Cricket, India vs Sri Lanka, Exploration
My friend Chino sent a note saying that in the midst of the tragedies on the world stage,
Though I didn't want to make this a formal event, it was another opportunity to explore sporting events' possible effects on the GCP network (they have generally been weak or null), so I asked Chino for a more focused prediction, and he responded that:
Indeed if we do look at this moment, the outcome is a significant deviation, mostly coming just at the very end of this time period.
What is most striking, however, is the picture of the data from the whole match. In contrast to the positive deviation of the finish, the 8-hour period of the full match shows a persistent low correlation in the network, so much so that the trend culminates in a deviation that has roughly 100 to 1 odds. See the second figure below. Please remember that these pictures of data are showing a combination of a small signal in a sea of noise, meaning that they cannot be interpreted literally.
It is important to keep in mind that we have only a tiny statistical effect, so that it is always hard to distinguish signal from noise. This means that every "success" might be largely driven by chance, and every "null" might include a real signal overwhelmed by noise. In the long run, a real effect can be identified only by patiently accumulating replications of similar analyses.