WEBVTT 00:00:00.000 --> 00:00:02.839 Be critical. Think about what you are measuring 00:00:02.839 --> 00:00:05.519 and why you're measuring it. And does the metric 00:00:05.519 --> 00:00:07.620 actually represent what you think it does? And 00:00:07.620 --> 00:00:10.419 so even if you don't use the domains that I've 00:00:10.419 --> 00:00:12.740 presented in this study, I would love it for 00:00:12.740 --> 00:00:15.720 you to go out and be very critical and understand 00:00:15.720 --> 00:00:18.219 the reasoning behind the selection of the test 00:00:18.219 --> 00:00:22.600 and the selection of the metric. Hi, Mary. It's 00:00:22.600 --> 00:00:24.699 my pleasure to have you on Evidence Strong Show. 00:00:24.839 --> 00:00:26.940 If you could briefly introduce yourself. My name 00:00:26.940 --> 00:00:29.579 is Mary Claire Jeannot. I typically go by MC 00:00:29.579 --> 00:00:32.140 in the sport environment. And I just completed 00:00:32.140 --> 00:00:34.899 my PhD at La Trobe University under the supervision 00:00:34.899 --> 00:00:38.420 of Dr. Lachlan James, Dr. David Carey, Professor 00:00:38.420 --> 00:00:41.119 Sam Robertson, and Professor Paul Gaston. I'm 00:00:41.119 --> 00:00:42.780 now working with the Canadian Sport Institute 00:00:42.780 --> 00:00:46.820 as a lead S &C coach and data analyst. And I've 00:00:46.820 --> 00:00:49.600 just started a new position as the IST lead for 00:00:49.600 --> 00:00:51.740 the Canadian women's volleyball team. And for 00:00:51.740 --> 00:00:54.579 the Australian listeners, an IST lead is kind 00:00:54.579 --> 00:00:56.420 of like a high performance manager type position, 00:00:56.659 --> 00:00:59.299 slipping along those lines. So high performance 00:00:59.299 --> 00:01:03.219 sport, data analysis, these are four topics that 00:01:03.219 --> 00:01:06.159 lead to the topic of today's conversation, which 00:01:06.159 --> 00:01:09.459 is strength, measurement and testing. So let's 00:01:09.459 --> 00:01:11.879 start with why. Why it is important. Why did 00:01:11.879 --> 00:01:14.159 you, because that was the topic of your PhD, 00:01:14.359 --> 00:01:16.299 isn't it? Yeah, correct. Why did you go there? 00:01:16.299 --> 00:01:18.060 This is the first. Yeah, great. So as you kind 00:01:18.060 --> 00:01:20.640 of mentioned, this was the part of my PhD. and 00:01:20.640 --> 00:01:23.060 this review that has just been published kind 00:01:23.060 --> 00:01:25.980 of kick -started this whole concept that led 00:01:25.980 --> 00:01:30.260 to my PhD. And it is well accepted in the strength 00:01:30.260 --> 00:01:32.640 and conditioning space that maximal lower body 00:01:32.640 --> 00:01:34.739 strength can be expressed in a number of different 00:01:34.739 --> 00:01:37.590 ways. This can look like... a rapid foot strike 00:01:37.590 --> 00:01:41.290 in a sprint, a vertical jump to block a volleyball, 00:01:41.510 --> 00:01:44.170 or a ruck in rugby, where an athlete is moving, 00:01:44.230 --> 00:01:46.310 you know, not only their own mass, but an opponent 00:01:46.310 --> 00:01:48.370 and maybe two opponents' mass at the same time. 00:01:48.450 --> 00:01:50.230 Now, these are all expressions of lower body 00:01:50.230 --> 00:01:52.450 strength, but as we know, they represent something 00:01:52.450 --> 00:01:54.390 different, and we use different training strategies 00:01:54.390 --> 00:01:56.769 to be able to target each of these different 00:01:56.769 --> 00:01:58.750 strength expressions. And it is important to 00:01:58.750 --> 00:02:01.450 monitor strength qualities that are expressed 00:02:01.450 --> 00:02:03.370 in sport. We're not just going to necessarily 00:02:03.370 --> 00:02:07.010 measure one rep max back squat. and assume that 00:02:07.010 --> 00:02:09.069 it's going to translate to all the different 00:02:09.069 --> 00:02:11.349 expressions of strength that I kind of briefly 00:02:11.349 --> 00:02:14.870 introduced. And so S &C coaches and sports scientists 00:02:14.870 --> 00:02:18.409 have gone down the route of looking to measure 00:02:18.409 --> 00:02:21.270 more unique or more specific qualities of strength 00:02:21.270 --> 00:02:23.550 that are more specific to different force expressions 00:02:23.550 --> 00:02:26.250 experienced by the athlete. This can be, this 00:02:26.250 --> 00:02:28.030 is really good, but it can be a slippery slope 00:02:28.030 --> 00:02:30.430 sometimes as we try to refine, refine, refine 00:02:30.430 --> 00:02:34.689 down to very specific and very like discrete 00:02:34.689 --> 00:02:37.180 metrics. Because it's not necessarily telling 00:02:37.180 --> 00:02:39.020 us more information than what a bigger, more 00:02:39.020 --> 00:02:41.379 inclusive metric would. And this is particularly 00:02:41.379 --> 00:02:44.219 true when we start measuring strength looking 00:02:44.219 --> 00:02:47.180 at or using force platforms. They've been used 00:02:47.180 --> 00:02:50.219 a lot in the literature to measure very unique, 00:02:50.340 --> 00:02:52.599 very small, different discrete types of strength 00:02:52.599 --> 00:02:55.780 expression. And instead of creating more clarity 00:02:55.780 --> 00:02:58.580 on how strength is expressed in sport, it's actually 00:02:58.580 --> 00:03:01.219 clouded our understanding and created some confusion 00:03:01.219 --> 00:03:03.000 because we don't know which metrics are important, 00:03:03.099 --> 00:03:06.400 which metrics. may be redundant. And so that 00:03:06.400 --> 00:03:09.539 kind of underlined the basis of my PhD, which 00:03:09.539 --> 00:03:12.039 was what are these strength qualities that underlie 00:03:12.039 --> 00:03:14.979 these strength metrics that we regularly collect 00:03:14.979 --> 00:03:16.400 in the strength conditioning environment? And 00:03:16.400 --> 00:03:19.080 how can we best identify them using the wide 00:03:19.080 --> 00:03:21.740 body of metrics that are available in the literature? 00:03:21.939 --> 00:03:24.000 And that's kind of under the assumption that 00:03:24.000 --> 00:03:26.520 there are physical characteristics that underlie 00:03:26.520 --> 00:03:28.979 performance of a task. Metrics related to a specific 00:03:28.979 --> 00:03:31.319 physical characteristic, such as the ability 00:03:31.319 --> 00:03:33.379 to produce really, really high forces or the 00:03:33.520 --> 00:03:35.340 ability to produce force really, really quickly 00:03:35.340 --> 00:03:38.360 will likely be highly correlated. So if we have, 00:03:38.400 --> 00:03:40.919 for instance, peak force in a squat jump and 00:03:40.919 --> 00:03:43.419 peak force in a countermovement jump, you know, 00:03:43.419 --> 00:03:45.500 assuming that those are very similar tasks, they 00:03:45.500 --> 00:03:47.400 likely will be highly correlated because someone's 00:03:47.400 --> 00:03:49.900 ability to produce high force dynamically underlies 00:03:49.900 --> 00:03:52.080 both of those metrics. Now, because of this, 00:03:52.259 --> 00:03:55.099 it may be advantageous to group metrics that 00:03:55.099 --> 00:03:57.419 are highly correlated and partition those who 00:03:57.419 --> 00:03:59.539 are not very highly correlated as they are likely 00:03:59.539 --> 00:04:02.219 underpinned by similar or different characteristics. 