Algo machín hoy.
Understanding training has been interesting to me before I even knew statistical software existed. The first time I ever input training data was with a V5 pen inside a composition notebook.
Consider something I've been thinking through:
We are a blob of networks.
Our self-efficacy, self-talk, nutrition, childhood interactions, parents, friends, taste in art, autobiographical memory biases, choice of music for the day, all of these relationships are constantly strengthening and influencing each other, and thus form a network within our selves. I then started to wonder, what would a network structure for an athlete look like? How does this network architecture of relationships change over time?
Achis? Y eso como, cabron?
Below is a completely fake and simple model built in R based off of variables like fatigue, confidence, stress, total quality distance ran, average pace, etc.
Let's say this is the network architecture modeled from 6 weeks (42 days) of training data.
From an analyst perspective, understanding how these variables interact over time to understand my athletic performance from a holistic view could help me address issues and improve my performance.
Since the above example is based off completely random mathematics, I will try to explain the parts that would make sense.
Node Centrality (Influencers)
In a network, I'm interesting in understanding what variable (node) is the most important/influential. Here, nodes like confidence, total quality distance, pain, nutrition, and sleep quality seem to be the most central nodes, which in theory would let me understand that these variables are critical to my overall structure. Which variables are they influencing? Is it good or bad? Is it strong or weak? Are these nodes resilient?
Edge Weights
Understanding the strength of the influence is another thing. Edge weights in a network represent the intensity or significance of the relationship between connected nodes. Thicker edges typically indicate stronger relationships, while thinner edges represent weaker connections.
Peripheral Nodes
Now, observe the weak relationship and isolation of the social support node. Theoretically, a lack of social support has a number of negative implications to an individual not only in athleticism, but in life in general, and would call for an intervention.
Well, how do we improve a person's social support?
How would the overall network architecture change?
Anyway,
That's kinda what I'm thinking about lately.
En una troca vieja,
El de las Chanclas Deportivas
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