So what are you going to do? You have to find young untried players who will eventually turn into Thomas Waldrom, Schalk Brits, Chris Aston or Tom Wood. How are you going to identify them when they haven't had a chance to prove themselves and amass some statistics to prove that they have the stuff of the egg-chasing gods.
You turn to the geeks, that's how you do it. How so? You regress your way to success. You would use my RugbyMetrics tool (click on this LINK to see all of the articles on RugbyMetrics). Then you would take a game film of your targeted acquisition and using the tool, digitize that player's performance. From there you would use advanced statistics to create a mathematic model (using regression and Bayesian inference) to determine if your player has the right stuff.
How does it work? The seeds of athletic greatness are sown early. However they may not become manifest because the player is not on a team that enhances his skillset, or he is blindside oriented on a team that is predominantly openside oriented. There are many many reasons, however that player will demonstrate the subtle qualities that shows that he has the key performance indicators that tend to greatness.
So what are these KPI's or key performance indicators? They are a new set of statistics that are gleaned from data mining every aspect of the game. These are proprietary knowledge to the users of the system. But as a trivial example, one finds that an Olly Barkley will average x amounts of carries, gaining y amounts of yards, in a certain ratio to the opposition yards gained. This is objective, scientific knowledge of the game of rugby that comes from the field of predictive analytics.
So once you have the three mathematical formulas gleaned from going through mountains of statistics, you can eliminate the pretenders and give yourself a roster of possible stars. This is not meant to replace the years of coaching and scouting, but rather it is meant to give the teams a scientific, valid starting point when scouting for new team members.
The interesting aspect is that the front 8 will have different formulas than the back seven, and each position will have different regression parameters in the models. Also style of play comes into effect as well. If you like a Tom Wood style of play, you would determine the mathematical model by analyzing his performance and looking for players who have similar numbers to him. It sure beats the shot in the dark method of a player that "looks good".
If you have any questions, please leave a comment and I will answer them.