00:04:02.729 --> 00:04:05.430 And this kind of led us to this strength classification 00:04:05.430 --> 00:04:08.349 process, which can be used by practitioners to 00:04:08.349 --> 00:04:10.990 help guide test and metric selection, as well 00:04:10.990 --> 00:04:13.150 as the metric interpretation within the strength 00:04:13.150 --> 00:04:15.389 diagnosis process with the understanding that 00:04:15.389 --> 00:04:18.009 there may be a simpler or a more straightforward 00:04:18.009 --> 00:04:20.670 understanding of what different types of strength 00:04:20.670 --> 00:04:23.449 characteristics exist and finding which metric 00:04:23.449 --> 00:04:25.550 best represents that particular strength characteristic. 00:04:25.990 --> 00:04:27.910 All right. So just to please let me know whether 00:04:27.910 --> 00:04:31.029 I understood correctly. So strength is this big 00:04:31.029 --> 00:04:33.189 term we all... about strength and getting our 00:04:33.189 --> 00:04:35.670 athletes stronger but now you can measure it 00:04:35.670 --> 00:04:38.069 in different ways and strength can be expressed 00:04:38.069 --> 00:04:41.889 in different ways too it can be huge loads moved 00:04:41.889 --> 00:04:45.810 slowly or it can be lower loads but moved very 00:04:45.810 --> 00:04:49.730 explosively so what we measure so the tests we 00:04:49.730 --> 00:04:53.230 use may measure different things the things that 00:04:53.230 --> 00:04:55.389 are important for certain athlete for example 00:04:55.389 --> 00:04:58.529 so that would mean that from all the tests that 00:04:58.529 --> 00:05:02.160 are possible in strength testing we have to choose 00:05:02.160 --> 00:05:04.199 the ones that are important for this athlete, 00:05:04.300 --> 00:05:06.420 for this sport, for this position. And now we 00:05:06.420 --> 00:05:09.860 have to ensure that the ones we choose will be 00:05:09.860 --> 00:05:13.079 highly correlated with the underpinning ability 00:05:13.079 --> 00:05:15.540 or capability that is important for the sport. 00:05:15.720 --> 00:05:18.319 Yeah, correct. And just on top of that, you know, 00:05:18.319 --> 00:05:20.420 we can have a bunch of metrics that are highly 00:05:20.420 --> 00:05:23.100 correlated to a sport -specific skill. And that 00:05:23.100 --> 00:05:25.480 may, you know, it may be viewed by a practitioner 00:05:25.480 --> 00:05:27.519 that that's really good, that all of these metrics 00:05:27.519 --> 00:05:30.120 are highly correlated to, let's say, sprinting. 00:05:30.379 --> 00:05:32.060 And if all of those metrics are highly correlated 00:05:32.060 --> 00:05:34.939 to sprinting, it's likely that they may all tell 00:05:34.939 --> 00:05:37.060 you the same thing. And we don't necessarily 00:05:37.060 --> 00:05:39.759 want to just keep comparing an individual strength 00:05:39.759 --> 00:05:42.579 metric to a sport specific quality all the time, 00:05:42.600 --> 00:05:44.680 because that may just be very, very redundant. 00:05:45.000 --> 00:05:47.720 And, you know, if we're distracting, if we're 00:05:47.720 --> 00:05:49.439 trying to look at the holistic picture of an 00:05:49.439 --> 00:05:51.819 athlete and the holistic understanding of strength 00:05:51.819 --> 00:05:53.680 expression, that may be important for sports. 00:05:53.759 --> 00:05:57.160 So the first step is understanding what exists 00:05:57.160 --> 00:05:59.360 in an athlete. And this may differ from athlete 00:05:59.360 --> 00:06:01.160 to athlete. athlete, but what range and what, 00:06:01.240 --> 00:06:04.040 yeah, what range and force expressions or physical 00:06:04.040 --> 00:06:06.379 characteristics underlie performance of that 00:06:06.379 --> 00:06:08.939 athlete. And then we can go in and start relating 00:06:08.939 --> 00:06:11.959 each of those important pieces to sport performance. 00:06:12.199 --> 00:06:14.240 And then that's when the individual can, or the 00:06:14.240 --> 00:06:16.560 practitioner can determine which one of those 00:06:16.560 --> 00:06:18.339 characteristics are more important than the other. 00:06:18.439 --> 00:06:21.000 So would the goal be, this is the idea profile 00:06:21.000 --> 00:06:23.279 of the athlete in this sport, in this position, 00:06:23.379 --> 00:06:26.819 this is this athlete, something is missing or 00:06:26.819 --> 00:06:31.170 is lower or is... extremely high. Now we want 00:06:31.170 --> 00:06:34.689 to know what, then we want to relate it to capabilities. 00:06:34.750 --> 00:06:37.829 Then we want to choose the best test for this 00:06:37.829 --> 00:06:41.069 capability. Then we want to train and then measure 00:06:41.069 --> 00:06:43.209 again. That's how we would use it. Yeah, pretty 00:06:43.209 --> 00:06:45.410 much. So you would figure out, first you would 00:06:45.410 --> 00:06:47.970 figure out what range of strength qualities exist. 00:06:48.149 --> 00:06:50.689 And this can be looking at tests of a variety 00:06:50.689 --> 00:06:52.750 of different constraints, which we will go into 00:06:52.750 --> 00:06:54.870 later today. And then you'll be able to reduce 00:06:54.870 --> 00:06:58.250 them down to metrics from those tests. that tell 00:06:58.250 --> 00:07:00.550 you something unique. Then you can see where 00:07:00.550 --> 00:07:03.769 a potential gap is in that athlete. For instance, 00:07:03.910 --> 00:07:06.209 the athlete jumps high in a catamaran jump, lifts 00:07:06.209 --> 00:07:08.329 a lot of weight in a squat, has a high peak force 00:07:08.329 --> 00:07:11.350 in an isometric test, but has really poor reactive 00:07:11.350 --> 00:07:13.230 strength in a drop jump. We can go in and say, 00:07:13.310 --> 00:07:15.550 okay, we want to then measure that or, sorry, 00:07:15.589 --> 00:07:17.470 train that particular quality in the reactive 00:07:17.470 --> 00:07:18.829 strength because that's lower than everything 00:07:18.829 --> 00:07:21.250 else. But that may not be as important for a 00:07:21.250 --> 00:07:23.930 swimmer as it is for a field sport athlete, for 00:07:23.930 --> 00:07:26.589 instance. And so we can look at these domains 00:07:26.589 --> 00:07:29.560 or... range of strength qualities and first determine 00:07:29.560 --> 00:07:31.180 which ones are important for sport performance. 