GBPF MALE AND FEMALE AVERAGE: LIFTS, TOTALS, ATTEMPTS AND JUMPS
By Jake Downes
"Powerlifting. Its beauty is in its simplicity”.
There could not be a truer statement to sum up what it is for me. It’s simple, get on the platform and perform better than you did last time and you’ve done your best. As a coach, your main duty is to peak the athlete both physically and mentally so that they achieve a personal best in at least one of the 3 lifts. Do that and you’ve gone some way to doing your task. It doesn’t always matter if they win or not, it’s simply getting up and achieving more than previously. I know many newcomers to the sport feel they have to lift a certain amount to even contemplate competing so I felt it was necessary to point out that it is not. It’s about becoming stronger, for you, no one else.
So now that I’ve not scared off the newcomers, I’d like to help coaches and athletes see how they can utilise the information contained within these graphs (and tables).
When training a powerlifter (or at a club) it’s important to understand the level they are currently at and where they want to progress to. From this you can then go about setting realistic expectations for the athlete. Now to get a grasp on where are currently is relatively simple; most recent personal bests, be it at competition or in training. Looking at the average charts can help you set realistic expectations of how competitive they might be on a national level.
There isn’t a whole lot of coachable data to be taken away from the average total, average squat, average bench press & average deadlift, however it would help to ascertain a higher standard for qualifying totals (QT’s). A higher qualifying total would only push the sport further and improve the quality of the standard throughout the UK. I hope this information has gone someway to helping the powers that be increase the QT’s for next year.
I see these averages being applied in clubs. For example: You’ve got 20+ lifters who are all at a high standard for their regions but unsure nationally. Well, having this information to hand, they could glance over; see if their total is above the national average, thereby knowing if they are in the top portion for the respective weight category. Alternatively, the coach can set the average as standards within their club. It would be a pretty high standard if your lifters were above the “average” in the UK for their respective weight class.
The average chart is more “wow this is cool, I’m above average at National level” for the novice lifter, which may help them with motivation and drive for further competitions.
The information contained within the table has more applicable information to the athlete and the coach.
For example: we can see that in the female 84kg class, the average attempts green lighted were 6.3. This might lead us to make lower attempt selections to get a higher green light rate, that may then edge out the competition, after all making a lift is going to give you a bigger total, than missing it.
The second set of data that is useable is the jumps between 1st and 2nd and then 2nd and 3rd. If we see on average that most people in your weight class take a 10kg+ jump on their 2nd to 3rd deadlift, but the made lifts is very low. Then we may look at jumping 5-7.5kg on your 3rd attempt, increasing the athletes’ chance of completion as well as then increasing their chance of out doing the competition.
Of course, the data can be interpreted in many different ways as the coach or athlete observes it. Keeping in mind that attempt selection is always going to be dependent on the athlete in question, so this data doesn’t give us an exact “how to” but it offers a hand in what direction we can take and may help to guide future attempts. As the competitions grow, so does the sample size making the information more astute.
I think it’s only right in pointing out that in many weight classes there is an outlier. An outlier who’s total (or single lifts) is so much higher than the rest that it sends the averages higher than they might have otherwise been. Most of these outliers are known via social media platform. The biggest disparity coming in the Male 120kg class: Tony Cliffe (total; 145kg higher than 2nd).
More research needs to be done to make this kind of data more applicable but by starting here, it is giving us a grounding, on which we can go forward from. The data is limited due to the outliers as mentioned above; this does however lead me to rethink the next set of data. Including the amount of lifters per category (example, there was only 1 competitor in Male 59kg class). With more information we might be better placed to set a definition on “novice”, “intermediate”, “advanced” and “elite” based upon the average standings, including the single lifts. We may see a lifter who’s total is in “advanced” whilst their bench may be “novice”. This could help coaches put a level on the athletes they have under their tutelage.