When watching a baseball game, it is hard to see all the work of the mind that goes into the process but in reality perception, motivation, the focus of attention and causality are involved, thus creating different levels of skill between players. All the players involved have done it before so they have a perceptual picture of what is going to happen. By knowing the laws of physics they are able to predict and determine the causality of actions and reactions. For example when a pitcher is about to throw the ball he focuses his attention on the glove, imagines how the ball will fly if it is going to curve, takes into account the wind or the absence of it and then visualizes the throw itself. There are several factors that could influence his attention during the process of the game. If he missed a practice or did not have enough sleep his attention might be below, as he is less focused because of feeling tired. His motivation on the other hand is derived from his want to win the game. If there is a big reward for winning, financially and prestige wise, he might be very determined and so his focus and attention will increase (Engelmann & Pessoa, 2007). But if the game is not important or he is thinking of quitting the league his focus will suffer greatly and influence his game.
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The best way to use cognitive powers of motivation and attention is to create a mental picture of the causes and effects that will take place. A batter can imagine that if at the last point he takes a step to the right it could influence the pitcher by confusing him and so the ball will not be thrown as fast or as precisely. Individual differences in attention, motivation and personal interests derived from character, all have an important role in the perception of causality and visual modeling. The player’s model of causality is mainly based on previous knowledge—memory and the ability to predict by comparing the possible outcomes of physical activity, to what has happened in the past in a similar situation (Malmberg & Annis, 2012). First, the player must focus his motivation on winning the game because without determination and motivation his attention will be below. While his attention has risen he is taking into a visual and mental account all the players that are located on the field, where everyone is situated and what they will do once the ball flies out of the pitcher’s hand.
There are two outcomes: either the ball will be caught right away or the batter will hit the ball. If the ball is caught there is no further action except if the player is sent out.
But if the ball is hit there are many things that will happen. The batter will start running to the base, if there were players at other bases they will also run to the next base and the catchers will try to predict where the ball will land and so they run towards that place to catch it. The best model of determining the causality of the game is by having the motivation and focusing attention, which is the moving force of the mental processes and perception. If attention is high, then perception is also high and it makes the determination and analysis of causality more productive (Brose & Schiedek, 2011). The role of attention and motivation is crucial because they affect the extraction of information from memory in order to adequately predict and structurize causality (Rouse & Boff, 2011). Human reasoning about complex causal systems determines the outcome of their actions and a baseball game is not any different.
Brose, A. & Schiedek, F. (2011). Daily variability in working memory is coupled with negative affect: The role of attention and motivation. American Psychological Association, 12(3), 605–617.
Engelmann, J. & Pessoa, L. (2007). Motivation sharpens exogenous spatial attention. American Psychological Association, 7(3), 668-674.
Malmberg, K. & Annis J. (2012). On the relationship between memory and perception: Sequential dependencies in recognition memory testing. Journal of Experimental Psychology, 141(2), 233-259.
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Rouse, B. & Boff, R. (2011). Human representation and reasoning about complex causal systems. Information Knowledge Systems Management, 10(1-4), 85-99.