00:07:31.459 --> 00:07:33.519 And then we go in and say, okay, where are the 00:07:33.519 --> 00:07:35.500 gaps and where do they matter? All right. So 00:07:35.500 --> 00:07:38.759 we covered the why. We have a clarity on why 00:07:38.759 --> 00:07:42.019 we should even care. Now, how did you go about 00:07:42.019 --> 00:07:45.259 classifying what strength capabilities they are 00:07:45.259 --> 00:07:48.019 and then the metrics, which one would be paired 00:07:48.019 --> 00:07:50.879 with which? Yeah, great question. This was the 00:07:50.879 --> 00:07:54.339 main basis of this review was to observe the 00:07:54.339 --> 00:07:56.920 literature within the context of of kind of a 00:07:56.920 --> 00:07:59.480 threshold -based approach of classification and 00:07:59.480 --> 00:08:02.519 use that to discuss what potential strength qualities 00:08:02.519 --> 00:08:05.360 exist. So what we did was we looked at, we did 00:08:05.360 --> 00:08:08.120 a literature search and looked for all of the 00:08:08.120 --> 00:08:11.459 studies that compared two or more different metrics 00:08:11.459 --> 00:08:14.120 of strength. So there were lots of studies that, 00:08:14.160 --> 00:08:16.339 for instance, had a kind of move and jump and 00:08:16.339 --> 00:08:18.519 a back squat, and they had a correlation between 00:08:18.519 --> 00:08:20.579 kind of move and jump, jump height and back squat 00:08:20.579 --> 00:08:22.939 load. So that's a good example of what exists 00:08:22.939 --> 00:08:24.759 in the literature. And there are more comprehensive 00:08:24.759 --> 00:08:27.680 ones as well. that looked at more of the relationship. 00:08:27.720 --> 00:08:30.199 So the, you know, using regression models to 00:08:30.199 --> 00:08:32.639 see how changes in counter -movement jump height 00:08:32.639 --> 00:08:36.039 relate to changes in one rep fast squat. All 00:08:36.039 --> 00:08:38.179 of those studies we looked at and tried to summarize 00:08:38.179 --> 00:08:41.220 and we've summarized in tables in this review. 00:08:41.519 --> 00:08:44.600 And what we did was interpreted them in the context 00:08:44.600 --> 00:08:48.000 of more similar or more different. So we used 00:08:48.000 --> 00:08:51.419 a cutoff threshold of 50 % shared variance and 00:08:51.419 --> 00:08:54.259 used that to interpret whether or not metrics 00:08:54.259 --> 00:08:56.429 were very... similar or whether or not metrics 00:08:56.429 --> 00:08:59.289 were more different than similar. And so a 50 00:08:59.289 --> 00:09:02.250 % shared variance cutoff is an R squared of 0 00:09:02.250 --> 00:09:06.450 .5 or an R of 0 .71. So we use those thresholds 00:09:06.450 --> 00:09:08.809 throughout and looked at all of the relationships 00:09:08.809 --> 00:09:11.029 that exist in the literature between metrics. 00:09:11.309 --> 00:09:14.029 Now, in order to effectively compare metrics, 00:09:14.190 --> 00:09:16.110 because there are too many to just go one for 00:09:16.110 --> 00:09:17.809 one throughout the whole body of literature. 00:09:17.970 --> 00:09:20.330 So we kind of made it a two -step approach. And 00:09:20.330 --> 00:09:23.629 what we first did was grouped metrics based off 00:09:23.629 --> 00:09:26.710 of the... task that they were derived from. So 00:09:26.710 --> 00:09:29.570 we use different task constraints to classify 00:09:29.570 --> 00:09:32.269 or categorize the different groups of tests. 00:09:32.370 --> 00:09:35.850 We grouped them based off of the external constraint, 00:09:36.009 --> 00:09:38.409 and that would look like, sorry, an external 00:09:38.409 --> 00:09:41.529 load. And what that would be is either acceleration 00:09:41.529 --> 00:09:43.870 due to gravity on the center of mass. So that 00:09:43.870 --> 00:09:46.570 would be a test such as a drop jump or rebound 00:09:46.570 --> 00:09:49.250 jump, where you're adding that pre -loading of 00:09:49.250 --> 00:09:51.450 acceleration on the center of mass prior to the 00:09:51.450 --> 00:09:53.559 test performed. Could be an external load. load, 00:09:53.840 --> 00:09:56.019 such as a barbell. And then there were time constraints. 00:09:56.139 --> 00:10:00.000 So a task that required a task to be performed 00:10:00.000 --> 00:10:01.779 within a certain period of time. Now, a good 00:10:01.779 --> 00:10:04.279 example of this would be the drop jump, where 00:10:04.279 --> 00:10:07.419 the instructions are given to move as fast and 00:10:07.419 --> 00:10:10.240 as high as possible. So that's a temporal or 00:10:10.240 --> 00:10:12.799 timing constraint. And the test needs to be performed 00:10:12.799 --> 00:10:15.519 ground contact times of less than 250 milliseconds. 00:10:15.960 --> 00:10:18.120 And so that's a constraint that would then group 00:10:18.120 --> 00:10:20.200 a test and how that would differ from something 00:10:20.200 --> 00:10:22.080 like a counter -moving jump, where there are 00:10:22.080 --> 00:10:24.759 no... tiny constraints. And then we also grouped 00:10:24.759 --> 00:10:27.500 them based off of the muscle action. So that's 00:10:27.500 --> 00:10:30.480 dynamic or isometric primarily. And under the 00:10:30.480 --> 00:10:32.980 dynamic category, we had non -ballistic and ballistic 00:10:32.980 --> 00:10:35.620 tasks. A ballistic task would be a jump, whereas 00:10:35.620 --> 00:10:37.860 a non -ballistic would be something like a one 00:10:37.860 --> 00:10:40.679 rep max deadlift or squat. And so in the first 00:10:40.679 --> 00:10:44.000 round of comparisons, we use that threshold approach 00:10:44.000 --> 00:10:46.899 to compare metrics that existed in the same test 00:10:46.899 --> 00:10:48.720 category. So for instance, within the counter 00:10:48.720 --> 00:10:51.539 movement jump, we looked at jump time and the 00:10:51.539 --> 00:10:53.159 core. correlation between jump time and jump 00:10:53.159 --> 00:10:55.000 height and all of those different metrics that 00:10:55.000 --> 00:10:57.159 exist, all from what's available from the literature. 00:10:57.320 --> 00:11:00.240 And from that, we determined whether or not different 00:11:00.240 --> 00:11:03.580 potential classifications or groups of metrics 00:11:03.580 --> 00:11:06.580 tended to emerge from within a test category. 00:11:06.779 --> 00:11:09.639 And then we looked across test categories. So 00:11:09.639 --> 00:11:12.440 we would look at, for instance, within the reactive 00:11:12.440 --> 00:11:14.779 strength test type, we would compare metrics 00:11:14.779 --> 00:11:17.240 from there to an isometric task and see what 00:11:17.240 --> 00:11:20.559 exists in the literature with different relationships. 00:11:20.970 --> 00:11:24.289 between those different task types. And by doing 00:11:24.289 --> 00:11:26.909 so, we were able to fully look at what's available 00:11:26.909 --> 00:11:29.509 in the literature in a somewhat systematic approach 00:11:29.509 --> 00:11:32.769 to be able to understand what types of strength 00:11:32.769 --> 00:11:35.289 qualities based on these metrics exist. So did 00:11:35.289 --> 00:11:37.470 you just go whatever is in the literature with 00:11:37.470 --> 00:11:40.809 the threshold in mind, whatever was tested or 00:11:40.809 --> 00:11:44.169 investigated, that's what you used to make classification? 