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Fittest? Or most active possibly? Just because they covered more ground during the match does not mean they were fitter than everyone else.
Also, from posts from Charlie on the first few pages of this, avg distnace of spain of 10.9 km/match (~6 miles). = avg speed of 7.26 km/hr (4.5 mph). Blazing fast 
Uruguay actually ran in total 336.72km without the ball (almost a massive 100km more than Spain), jeez. But Spain ousted them in Total distance covered (767.39km).
Keen to note that the teams that underperformed so badly at the World Cup, Italy, France, Nigeria topped the table for Distance covered not in possession (km) of the ball. POOR WORKRATE off the ball.
Seems to me the teams working on speed as opposed to stamina (workrate) are going the wrong way (according to the stats) for success at the World cup, although Spain were 5th (Top speed) with Mexico & Greece top 2.
Which proves one massive point. You don’t have to be blazing fast to be successful in soccer.
Agreed
Be careful drawing conclusions from physical data
Again, be careful assessing that data.
Most of the teams that went out early obviously only played poor teams, in poor matches.
Secondly does poor stats show poor fitness or poor skill levels?
Do you need to work harder against poorer teams?
How do you know that the team who ran less with (or without) the ball had poorer fitness.
I.e. The biggest question not answered there is % possession.
There are many, many ways to interpret the data.
Guys,
I see a lot of confusion, a lot. Players are with the national team for approximately 3 weeks before the start of the work cup, it is a long time full of opportunities if you want to destroy someone, not a lot of time if you want to improve. Do you really think that fastest players were fastest because of the 3 weeks spent with the national team?
Players are selected and not trained, in a general sense (of course when they are playing with the national team, less so with their clubs).
Soccer is a complex sport like many others, in which the result is determined by a multitude of factors and not easily identifiable. You look a the data, fitness, average velocity, ball possession and so on, at the end maybe the only goal was scored in a corner.
In track and field, let’s say 100 m dash, it is easier to look at quantitative data and have insights (reaction time, start and drive, max V etc.).
For example, ball possession is not a good indicator of winning probabilty, especially in the last decade, maybe two. If any of you have seen the statistics of the semi-final of Champions’ League, Barcellona-Inter, ball possession was around 70% for Barcellona, but you remember who won, don’t you?
There was a paper published a few years ago, where it was shown that lesser teams against better teams ran substantially more. You can thus conclude that lesser teams were more fitted, can’t you?
Wrong conclusion. They were chasing all the time.
Italy, England & France were ranked 5th, 8th & 9th respectively in the World rankings.
Uruguay, Paraguay, Ghana were ranked 16th, 31st & 32nd.
Your definition of a poor team?. Italy, England & France all ranked in top 10 & eliminated early? or Uruguay, Paraguay & Ghana who went further into the tournament?.
Evidently it shows poor performances through early elimination. The team with the highest distance covered, best passing completion rate, suprise, suprise won the tournament. Team with the best stats won. Teams in general with poor stats dropped out early. Good indication.
Such as Uruguay, Paraguay & Ghana? Yes! If you want to reach the latter stages of the tournament.
Because there yardage outputs & work rates during games fell short of the teams who reached the latter stages.
Not that I have much to add but it seems that looking at average speed doesn’t really say much.
I mean an average could represent so many different distributions (including both the fastests fasts and slowest slows and everything in-between) that I don’t know if it ‘proves’ that high speed work is somehow unnecessary.
Certainly most of the time seems to be spent moving slowly (and a certain work capacity is required for that) and the durations moving slowly would tend to skew the average way down but that doesn’t mean that the high speed bits are either irrelevant or unimportant to overall performance.
Lyle
Average speed over a game is a complete waste of time.
(To be honest trying to use ‘average’ anything, for game analysis, usually is in team sports)
You’re making the basic mistake of looking at one isolated type of physical data and trying to draw conclusions from it.
