing the Next Game Changer: Organizational Architecture, Cognition and Adaptation to Environmental Change (link). His paper provides the detail that Lee points to and is a discussion of “a theory of collective sensemaking in the face of environmental change”.
To explore staying ahead in business, Julien looked at eSports professional multiplayer games. He noted:
the elements of business competition are there: eSports teams are high-stakes, profit-seeking enterprises that can earn millions of dollars a year and that use strategy and tight coordination in an arena where sudden and unforeseen changes occur in the form of game updates.
Julien looked closely at a game called Defense of the Ancients 2. Lee Simmons (2019) (link) observed of this approach:
His theory was that something in the very structure of organizations — of any sort — shapes how the individuals inside them see the world. And that worldview, in turn, can make them slow to adapt.
In Defense of the Ancients, disruption comes in the form of revisions to the game’s code. Julien’s research considered “when these updates came out, would teams revise their game plan, or would they continue with the same plan and just swap in stronger heroes?” Would this be systemic change or “business as usual with different personnel?”
When hero abilities changed, most teams responded only by switching heroes.
Only after a lag of several weeks did some begin to revise their strategies.
Immediately after a change, teams were less innovative than in stable periods.
Small, nimble teams exhibited the same inertia that big corporations exhibit when faced with change.
It was a failure to recognize the full, systemic implications of external change.
Firms fail to adapt when they focus on specific tasks at the expense of system-wide behavior.
Julien pondered if in “times of tumult, could strong leaders guide their organization’s adaptation?” He noted:
information flowed in a hub-and-spoke pattern from the leader to the other players. In others, the flow was more even and distributed, as players seemed to be mutually adjusting to each other rather than just listening to the captain.
Teams with flatter structures, where everybody seemed to be talking and contributing, were more likely to recognize the need to look for a new strategy rather than just swapping in new heroes. Only when the updates had an obvious and direct system-wide effect, such as far-reaching changes in the rules of the game, did teams with dominant leaders adapt faster.
A central leader may speed things up when it’s fairly clear how the organization should respond to change. But when the problem is to figure out how to respond, a less hierarchical structure might be more effective.
His conclusion to this research was:
Companies might view change as an opportunity, especially when the consequences of the change aren’t immediately obvious. When things are moving fast, it’s natural to narrow your focus and concentrate on keeping the ship on course. But it might be smart, this study suggests, to take a step back and think about where you’re headed and how the entire organization works.
This conclusion resonates powerfully with the issues discussed at the start of this post. I think it provides an excellent example of the entaglement of leadership and followership and how organisations enable a less hierarchical structure that is not a threat to the organic structure of the organisation. In the process it will be fascinating to see how dynamic they can be in response to structural changes in performance environments. As Julien concludes in his paper, discussions about change advance “our understanding of the mechanisms underlying organizational adaptation and the coordination structures which may facilitate it”.
What will be of great interest is how we develop our cognitive understanding of what will be and how we as decision makers can facilitate mental time travel into what will be given that we are often appointed for what we did. It seems to me that we will have to make sense of entanglement and diffraction as we address and flow with change.
Finn Marsland is graduating as a Doctor of Philosophy at the University of Canberra’s graduation ceremony in October 2019 (link).
The title of Finn’s thesis is Macro-kinematic performance analysis in cross-country skiing competition using micro-sensors. I am delighted that Finn has completed this remarkable thesis. From the outset, I saw his work as a great example of praxis in his combination of practice as a coach and a profound theoretical understanding of emerging micro-sensors developed with Colin Mackintosh at the Australian Institute of Sport. Dale Chapman was unable to attend the meeting too but he became a key member of Finn’s support team and who brought enormous knowledge of winter sports to the research team.
Finn’s research “lays the ground-work for future research and practical applications, which could include daily training monitoring, course profiling, evaluation of sub-technique efficiency, and similar algorithm development for the Freestyle technique”.
I met Finn in 2009 when I started my tenure at the University of Canberra. Our meeting was with Gordon Waddington and Judith Anson in the Physiology Canteen at the Australian Institute of Sport. It was a very important meeting that combined Gordon and Judith, champions of Finn’s work and Finn in the applied context of the Institute. Colin Mackintosh, pivotal in Finn’s use of micro-sensors, was unable to be at the meeting but he and Finn had met previously to prepare for the meeting.
Thereafter, Finn became one of Sport’s first PhD students. For me, it was an opportunity to explore Finn’s praxis ideas as a coach researcher. At that time he was Cross Country Skiing Program Director and Coach of Ski and Snowboard Australia.
Finn’s thesis contains four peer reviewed, published papers and one yet-to-be published papers.