00:11:44.929 --> 00:11:47.970 Yes, exactly. So there were some tests that had 00:11:47.970 --> 00:11:50.330 a lot of literature on it, such as the... movement 00:11:50.330 --> 00:11:52.809 jump and one or a back squat, for instance, there's 00:11:52.809 --> 00:11:54.629 a decent amount of literature out there for that, 00:11:54.750 --> 00:11:57.009 whereas other ones there were not. And so we 00:11:57.009 --> 00:11:59.529 discussed the potential gaps that existed in 00:11:59.529 --> 00:12:01.330 the literature, which were pretty evident. There 00:12:01.330 --> 00:12:03.649 were some pretty gray areas, particularly with 00:12:03.649 --> 00:12:06.789 the loaded jump and relating that variable to 00:12:06.789 --> 00:12:08.950 any other strength test. Where do you want to 00:12:08.950 --> 00:12:11.830 see the differences and where you are all right 00:12:11.830 --> 00:12:14.450 with having a more global measure, I guess? Yeah, 00:12:14.470 --> 00:12:16.870 exactly. And as part of this research too, there's 00:12:16.870 --> 00:12:20.460 kind of levels of strength. information you can 00:12:20.460 --> 00:12:23.059 say so if we're just looking at dynamic outcomes 00:12:23.059 --> 00:12:25.139 so we're just looking at how high you know how 00:12:25.139 --> 00:12:27.080 much impulse can you create dynamically in an 00:12:27.080 --> 00:12:29.059 unloaded condition then you likely only need 00:12:29.059 --> 00:12:31.379 one test but if you want to dig a little bit 00:12:31.379 --> 00:12:33.960 deeper and understand how that impulse is generated 00:12:33.960 --> 00:12:35.940 or your strategy behind that then you can kind 00:12:35.940 --> 00:12:38.580 of look at another level and at one point in 00:12:38.580 --> 00:12:40.460 those layers depending on your ahu that you're 00:12:40.460 --> 00:12:42.559 interested in then you can dig a little bit deeper 00:12:42.559 --> 00:12:44.639 and include that squat jump in addition to a 00:12:44.639 --> 00:12:46.200 counterweight jump well this is really important 00:12:46.200 --> 00:12:48.899 because what it means for practitioners who working 00:12:48.899 --> 00:12:52.460 with the team is they don't have to go deep enough 00:12:52.460 --> 00:12:55.740 with all the athletes. They may just need the 00:12:55.740 --> 00:12:58.500 deeper measurements for some athletes, not the 00:12:58.500 --> 00:13:02.019 others, which is time -saving and so on. So this 00:13:02.019 --> 00:13:04.440 is really good. Yeah, exactly. And there's a 00:13:04.440 --> 00:13:06.980 tendency to go deep. pretty quick without kind 00:13:06.980 --> 00:13:08.980 of zooming out and looking at the big picture. 00:13:09.159 --> 00:13:11.500 And so there's a lot of, there are a lot of options 00:13:11.500 --> 00:13:13.879 out there to, you know, to go big picture without 00:13:13.879 --> 00:13:16.799 missing out too much. And so that's, that's definitely 00:13:16.799 --> 00:13:19.620 the purpose of this work is, okay, can we get 00:13:19.620 --> 00:13:22.820 90 % of the information by doing 1 % of the tests 00:13:22.820 --> 00:13:25.500 or 1 % of the metrics? And the answer is probably, 00:13:25.639 --> 00:13:28.080 yeah. And sometimes you will want to dig into 00:13:28.080 --> 00:13:31.259 that extra 10%, but that's not always the case. 00:13:31.340 --> 00:13:33.620 And it's frequently not, not, not usually the 00:13:33.620 --> 00:13:35.679 case. So you touched the very important point 00:13:35.679 --> 00:13:38.840 so as the technology makes its way to sports 00:13:38.840 --> 00:13:41.740 science and athlete monitoring we are tempted 00:13:41.740 --> 00:13:44.460 to measure everything because we can but then 00:13:44.460 --> 00:13:47.580 we end up with huge data sets that are very hard 00:13:47.580 --> 00:13:51.320 to process and make sense of and then used to 00:13:51.320 --> 00:13:54.259 meaningfully impact the decision making I guess 00:13:54.259 --> 00:13:58.279 on either selection or training management and 00:13:58.279 --> 00:14:02.539 so on so having structure of metrics what is 00:14:02.539 --> 00:14:06.139 measuring what and to what and how important 00:14:06.139 --> 00:14:09.980 global or how in -depth the measurement is, is 00:14:09.980 --> 00:14:12.980 actually super useful for that reason also. Yeah, 00:14:13.120 --> 00:14:15.440 you nailed it. What did you use and how? Yeah, 00:14:15.480 --> 00:14:18.259 so for this review, we used a threshold approach 00:14:18.259 --> 00:14:21.899 to determine similarity or uniqueness between 00:14:21.899 --> 00:14:25.100 metrics. And for the review, what we did was 00:14:25.100 --> 00:14:27.659 just look at all of the literature that exists 00:14:27.659 --> 00:14:29.960 with comparing different metrics under different 00:14:29.960 --> 00:14:33.120 tests and use the reported either association. 00:14:33.519 --> 00:14:35.360 or a correlation. So that's using a correlation 00:14:35.360 --> 00:14:38.740 analysis and just a single R. We also looked 00:14:38.740 --> 00:14:41.779 at studies that had relationships between metrics. 00:14:41.960 --> 00:14:44.120 So that would be after a regression model, you 00:14:44.120 --> 00:14:46.179 would get an R squared. And then we also looked 00:14:46.179 --> 00:14:49.220 at, and mostly included in the discussion of 00:14:49.220 --> 00:14:52.240 the findings, factor analyses or principal component 00:14:52.240 --> 00:14:56.320 analyses. Now these existed mostly in comparisons 00:14:56.320 --> 00:14:58.519 of the counter -movement jump, but they also 00:14:58.519 --> 00:15:01.580 existed in other spaces as well, where they were 00:15:01.580 --> 00:15:04.570 looking at the component loading of different 00:15:04.570 --> 00:15:06.970 metrics from different tests to determine you 00:15:06.970 --> 00:15:09.409 know how many different types of strength expression 00:15:09.409 --> 00:15:11.309 existed essentially essentially what we're doing 00:15:11.309 --> 00:15:14.409 here and so although those are hard to directly 00:15:14.409 --> 00:15:17.370 compare to correlation analyses or regression 00:15:17.370 --> 00:15:20.450 analyses they provided extra strength essentially 00:15:20.450 --> 00:15:22.970 to our findings with those correlation regression 00:15:22.970 --> 00:15:26.789 analyses and so we use those values to cluster 00:15:26.789 --> 00:15:31.789 anything that was in r squared of 0 .5 or greater 00:15:31.950 --> 00:15:34.590 into the more similar than different category 00:15:34.590 --> 00:15:38.350 and everything that was 0 .49 or less R squared 00:15:38.350 --> 00:15:41.149 in the more different than similar category. 00:15:41.330 --> 00:15:44.710 And that equated to a cutoff of an R of 0 .71. 00:15:44.970 --> 00:15:48.049 So we use those parameters to help discuss the 00:15:48.049 --> 00:15:50.450 findings. There were some that kind of crossed 00:15:50.450 --> 00:15:53.769 that gray area and those were discussed in the 00:15:53.769 --> 00:15:56.889 context of, you know, kind of the crossing zero. 00:15:56.970 --> 00:15:58.789 Some of them are more similar, some of them are 00:15:58.789 --> 00:16:00.750 different, but a lot of them that were pretty 00:16:00.750 --> 00:16:02.779 certain. about kind of really fell into the one 00:16:02.779 --> 00:16:05.279 camp. So we're either a lot similar or a lot 00:16:05.279 --> 00:16:07.379 different growth literature. Awesome. Could we 00:16:07.379 --> 00:16:11.080 go step back and could you simply explain what 00:16:11.080 --> 00:16:13.559 did you use correlation for and what did you 00:16:13.559 --> 00:16:17.120 use regression for? So all we did was look at 00:16:17.120 --> 00:16:20.200 the results from the recent studies and some 00:16:20.200 --> 00:16:23.080 had used correlation analyses and some had used 00:16:23.080 --> 00:16:26.220 regression analyses to compare the relationships 00:16:26.220 --> 00:16:29.379 between different metrics of strength. And so 00:16:29.379 --> 00:16:31.799 for the purpose of the study, we kind of took 00:16:31.799 --> 00:16:34.539 them as a very similar result. So if there was 00:16:34.539 --> 00:16:38.120 a correlation of, let's say, 0 .88, we would 00:16:38.120 --> 00:16:40.059 know that that would be in the more similar than 00:16:40.059 --> 00:16:43.360 different category. So metrics such as jump height 00:16:43.360 --> 00:16:45.799 and takeoff velocity of a countermovement jump, 00:16:45.820 --> 00:16:47.519 because they're derived pretty much from the 00:16:47.519 --> 00:16:50.440 same variable, they were like a 0 .99 correlation. 