Better teams don’t always (in fact most of the time) look better on physical statistics - except one - the scoreboard.
Look the stat’s of some of the best teams/players and many of them according to Prozone/Amisco etc have poor stat’s in games - but the relative contribution is what is most important. (Not to mention the questions over accuracy of the data).
Also, taking averages alone is a waste of time. You’ve no input or record of when, % possession, when possession was, number of players on the field, number of injuries, Number of games at altitude, time of goals number of cards, playing formation etc etc.
ALL these things are factors on physical outputs.
Trust me, this is an incredibly complex topic and area which many have tried to solve - and it is silly to attempt it yet without using the most important factor - common sense! As one coach is fond of saying drawing simple conclusions from simple data is for simple minds.
This was the gist of Charlie’s point.
Average speed over a game is a complete waste of time.
I agree this doesn’t say a ton, but it does help provide evidence against old school “endurance” coaches that your players, on average, aren’t moving that fast over the course of match.
I have seen nearly every athlete who sees me, they are given runs that emphasize runs 20 minutes progressing upwards of 70 minutes, but typically 50 minutes straight, 3 days a week.
Possibly, but I’d argue that’s not really positively impacting or shifting performance, apart from pacifying a coach - though that might be your point.
50 min runs? I still can’t believe players are given that kind of running to do!
One of the problems with more recent sports science is that physical performance data is being produced by the page full, but being looked at in isolation, painting a false perspective. It MUST be assessed alongside performance data.
As an example …
The four most important things to look at from a game perspective when assessing average speeds (m/min or km/hr) in team sports are …
- Number of runs (instances) at the higher speeds or speed zone specified
- Time of the runs during the game (not duration) when they occurred
- Proximity to effective action, (how effective that run was)
- Positive negative outcome
Agreed on all points above. Watching younger players, it is quite humorous to see the outside mid run up and down the sidelines open on runs and the center mid, head down, misses opportunity after opportunity, or just running up and down the sidelines when the ball isn’t in a playable range, in which case you are wasting energy. These two examples are relatable and help show your points above.
As I posted earlier, after individual analysis of actual ball possession time of an athlete, it helped prove point that in her specific instance, she did nothing but one touch pass the ball, and the rest of the time was specific “fitness.”
Exactly.
I’ve stories, that I won’t bore you with, from personal experiences of well known players running numbers up to keep stat’s up (distances, sprints) and then on the other side, some of the greats showing incredibly low numbers yet being the most effective player, and game winning, on the team. Also of whole team stat’s showing the same.
The biggest danger I see is actually the focusing on the stat’s incorrectly and this then becomes a motivator for players to do stupid things.
Think ‘headless chicken’.
no23, are you sure about that? From my personal experience, in Italy no player gives a damn about statistics, nobody talks about that. The only metrics are goal scored, maybe assists, and money. For other players, not forwards, metrics are not readily used.
Thus, it looks suspect that people in other places do care about those stats.
You only give a damn about stat’s if you have them!
In other words, teams that don’t have statistics available to them or don’t use the systems (Prozone, Amisco etc) certainly don’t (can’t) care about them!
However in some teams where they are used and are available coaches look at the raw data and make comments/decisions on this. When players notice this then they often respond like I describe.
Of course, in the broadest sense though, all that really matters to soccer players is money!
All higher level teams have the possibility of having stats, technology is mature ad readily available.
I’m not quite sure what you mean by your response? If you mean that they must play 10 months by contract-to be paid- I fully understand that. My comment about them playing that much helped to better shape my understanding of the training limitations these top players are under and how there was not much time in their offseason.
I simply did not know the year of the top professional lasted that long.
I meant that before discussing strategies for athletic preparation we have to know the boundaries within which we are operating. That means that 10 months of play + 1 month of vacation leave 1 month maximum for a GPP phase (melting into the early stage of team training). I basically wanted to say that, nothing personal.
For a simple game.
Well it is… Its just that England in particular made it look very complicated.