The abstract of Finn’s thesis is:
Performance analysis in cross-country skiing is constrained by the variability of
environmental conditions and terrain, and complicated by frequent changing between sub-
techniques during competition. Snow conditions and skiing speed change constantly from day
to day and often during the day, and competition courses vary in the length, gradient and
distribution of hills from venue to venue. The aim of this body of work was to develop a new
performance analysis method, using a single micro-sensor, to continuously detect skiing sub-
techniques and quantify the associated kinematic properties that describe a skier’s
performance during training and competition. Of particular interest was the relative use of
each sub-technique, together with velocity, cycle rate and cycle length characteristics
collectively defined as cross-country skiing macro-kinematics. Over five studies this thesis
explores proof of concept through detection of different sub-techniques, develops an
algorithm for the quantification of macro-kinematic parameters during training, demonstrates
the use of a refined algorithm to investigate performance demands and macro-kinematic
variability over an entire competition, compares macro-kinematics between different types of
event, and finally examines the implication for coaches arising from analysis throughout
rounds of a sprint event.
The first study (Chapter 3) (link) in this research showed how the cycles of sub-techniques of both classical and freestyle technique could be identified using a single micro-sensor unit, containing an accelerometer, gyroscope and GPS sensors, mounted on the upper back. Data was collected from eight skiers (six male and two female), of which four were World Cup medallists, skiing at moderate velocity. Distinct movement patterns for four freestyle and three classical cyclical sub-techniques were clearly identified, while at the same time individual characteristics could be observed.
The second study (Chapter 4) (link) quantified macro-kinematics collected continuously from seven skiers (four female and three male) during an on-snow training session in the classical technique. Algorithms were developed to identify double poling (DP), diagonal striding (DS), kick-double poling (KDP), tucking (Tuck), and turning (Turn) sub-techniques, and technique duration, cycle rates (CR), and cycle counts were compared to video-derived data to assess detection accuracy. There was good reliability between micro-sensor and video calculated cycle rates for DP, DS, and KDP, while mean time spent performing each sub-technique was under-reported. Incorrect Turn detection was a major factor in technique cycle misclassification.
The third study (Chapter 5) (link) used an algorithm with improved Turn detection to measure macro-kinematics of eight male skiers continuously during a 10 km classical Distance competition. Accuracy of sub-technique classification was further enhanced using manual reclassification. DP was the predominant cyclical sub-technique utilised (43 ± 5% of total distance), followed by DS (16 ± 4%) and KDP (5 ± 4%), with the non-propulsive Tuck technique accounting for 24 ± 4% of the course. Large within-athlete variances in cycle length (CL) and CR occurred, particularly for DS (CV% = 25 ± 2% and CV% = 15 ± 2%, respectively). For all sub-techniques the mean CR on both laps and for the slower and faster skiers were similar. Overall velocity and mean DP-CL were significantly higher on Lap 1, with no significant change in KDP-CL or DS-CL between laps. Distinct individual velocity thresholds for transitions between sub-techniques were observed.
In the fourth study (Chapter 6) (link) macro-kinematics were compared between six female skiers competing in Sprint and Distance competitions in similar conditions on consecutive days, over a 1.0 km section of track using terrain common to both competitions to eliminate the influence of course topography. Mean race velocity, cyclical sub-technique velocities, and CR were higher during the Sprint race, while Tuck and Turn velocities were similar. Velocities
with KDP and DS were higher in the Sprint (KDP +12%, DS +23%) due to faster CR (KDP
+8%, DS +11%) and longer CL (KDP +5%, DS +10%), while the DP velocity was higher
(+8%) with faster CR (+16%) despite a shorter CL (-9%). During the Sprint the percentage of
total distance covered using DP was greater (+15%), with less use of Tuck (-19%). Across all
events and rounds, DP was the most used sub-technique in terms of distance, followed by
Tuck, DS, Turn and KDP. KDP was employed relatively little, and during the Sprint by only
half the participants.
The final case study (Chapter 7) focused on the insight coaches could gain from examining
variations in individual macro-kinematics for six female skiers across three rounds of a classic
Sprint competition. Individual macro-kinematic variations were influenced by personal
strengths and preferences, pacing strategies, and by interactions with other skiers in the head-
to-head rounds. Potential coaching implications include using a range of CR and CL during
training, modifying these parameters during training to work on weaknesses, and altering
macro-kinematic race strategies depending on the course terrain, event round and on other
In conclusion this thesis outlines the development of a new cross-country skiing analysis
method that uses a single micro-sensor and a unique algorithm to effectively measure macro-
kinematic parameters continuously during training and competition. This tool could be used
by researchers, coaches and athletes to better understand training and competition demands
and enhance performance. This research lays the ground-work for future research and
practical applications, which could include daily training monitoring, course profiling,
evaluation of sub-technique efficiency, and similar algorithm development for the Freestyle
I am looking forward to doffing my cap to Finn in October when he officially becomes Dr Finn Marsland after a decade of seminal research. His upgrade seminar was in 2012 (link).