00:16:50.899 --> 00:16:53.159 And so there were some of the metrics that really 00:16:53.159 --> 00:16:56.480 existed far in that end. And then with the regression 00:16:56.480 --> 00:16:59.519 analyses, the same process was gone through. 00:16:59.600 --> 00:17:02.659 but they would be interpreted as an R squared. 00:17:02.860 --> 00:17:05.099 So a 0 .5 would be more similar than different, 00:17:05.220 --> 00:17:08.779 whereas a 0 .49 would be more different than 00:17:08.779 --> 00:17:11.920 similar. So all we did with that was just interpret 00:17:11.920 --> 00:17:15.700 the findings in that context or in that systematic 00:17:15.700 --> 00:17:18.220 approach. So whatever the authors of the original 00:17:18.220 --> 00:17:21.240 study used, you would take that and interpret 00:17:21.240 --> 00:17:24.039 it according to your cutoff points. Yes, yes, 00:17:24.059 --> 00:17:26.180 exactly. Which was a bit difficult sometimes 00:17:26.180 --> 00:17:28.579 because, well, a lot of the time, because... 00:17:28.809 --> 00:17:30.630 If we're just looking at a single measure, we 00:17:30.630 --> 00:17:33.230 don't, we all know as S &C coaches that the way 00:17:33.230 --> 00:17:36.470 a test is performed can greatly affect the metric. 00:17:36.789 --> 00:17:38.950 And so we're just looking at that single outcome 00:17:38.950 --> 00:17:41.049 metric, the correlation between two measures. 00:17:41.109 --> 00:17:43.190 You know, there's a lot of assumption behind 00:17:43.190 --> 00:17:45.690 that, but that was part of the review process. 00:17:46.029 --> 00:17:49.710 And I think we did an okay job to under, to explain 00:17:49.710 --> 00:17:52.250 the limitation of this approach, but it just 00:17:52.250 --> 00:17:54.230 helped guide discussion. And like I said, there 00:17:54.230 --> 00:17:56.809 were some that were very end ranges and we could 00:17:56.809 --> 00:17:58.650 be pretty certain about those. those things the 00:17:58.650 --> 00:18:00.970 stuff we just said hey we don't know and we need 00:18:00.970 --> 00:18:03.569 to improve our research to to be able to find 00:18:03.569 --> 00:18:05.809 out how to sift through that very not a tricky 00:18:05.809 --> 00:18:08.809 question maybe too detailed question but i had 00:18:08.809 --> 00:18:11.730 a person here on the evidence sanctuary talking 00:18:11.730 --> 00:18:15.769 about how the cues for a drop jump will influence 00:18:15.769 --> 00:18:18.289 the outcome so whether the athlete is instructed 00:18:18.289 --> 00:18:21.450 to jump as high as possible or to rebound as 00:18:21.450 --> 00:18:24.670 fast as possible will influence what metrics 00:18:24.670 --> 00:18:28.660 will be elevated versus the So was it enough 00:18:28.660 --> 00:18:32.779 studies to go into that level? So did you separate 00:18:32.779 --> 00:18:35.900 what the cue was used and then what the correlations 00:18:35.900 --> 00:18:38.099 were between the metrics? I'm really happy you 00:18:38.099 --> 00:18:39.660 asked that because that actually was one of the 00:18:39.660 --> 00:18:42.079 main discussion points at the end of our paper. 00:18:42.220 --> 00:18:44.859 And we didn't necessarily, because the cues were 00:18:44.859 --> 00:18:47.900 kind of not always reported, we didn't necessarily 00:18:47.900 --> 00:18:51.420 go to the cues, but we did compare the contact 00:18:51.420 --> 00:18:53.759 times. So when it was reported, we could see 00:18:53.759 --> 00:18:56.259 that the metrics from the drop jump that were 00:18:56.460 --> 00:19:00.150 derived from a test that had less than... 250 00:19:00.150 --> 00:19:03.490 milliseconds of contact time were unique from 00:19:03.490 --> 00:19:05.130 a countermovement jump. So if we're talking about 00:19:05.130 --> 00:19:06.789 jump height and jump height, they were unique 00:19:06.789 --> 00:19:10.509 if the constraints of the drop jump were, like 00:19:10.509 --> 00:19:13.450 you said, jump high and jump fast and they had 00:19:13.450 --> 00:19:15.690 a contact time of less than 250 milliseconds. 00:19:16.150 --> 00:19:19.589 But if in some cases where the contact times 00:19:19.589 --> 00:19:23.049 were elongated past the 250 milliseconds, then 00:19:23.049 --> 00:19:25.269 the relationship between countermovement jump 00:19:25.269 --> 00:19:27.950 and drop jump metrics were much closer. And so 00:19:27.950 --> 00:19:29.329 they would actually be grouped into the same 00:19:29.329 --> 00:19:31.529 category. So this was a really important finding 00:19:31.529 --> 00:19:34.490 that, you know, the task constraints greatly 00:19:34.490 --> 00:19:37.750 influence the discovery of these strength domains 00:19:37.750 --> 00:19:40.410 or strength qualities. And so we have to be very 00:19:40.410 --> 00:19:43.509 specific when we are conducting these tests so 00:19:43.509 --> 00:19:45.210 that we understand how the test is performed, 00:19:45.470 --> 00:19:47.450 what the outcome of the test is trying to be, 00:19:47.490 --> 00:19:49.250 what we're trying to gather from that test. And 00:19:49.250 --> 00:19:52.109 if for some reason a person can't do a drop jump 00:19:52.109 --> 00:19:54.549 with a contact time of 250 milliseconds, then 00:19:54.549 --> 00:19:56.230 it likely isn't the right test for them. They're 00:19:56.230 --> 00:19:57.809 not measuring it. reactive strength quality. 00:19:57.990 --> 00:19:59.890 So we have to consider all of those factors when 00:19:59.890 --> 00:20:03.130 we are implementing this testing. I like finding 00:20:03.130 --> 00:20:05.630 things out. I thought that it may be a little 00:20:05.630 --> 00:20:08.150 bit too detailed question, but actually looked 00:20:08.150 --> 00:20:10.990 into it. So are we ready for the results? Yeah, 00:20:11.029 --> 00:20:13.190 sounds good. Awesome. So what are the results? 