Slowly but surely we tend to believe that we need all kind of cool tools, expensive equipment or sophisticated toys in order to get and to process data of our athletes or teams; data that might be helpful in programming their planning and training.
I will try to show that you can get extremely helpful data without any tools, simply because it’s data we already have, but seldom look at in this way.
1 Analyze the simple data of the season, such as:
– number of competitions
– number of starts
– number of travelling days
– number of workouts
– number of strength workouts
– number of speed and speed-related workouts
– number of endurance workouts
– number of resting days (no travel, training or competition)
– number of recovery workouts
This information will give you direction, a sense of proportion and it also shows you if and how far you deviated from you original planning and intentions.
I have done this and published it in 1989 (and somebody translated this into English, see the link below)
So you see that with having these relatively simple data you can get a lot of information that will help you to adjust the training process.
2 When does the athlete peak?
In many sports we have a competition period during which the athlete will try to reach his/her full potential by performing at his/her best at the right time. This isn’t always possible e.g. due to environmental circumstances such as temperature, wind, etc. Anyhow once the season is over and we have the results of competition we can analyze these data and it becomes even more clear after a few years doing this.
When does the athlete perform at his/her best? Within the first 5 competitions of the season and all downhill from there or is does the athlete have a slow start of the season and peaks at the end of it after let’s say 20 competitions? (see the graph below.)
Most of the time there is pattern. There are athletes who peak early, those who peak in the middle and others who peak at the end of the season.
Since we know the time of the major competition or championships (red arrow) we can easily see if our athletes peaked too early or too late, in this particular case, one athlete (green line) peaked to early, while the other (blue line) peaked too late.
So this is something to take into account as far as planning is concerned. If you perform your seasons’ best always in one of the first 5 competitions, but your main peak, let say World Championship or Olympic Games, is the 18th planned competition of the season, you might be in trouble. And sometimes the opposite is true, some athletes have a hard time qualifying by performing qualification times in the beginning in the season. Almost at the edge of not qualifying at all. While at the major competitions (at least if they qualify for it) they always break the year’s best performance. Another factor is to look at is how long the athletes can maintain their “shape” and as of which number of competitions their performances start to decrease irreversibly.
It depends on the sport you are in. Sometimes you count the competitions, in other sports you have to count the amount of starts (in track and field in the Diamond League you mainly have one start a day – straight finals), but at championships you have to go through multiple rounds, preliminaries, qualifications, heats, etc. Since you have the data you can take a look at the competitions and at the amount of starts as well.
3 Look at the variation of performance within the starts of a championship or a competition.
Look at the performances in the heats, the quarter finals, semi-finals and in the finals. Also here you will find individual patterns. What we find here is the interface between physical and mental factors at work! A lot of athletes do great in the quarter-finals and/or semi-finals and are not getting any better when it really counts …… in the finals.
(see the graph below for 4 different patterns)
Now you are able to figure out the relationship between their performances in the preliminary rounds, the effort of the athlete and their perceived effort. This is where even in individual sports, like track and field, tactics can play a role!
Normal approach in sprints: “saving energy” in the heats, running easy, cruising and running relaxed.
But my approach is to go fast already in the heats for the following reasons:
– sometimes the circumstances, weather, wind are perfect in the heats and assuming the athlete is in good shape: why not run a personal record in the heats. One never knows what happens later on in the competition, it may start raining and you miss an opportunity to run a personal best.
– a good time in the heats may put some pressure on the opponents, especially when it still looks relaxed and easy
– a good time in the heats increases the self-confidence of the athlete. Knowing he or she is in the shape of his/her life or at least of the year.
– less chance to get surprised at the tape while you slow down
– sets you up for a good lane in the next round
The main discussion is: is the athlete not spending unnecessary “energy “ by going full speed in the heats, thereby assuming the athlete will be “fatigued” in the finals when it counts. But then…. here is my question: what is fatigued? What is the real difference in perceived fatigue, let’s say in the women’s 100 meters between running 11.18 or running 10.98?
Here is an example: ever watched a good 400 meter race – who makes the most fatigued impression to you: the guy who wins the gold, but needed to run a personal best or the guy that ran 0.5 seconds slower than his personal best, coming in 6th place? The winner ran faster than number 6 in absolute terms as well as in relative terms, and still he is able to run a victory lap with a smile on his face while number 6 is flat out on the track for 3 minutes, looking really, really tired. A simple lesson here: there is no better recovery that a good performance!
4 Henk’s 1% rule: what is “peaking”.
1% is the margin in which I judge if at peaked the right moment. That is to say: when participating in the peak competitions (often major championships) the result should be within 1% of the previous best result of that year.
Basically it is very simple: an athlete ran the 100 meter in 10.20 sec this year, now the ‘big’ championship is coming up. The athlete does well if he runs 10.20 + or -1%, that is between 10.10 and 10.30. If the athlete runs over 10.30 sec at that championship, he failed, or better….. I failed somewhere down the line (see the graph below for explanation).
I analyzed the Dutch track and field team that competed at the European championships in Zürich this year.
Some observations: a 400 meter runner broke the national record in 45.41 but ran 46.38 at the EC, only three weeks later, more than 2% worse. A female sprinter ran 11.12 this year, but ran 11.54 at the EC, close to 4% worse. A discus thrower threw 65.24 this year, but did not even qualify for the finals with a meager 62.18 meters, more than 4% worse. He clearly did not peak and he has shown this pattern over and over again. The 3 male marathon runners ran 8, 5, and 5 minutes slower than they did before, another one did not even make it to the starting line, whereas two of the female marathon runners broke their personal best. Now you might say: the circumstances where not optimal, but the circumstances are the same for everybody so why do their opponents break their personal bests and break the national records in that competition?
The above told me that despite the excellent performances of a handful of athlete, the majority of the rest of the team should not have been there. Not because they did not win a medal, but simply because they stayed far below their performances of this year, e.g. at the national championships a few weeks earlier. This tells us something about the ability of the coach to bring his athletes into good shape and allow them to peak at the right time when it counts and that is the major championship.
The 1% is the variation for the track, the temperature, the wind etc. For more complex events with more variables I shift to the 1.5% rule. Like in the shot put: if somebody threw 20.00 meters that year, 1.5 times 20 cm is 30 cm, so 19.70 is still OK.
This is rather easy for the field events, the sprints and the hurdles where tactics don’t play a role and we assume a 100% effort to win. But in the middle- and longer distance one is able to win a gold medal with a time considerably slower than the year’s best performance of even in the heats or semi-finals just because everybody is waiting and looking at each other in the first part of the race and they wait until the final lap to kick, resulting in a slow time overall.
So in general you don’t have to rely on machines of software to see the strengths or weakness in your athletes or your teams. I fully realize that this is different for different sports, it’s just to show you some general ideas.