'That's ideology, not science' - Renowned sports scientist steps in on transwomen in rugby debate

Sports scientist Ross Tucker has waded into the debate over the participation of transwomen in rugby and the safety concerns around their participation in women's rugby.

In July The Guardian revealed that World Rugby appear set to exclude transwomen from playing womens' rugby on safety grounds following a workshop on the issue. A 38-page draft document suggested “at least a 20-30% greater risk” for a women who is tackled by a player who has gone 'through male puberty'.

The news was greeted with heavy criticism from LGBTQ advocates,  many of whom contend that the jury is still out on the scientific argument for excluding transwomen. This week Michelle Daltry, who represents LGBT+ Sport Cymru said: “We are asking rugby clubs at all levels of the game to stand with us against a ruling that is exclusionary and that will impact some of the most vulnerable people in the community”.

Now renowned sports scientist Ross Tucker has attempted to answer the question in an extensive Twitter thread on the thorny subject. Tucker, a World Rugby consultant, argues that transwomen athletes in rugby enjoy a significant advantage over their biologically female peers and that these advantages give rise to a higher risk of injury.

"This has been a common argument in the trans women in rugby debate. People have the idea that unless you *directly* study rugby AND show that TW cause injuries, it can’t be evidence based. Of course it can - there are peer reviewed studies that show two related things"

"First, you have so many studies that identify both performance determinants and risk factors for injury in rugby. Dozens of studies identify when injury occurs, and thus what the significant risks for injury are. Similarly, performance is multifactorial but is KNOWN to be significantly influenced by a handful of testable/measurable factors. In fact, these measurable factors are so crucial and “robust" that teams actually have minimum standards for them, and select or drop players based on achieving these targets. They’re not “guesses”.

"Then second, you have a number of peer reviewed studies that have examined and described both the performance AND biological differences between M and F. So performance differences in tasks ranging from running to jumping to kicking to punching to throwing are known, and so too are biological factors underpinning the differences. For instance, it is known that throwing, kicking, punching, jumping, hitting etc are 20% to 160% better in males, elite & untrained, as a result of biological variables that include muscle mass, levers, tendons etc

"This is really important because if you know the outcome (B, performance), and you know the factors that contribute significantly to the outcome (A, biological variables), then it’s hardly a leap to surmise what would happen to B if A changes, or doesn’t change. Make sense?

"So you take these parallel streams, and next, consider 11 longitudinal studies, all peer reviewed, that show that T suppression only removes a very small part (or none) of the muscle mass, volume, or strength advantages, and doesn’t change skeletons. What does this mean?

"Remember that if B (performance or injury risk) is the result of A (biology), and you know that A is barely changed, then on what basis would you speculate that B is going to change meaningfully? You’d have to introduce something new to even make a start on this theory.

"Basically, you’re surmising that no advantage DESPITE the persistence of measured biological advantages? That’s ideology, not science. We can get a whole lot more specific than this. Here’s one example, for injury risk factors...

"It is known that in rugby, injury is the result of excessive energy transfer to a player (this is literally the definition). This is a function of mass, speed and force exerted, along with the ability of a player to absorb that force/torque. So we have A, B and C = injury

"We know, for instance, that head injuries occur when head kinematics (acceleration) and kinetics (neck force and moments) exceed a threshold. So there are DIRECT links between these risk factors and the ‘inputs’, which are speed, mass and force applied in contacts.

"Now, we can take mass, just to *ILLUSTRATE* a point, and ask "What would happen in a typical male-bodied mass tackled a typical female bodied mass?”. In the elite game, we know the mass disparity, so we can model “typical vs typical” and we discover that the RISK FACTORS are 20% to 30% higher based ON MASS ALONE. Remember that injury is three variables - mass, strength & speed (or rate of force application, perhaps more accurate). So if we factor in strength disparities, plus speed, might the risk go up even more? Yes. Each may be additive.

The premise of the model is evidence-based: Injury & performance are the DIRECT result of variables A, B & C. Thus, if you take A, B & C, and find:

a) They’re significantly higher in M than F;

b) Reducing T does not reduce A, B and C to female levels;

what can you conclude?

"The ONLY conclusion you can draw is that injury risk & performance will remain significantly elevated. To argue anything other than this means you have to redefine injury and negate variables that are KNOWN to significantly elevate performance. It’s impossible. On what basis will the contributing factors remain similar and the outcome change? The entire context will have to change. Please note - this does NOT mean that A, B and C are exhaustive.

"Things like technique and context modify risk, we know this. But you don’t need to assess this to make an evidence-based conclusion that risk will increase and fairness will be compromised when the links between the input and output are so clear. Also, it is acknowledged that more research is required - it would be great to actually quantify force in the tackles when mass, strength and speed are all factored in. We are committed to this research, but it’s not easy to do. You’re asking to quantify the biomechanics of this kind of situation across hundreds of simulations with different inputs. It’s not a fun watch:

"This kind of biomechanical study must be done, but it’s not quite as simple as this crude illustration suggests. But it WILL BE explored. But its absence is not sufficient to conclude that there’s no issue.

"There’s plenty of reason to link our knowledge of biology, performance and injury risk, and to ask how they outcomes change (they don’t) if the inputs change (they don’t, either. Which is kind of the point). So that’s the evidence-base. Incomplete? Yes. Guess? No way

"Anyway, that’s all for now. The other common response is that some women are heavier/stronger/faster than some men, and since the ranges overlap, there should be no problem with cross-over, or case by case assessment. That’s all kinds of wrong, but it’s for another day. END

Oh, and this will definitely be a subject on a future episode of @sportsscipod. We just have to be patient, because I can only do it after World Rugby's final policy is announced. Then I can talk about the whole thing, not pieces of if, and semi-transparency helps nobody. END END

While Tucker voice is a powerful one in rugby. Tucker, a PhD in Exercise Physiology, was named by Mail and Guardian in their list of Top 200 Influential Young South Africans, and by the Minister of Sport as one of the 100 Influential people in South African Sport.