00:20:13.509 --> 00:20:16.150 Okay, so at the end of this whole systematic 00:20:16.150 --> 00:20:18.950 approach, we found that there were five different 00:20:18.950 --> 00:20:20.849 domains of strength. So we termed them domains 00:20:20.849 --> 00:20:23.210 of strength, and those were reactive, unloaded 00:20:23.210 --> 00:20:26.390 dynamic, loaded dynamic, maximal isometric. and 00:20:26.390 --> 00:20:29.170 early isometric. Yes. So these group of strength 00:20:29.170 --> 00:20:32.250 metrics were discovered by first comparing within 00:20:32.250 --> 00:20:34.390 the task category and then again across task 00:20:34.390 --> 00:20:36.750 categories, as we mentioned. But there were some 00:20:36.750 --> 00:20:39.430 considerations. So like I mentioned previously, 00:20:39.769 --> 00:20:42.069 the reactive strength category is highly dependent 00:20:42.069 --> 00:20:45.069 on how the test is performed. So as we mentioned, 00:20:45.130 --> 00:20:48.390 if you get a contact time greater than 250 milliseconds, 00:20:48.710 --> 00:20:50.809 then it actually, the metrics derived from that 00:20:50.809 --> 00:20:54.230 test actually group in the unloaded dynamic category. 00:20:54.490 --> 00:20:56.539 And so in order for... For it to be a distinct 00:20:56.539 --> 00:20:59.140 domain of strength, the task has to be performed 00:20:59.140 --> 00:21:02.039 a certain way. And so that was a main kind of 00:21:02.039 --> 00:21:04.220 outcome of our study. Another notable finding 00:21:04.220 --> 00:21:07.319 was within the unloaded dynamic strength category. 00:21:07.440 --> 00:21:10.099 As there's a decent amount of literature to suggest 00:21:10.099 --> 00:21:12.440 that there are actually different strength qualities 00:21:12.440 --> 00:21:15.720 that can be discovered within the unloaded dynamic 00:21:15.720 --> 00:21:18.420 strength category. So for instance, the timing 00:21:18.420 --> 00:21:20.240 of the test. So we're talking about a counter 00:21:20.240 --> 00:21:22.220 -movement jump here. The timing of the counter 00:21:22.220 --> 00:21:24.759 -movement, the forks input of the... counter 00:21:24.759 --> 00:21:27.759 movement. So we're talking about like mean concentric 00:21:27.759 --> 00:21:30.319 or mean propulsive force, the outcome. So we're 00:21:30.319 --> 00:21:31.880 talking about jump height there. And then there 00:21:31.880 --> 00:21:34.400 are also some other movement strategy characteristics, 00:21:34.619 --> 00:21:37.119 such as the speed of the depth of the counter 00:21:37.119 --> 00:21:40.039 movement. So those all kind of emerged in this 00:21:40.039 --> 00:21:42.640 study and some other studies as likely unique 00:21:42.640 --> 00:21:45.640 characteristics. But when those metrics were 00:21:45.640 --> 00:21:48.980 compared across task categories, it got a little 00:21:48.980 --> 00:21:51.579 gray. So we couldn't necessarily find distinctions 00:21:51.579 --> 00:21:53.700 when measuring outside of the task category. 00:21:53.839 --> 00:21:57.200 So because of that, we decided to collapse the 00:21:57.200 --> 00:21:59.599 unloaded dynamic strength to a single quality. 00:21:59.779 --> 00:22:02.460 But there's a lot of more work that can be done 00:22:02.460 --> 00:22:04.539 in that area. And then another important finding, 00:22:04.700 --> 00:22:07.000 sorry, the loaded ballistic tasks. So we're talking 00:22:07.000 --> 00:22:08.819 about a loaded countermovement jump or squat 00:22:08.819 --> 00:22:12.339 jump. There is very few studies out there that 00:22:12.339 --> 00:22:14.539 actually looked at a correlation between a non 00:22:14.539 --> 00:22:17.140 -ballistic task such as a one rep max back squat 00:22:17.140 --> 00:22:20.059 or an unloaded countermovement or any other. 00:22:20.650 --> 00:22:22.509 comparisons, really. There were very few studies 00:22:22.509 --> 00:22:24.730 that looked at the comparison between a ballistic, 00:22:24.950 --> 00:22:27.490 a loaded ballistic task and an isometric or reactive 00:22:27.490 --> 00:22:29.890 strength tasks. So those studies don't necessarily 00:22:29.890 --> 00:22:33.029 exist when we're looking at it that way. And 00:22:33.029 --> 00:22:35.589 so because of that, we weren't really able to 00:22:35.589 --> 00:22:38.730 determine its distinction. So where a loaded 00:22:38.730 --> 00:22:41.789 jump may be more similar or different than an 00:22:41.789 --> 00:22:44.390 unloaded jump or a one rep MACBAT squat. So then 00:22:44.390 --> 00:22:46.130 we know there's a spectrum here. We don't know 00:22:46.130 --> 00:22:49.430 where the difference starts to occur. And so 00:22:49.430 --> 00:22:52.509 there's more research to be done on where that 00:22:52.509 --> 00:22:55.430 loaded ballistic task becomes more different 00:22:55.430 --> 00:22:57.809 than an unloaded ballistic task and vice versa 00:22:57.809 --> 00:22:59.750 working the other way around. So that was a big 00:22:59.750 --> 00:23:02.150 gap identified in this study. And then lastly, 00:23:02.269 --> 00:23:04.490 another important finding was the distinction 00:23:04.490 --> 00:23:07.289 between early and maximal isometric strength. 00:23:07.509 --> 00:23:10.109 So this is something that has been theoretically 00:23:10.109 --> 00:23:12.690 discovered in individual studies suggesting that 00:23:12.690 --> 00:23:15.910 early isometric strength produced, so force produced 00:23:15.910 --> 00:23:17.970 kind of within the first 100 milliseconds or 00:23:17.970 --> 00:23:20.549 so, may be... distinct from your maximal force 00:23:20.549 --> 00:23:23.329 capability. And we found in the study that it 00:23:23.329 --> 00:23:26.289 does, in fact, consistently demonstrate a distinction. 00:23:26.630 --> 00:23:28.670 So yes, there's a distinction identified between 00:23:28.670 --> 00:23:31.869 early and maximal isometric strength, where the 00:23:31.869 --> 00:23:35.569 early isometric strength metric was likely around 00:23:35.569 --> 00:23:39.569 100 milliseconds. So force produced at 100 milliseconds 00:23:39.569 --> 00:23:42.809 is usually the cutoff. So anything past that, 00:23:42.910 --> 00:23:45.390 so past 150 milliseconds. So if you're measuring 00:23:45.390 --> 00:23:47.930 force in an isometric task for around 200 or 00:23:47.930 --> 00:23:51.680 200... 50 milliseconds. It is more similar to 00:23:51.680 --> 00:23:54.609 maximal. isometric strength than it is to the 00:23:54.609 --> 00:23:57.529 early. So when we are looking at isometric tasks 00:23:57.529 --> 00:24:00.390 and want to look at a distinction, it's recommended 00:24:00.390 --> 00:24:02.809 that about 100 or 150 milliseconds is where you 00:24:02.809 --> 00:24:05.710 measure that strength expression. And anything 00:24:05.710 --> 00:24:08.970 later, it's very, very similar to maximal. But 00:24:08.970 --> 00:24:12.069 this is only possible if the task is done with 00:24:12.069 --> 00:24:14.529 a rapid intent. And what I mean by rapid intent 00:24:14.529 --> 00:24:17.849 is that it's been instructed to push or pull 00:24:17.849 --> 00:24:21.130 as fast and as hard as possible. So those two 00:24:21.130 --> 00:24:23.970 characteristics critical if we do want to measure 00:24:23.970 --> 00:24:27.109 rapid strength or this early isometric strength. 