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Results
Will an optimized scan behavior always lead to enhanced decision making in football?
To be able to answer this question we have designed two tests. One to analyze the scan behavior of the average football player and the other to analyze the action execution preference. (By action execution preference we mean, is there any preference in the visual field while executing the action)
The tests were designed and developed by our experts in cognitive neuroscience and neuromuscular training. The tests were taken in the SIMUST arena, where all actions and moves were registered by cameras and analyzed by our AI-driven software.
Players participating in the tests were between the ages of 11 and 19, with a total of 2691 tests completed.
Phase one: Scanning behavior
The aim is to see if the player has 360-degree awareness. If so, is he/she able to recognize all available targets to choose from. And finally, is the player able to execute his/her action while being aware of the position changes of his/her teammates on the field. For this test the players are repeatedly given randomized playable choices on the right and left side of their visual field to pass the ball to. The players must also recognize and be aware of the position of the next available possibility.
Parameters used for this phase:
TR (Target Recognition /Field Awareness (60-90-210-360-degree)
DA (Divided Attention)
SAE (Successful Action Execution)
Results average per age category.
|
TR (%) |
DA (%) |
SAE (%) |
|
O12 |
68,3 |
52,7 |
52,7 |
|
O13 |
69,2 |
67,2 |
49,7 |
|
O14 |
72,3 |
66,8 |
51,9 |
|
O15 |
67,4 |
60,9 |
47,0 |
|
O16 |
65,8 |
59,7 |
42,4 |
|
O17 |
67,8 |
62,1 |
46,2 |
|
O19 |
72,0 |
65,8 |
53,4 |
TR shows that there is a certain lack in scanning behavior in all age categories. An average of 31% of the tested players were not able to identify all playable targets due to preferences to one side of their visual field.
DA shows, when we add an extra task (player has to pass the ball while at the same time recognizing and being aware of the next possibility) the scanning capability drops by another 8% to15 %.
SAE drops dramatically to an average of 50% when the players have to execute an action and scan and recognize the next playable possibilities.
Phase two: Decision-making and Action Execution
As we know, prior to any action, the visual processing starts while scanning and this leads to the decision-making.
The aim was to discover if flawless scanning behavior automatically enhances the decision-making process.
For this test, the players were repeatedly given two simultaneous, identical playable options to choose from, one on the right and the other on the left side of their visual field. The players had to execute their actions by passing the ball to their preferred side.
The test is designed in such a way that it is virtually impossible not to see one of the given options.
Parameters used for this phase:
AEP (Action Execution Preference)
When we studied the decision-making process and the action execution preference, we discovered that, although the players in this test were fully aware of the given choices, they tended to pass the ball to their preferred side and neglected other given options.
Conclusion
The conclusion of our study is that optimized scan behavior is just the starting point and will not necessarily and automatically lead to increased playable options and enhanced decision-making. The decision-making is heavily dependent on the action execution preference, using conditioned and recorded patterns from the past. In other words, the player will decide to play the ball to where it feels safe (within the range of his/her comfort-zone).
Suggestion: To overcome this, the player needs to expand his/her comfort-zone. We invite you to discover how this is made possible.
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