00:24:27.230 --> 00:24:29.589 And that's really important. So it's another 00:24:29.589 --> 00:24:32.730 example of ensuring that the task constraints 00:24:32.730 --> 00:24:36.569 are upheld or else the whole representation of 00:24:36.569 --> 00:24:40.259 a strength domain. won't exist. And so, you know, 00:24:40.299 --> 00:24:42.519 with some of the force plate technology, you 00:24:42.519 --> 00:24:45.140 can make a flag or a tag that says if it's done 00:24:45.140 --> 00:24:47.480 rapidly or not. And I'd recommend doing that 00:24:47.480 --> 00:24:50.140 because it does influence the interpretation 00:24:50.140 --> 00:24:52.960 of that metric. Okay. So now let's go back to 00:24:52.960 --> 00:24:55.940 practitioners. How would they go about choosing, 00:24:55.980 --> 00:24:58.859 I guess? Yeah. So the first step is determining 00:24:58.859 --> 00:25:01.740 what your athlete is used to performing. So before 00:25:01.740 --> 00:25:05.099 we even go down the road of what exists, it's 00:25:05.099 --> 00:25:07.579 what can the athlete perform? athlete has never 00:25:07.579 --> 00:25:10.099 done an isometric test before, brain them up, 00:25:10.119 --> 00:25:11.599 show them how to do it, make sure they're used 00:25:11.599 --> 00:25:14.359 to do it, or else you won't get a maximal expression 00:25:14.359 --> 00:25:16.500 of force. So that would be my number one advice 00:25:16.500 --> 00:25:19.160 is make sure that the tests that you are doing 00:25:19.160 --> 00:25:22.420 allow us for the athlete to express force maximally. 00:25:22.460 --> 00:25:24.819 Second, figure out what, you know, out of the 00:25:24.819 --> 00:25:28.000 range of tests, which ones matter the most for 00:25:28.000 --> 00:25:30.400 your athlete group. So if you're looking at novice 00:25:30.400 --> 00:25:33.000 athletes who, you know, everyone just needs to 00:25:33.000 --> 00:25:35.619 get stronger and get exposure to strength conditioning, 00:25:35.900 --> 00:25:37.640 I would I wouldn't worry too much about getting 00:25:37.640 --> 00:25:40.720 the wide spectrum of strength, but I would measure 00:25:40.720 --> 00:25:42.680 countermovement jump and I would get jump height. 00:25:42.759 --> 00:25:45.299 I would get kind of the big rocks measured early. 00:25:45.480 --> 00:25:48.259 And then when you are working with an athlete 00:25:48.259 --> 00:25:51.259 group that is well -trained and you are looking 00:25:51.259 --> 00:25:54.019 at kind of a wide range of strength expressions, 00:25:54.180 --> 00:25:57.000 the tests I would recommend are a drop jump or 00:25:57.000 --> 00:25:59.420 a rebound jump. So one of those two to get a 00:25:59.420 --> 00:26:01.619 reactive strength quality, a countermovement 00:26:01.619 --> 00:26:03.880 jump. And from there, you can get the big, you 00:26:03.880 --> 00:26:06.750 know, the big strength. domain of just unloaded 00:26:06.750 --> 00:26:08.789 dynamic but then you can also get all of those 00:26:08.789 --> 00:26:11.630 other kind of second layer metrics as well i 00:26:11.630 --> 00:26:15.710 would then do either a one rep max or a loaded 00:26:15.710 --> 00:26:18.910 jump squat now these can be these are sometimes 00:26:18.910 --> 00:26:22.150 avoided by strength strength trainers or or snc 00:26:22.150 --> 00:26:24.630 coaches or you know the coaches just say no or 00:26:24.630 --> 00:26:27.309 the athletes are like nah no way and so if that's 00:26:27.309 --> 00:26:30.289 the case and what i currently do is find ways 00:26:30.289 --> 00:26:33.529 to do heavy non -ballistic movements and measure 00:26:33.529 --> 00:26:36.470 the velocity of the bar So I gain information 00:26:36.470 --> 00:26:39.589 on that quality by doing assessments of their 00:26:39.589 --> 00:26:41.690 strength training practices rather than doing 00:26:41.690 --> 00:26:44.450 a distinct test. And I find that that works really 00:26:44.450 --> 00:26:47.109 well. But measuring that heavy expression of 00:26:47.109 --> 00:26:49.950 dynamic strength is a unique quality. And so 00:26:49.950 --> 00:26:52.730 we need to measure it somehow if you do want 00:26:52.730 --> 00:26:56.069 to fill out that spectrum. On that, do you cue 00:26:56.069 --> 00:26:59.589 athletes to, I don't know, they do heavy squats 00:26:59.589 --> 00:27:02.450 in a set of five reps. Do you cue them to do 00:27:02.450 --> 00:27:04.519 them as quickly as they can? That's a really 00:27:04.519 --> 00:27:07.240 good question. I program to have kind of heavy 00:27:07.240 --> 00:27:10.400 3Ds. And so they would be moving them fast. It 00:27:10.400 --> 00:27:13.039 would be in a maximal intent day. So it's like, 00:27:13.079 --> 00:27:14.680 hey, these are important. We're trying to get 00:27:14.680 --> 00:27:16.960 a max velocity on these. And they wouldn't necessarily, 00:27:17.180 --> 00:27:18.960 like they wouldn't jump, but they would move 00:27:18.960 --> 00:27:21.140 the bar with high intent, I tend to call it. 00:27:21.200 --> 00:27:23.579 And they, you know, the athletes, when they do 00:27:23.579 --> 00:27:26.420 have the accelerometer or the linear position 00:27:26.420 --> 00:27:29.839 transducer on the bar, they tend to push for 00:27:29.839 --> 00:27:32.039 that higher velocity. And so it works well in 00:27:32.039 --> 00:27:34.180 my context. I know that's not always the case, 00:27:34.319 --> 00:27:36.220 but just that's a really good point. If you are 00:27:36.220 --> 00:27:39.180 using that option, that it needs to be a maximal 00:27:39.180 --> 00:27:41.019 intent or else you're not going to measure the 00:27:41.019 --> 00:27:42.799 quality that you want. And so if you can't get 00:27:42.799 --> 00:27:44.839 that in training and you need to do a specific 00:27:44.839 --> 00:27:47.359 testing, then know that that is your option, 00:27:47.440 --> 00:27:49.059 that you should do the specific testing. And 00:27:49.059 --> 00:27:51.920 then in addition to the dynamic test, doing isometric 00:27:51.920 --> 00:27:54.920 test two does seem to measure a unique quality 00:27:54.920 --> 00:27:57.400 of kind of that, you know, that underlying ability 00:27:57.400 --> 00:27:59.799 to produce force irrespective of a movement strategy. 00:28:00.099 --> 00:28:02.619 And so getting a maximal isometric. strength, 00:28:03.000 --> 00:28:06.880 and then also a rapid or a strength test, or 00:28:06.880 --> 00:28:08.660 sorry, a strength metric at 100 milliseconds 00:28:08.660 --> 00:28:11.079 is also what I recommend. Now, if you're trying 00:28:11.079 --> 00:28:14.359 to avoid the rapid movement in, well, it's not 00:28:14.359 --> 00:28:16.279 movement, but the rapid intent in an isometric 00:28:16.279 --> 00:28:18.400 task, as some practitioners are, I would say 00:28:18.400 --> 00:28:20.940 do a slow gradual and just know that you're likely 00:28:20.940 --> 00:28:23.839 missing that extra bit of information that maybe 00:28:23.839 --> 00:28:26.339 you want to incorporate later on because it does 00:28:26.339 --> 00:28:28.519 tell you something unique. But overall, those 00:28:28.519 --> 00:28:30.640 are the tests I recommend and you can get most 00:28:30.640 --> 00:28:33.289 information. from those four tests. Awesome. 00:28:33.490 --> 00:28:36.450 I have a tricky question now. So are you familiar 00:28:36.450 --> 00:28:38.650 with Olympic weightlifting? Yeah, that's a sport. 00:28:38.849 --> 00:28:42.369 So if you would assist a skill coach, a weightlifting 00:28:42.369 --> 00:28:45.869 coach, and you would propose a battery of tests 00:28:45.869 --> 00:28:48.650 for a weightlifter, what would be your approach? 00:28:48.890 --> 00:28:51.089 Good question. I would first, if I were to do 00:28:51.089 --> 00:28:53.509 this the really complicated way, I would first 00:28:53.509 --> 00:28:57.150 measure a series of tests using a force platform 00:28:57.150 --> 00:28:59.990 and then do some data reduction myself to understand 00:28:59.990 --> 00:29:01.490 which ones are different. which ones are similar. 00:29:01.630 --> 00:29:04.069 Now with weightlifting, with Olympic weightlifting, 00:29:04.210 --> 00:29:06.190 because these movements, particularly like a 00:29:06.190 --> 00:29:08.710 mid -thigh pull, is so specific to their sport, 00:29:08.849 --> 00:29:10.730 it was essentially designed for the sport, you 00:29:10.730 --> 00:29:13.930 might actually see very unique emerging elements 00:29:13.930 --> 00:29:16.269 of strength domains than if you were to measure 00:29:16.269 --> 00:29:18.950 a field sport athlete, for instance. So what 00:29:18.950 --> 00:29:21.369 I would do is I would do an unloaded catamaran 00:29:21.369 --> 00:29:23.450 jump. I likely wouldn't do a reactive strength 00:29:23.450 --> 00:29:26.190 test due to the nature of their sport. So because 00:29:26.190 --> 00:29:29.910 they don't necessarily have any cutting or a... 00:29:29.960 --> 00:29:33.099 preload, I wouldn't kind of tap into that. that 00:29:33.099 --> 00:29:35.619 realm as it's not specifically evident to be 00:29:35.619 --> 00:29:37.539 important for their task. And I think there might 00:29:37.539 --> 00:29:41.019 be subtle differences in the concentric only 00:29:41.019 --> 00:29:44.319 aspect of weightlifting that might emerge rather 00:29:44.319 --> 00:29:46.700 than a reactive strength test. Yeah, I would 00:29:46.700 --> 00:29:49.559 do a counter movement jump and an isometric mid 00:29:49.559 --> 00:29:52.140 -bike pull. And then since like that sport is 00:29:52.140 --> 00:29:55.720 so dependent on just obviously it's about how 00:29:55.720 --> 00:29:58.660 much you lift, you kind of always have a really, 00:29:58.660 --> 00:30:01.279 really close and really clean understanding of 00:30:01.279 --> 00:30:03.640 what they can move. dynamically. And so the two 00:30:03.640 --> 00:30:05.900 ends of the spectrum might be where you'd want 00:30:05.900 --> 00:30:07.940 to measure because you're not necessarily training 00:30:07.940 --> 00:30:09.640 those two ends of the spectrum. And so gaining 00:30:09.640 --> 00:30:12.940 some insight on what they absolutely can produce 00:30:12.940 --> 00:30:15.940 and what they can do under the lightest load 00:30:15.940 --> 00:30:17.920 might give you some insight of what they need 00:30:17.920 --> 00:30:20.960 to improve in order to get that loaded dynamic 00:30:20.960 --> 00:30:24.160 task better. All right. Awesome. Would you have, 00:30:24.299 --> 00:30:27.000 if you would have to give advice for the coaches, 00:30:27.240 --> 00:30:30.500 SNC coaches or other coaches that may use this 00:30:30.500 --> 00:30:32.759 study, how... they should go about it? Would 00:30:32.759 --> 00:30:35.779 I take home messages? Yeah. The biggest one is 00:30:35.779 --> 00:30:39.019 be critical. Think about what you are measuring 00:30:39.019 --> 00:30:41.700 and why you're measuring it. And does the metric 00:30:41.700 --> 00:30:43.799 actually represent what you think it does? And 00:30:43.799 --> 00:30:46.579 so even if you don't use the domains that I've 00:30:46.579 --> 00:30:49.220 presented in this study, I would love it for 00:30:49.220 --> 00:30:52.180 you to go out and be very critical and understand 00:30:52.180 --> 00:30:54.759 the reasoning behind the selection of the test 00:30:54.759 --> 00:30:57.019 and the selection of the metric. The more that 00:30:57.019 --> 00:30:59.859 we can understand, even just the math behind 00:30:59.859 --> 00:31:02.609 it, the more... that we can be intentional with 00:31:02.609 --> 00:31:04.890 selecting different tests. Now, if you are wanting 00:31:04.890 --> 00:31:07.230 to use the results of this study, and this is 00:31:07.230 --> 00:31:09.509 particularly helpful for like a field sport athlete 00:31:09.509 --> 00:31:12.369 type of cohort, I'd recommend starting with those 00:31:12.369 --> 00:31:14.789 big rocks that I recommend in those five domains, 00:31:14.950 --> 00:31:17.529 and then moving on to the second layer, which 00:31:17.529 --> 00:31:20.329 may be presented in my subsequent studies and 00:31:20.329 --> 00:31:23.170 other authors' subsequent studies that look into 00:31:23.170 --> 00:31:25.769 the details of each test. But start with the 00:31:25.769 --> 00:31:27.809 big rocks, do them well, do them consistently, 00:31:28.049 --> 00:31:30.230 have a grasp of the understanding. of what you're 00:31:30.230 --> 00:31:32.430 measuring and then go from there. Do a few things 00:31:32.430 --> 00:31:34.410 and do them well. Do them consistently. Know 00:31:34.410 --> 00:31:36.430 what they are. Those will go a longer way. It's 00:31:36.430 --> 00:31:39.589 easier to do, too, because you can focus on just 00:31:39.589 --> 00:31:42.349 these things and have the data. Athletes can 00:31:42.349 --> 00:31:45.029 do them really well. The data is clearer. The 00:31:45.029 --> 00:31:49.150 variance is smaller. The data is better quality. 00:31:49.329 --> 00:31:51.990 Therefore, your reasoning will be closer to what 00:31:51.990 --> 00:31:54.569 is, hopefully, closer to what is going on. Yeah, 00:31:54.670 --> 00:31:58.829 exactly. You just limit as many of those potential... 00:31:59.079 --> 00:32:02.160 human errors as possible and and then you you 00:32:02.160 --> 00:32:04.700 get to the real thing right okay so two questions 00:32:04.700 --> 00:32:07.700 to finish the first one would be what is your 00:32:07.700 --> 00:32:11.039 favorite exercise yeah so i grew up playing like 00:32:11.039 --> 00:32:14.660 varsity ice hockey and so uh we loved our bulgarian 00:32:14.660 --> 00:32:17.299 split squats and so as much as that's everyone's 00:32:17.299 --> 00:32:19.680 least favorite exercise that's still my favorite 00:32:19.680 --> 00:32:23.740 i can still bulgarian you know 70 kilos all right 00:32:23.740 --> 00:32:26.000 then the last question is where people can find 00:32:26.000 --> 00:32:28.240 you online if they want to follow your work and 00:32:28.299 --> 00:32:30.640 be up to date or maybe even ask a question. Where 00:32:30.640 --> 00:32:33.839 should they go? Yeah, great. My research is always 00:32:33.839 --> 00:32:37.259 updated on ResearchGate and you can find me, 00:32:37.359 --> 00:32:41.519 I think it's MCGino. And then also on Twitter 00:32:41.519 --> 00:32:44.519 and Instagram, MCGino. Those are most of the 00:32:44.519 --> 00:32:46.839 platforms that I'll be on. And everything, because 00:32:46.839 --> 00:32:51.220 I'm the only MCGino around, is just at MCGino 00:32:51.220 --> 00:32:53.039 and you'll find me in all those places. Awesome. 00:32:53.099 --> 00:32:55.119 Thank you so much, Mary. It was a pleasure. Yeah, 00:32:55.160 --> 00:32:55.539 thank you.