Top 8 chance line graph race

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Ladder Simulation Objectives & Challenges

The primary objective of ladder simulations is to anticipate the prospective rankings of teams at the culmination of the home and away season. Our adopted approach is designed to generate forecasts pertaining to likely triumphs, percentage, expected profiles of final placings, and the likelihood of attaining a top 8 or top 4 ranking.

An inherent challenge in devising such predictions is the existence of an extremely vast range of possible permutations, particularly during the early stages of the season. To address this complex issue, a rigorous and systematic approach must be employed.

Our methodology involves the execution of exhaustive, brute force calculations to account for the multitude of possible outcomes. This approach enables us to offer an accurate, data-driven forecast of the possible outcomes, thereby facilitating informed decision-making among fans and analysts alike.

In conclusion, we utilise a rigorous and systematic methodology to deliver comprehensive ladder simulations that enable fans to anticipate the potential outcomes of the home and away season with greater accuracy and confidence.

Ladder Simulations Methodology

The methodology behind AFL ladder simulations is of significant interest to sports researchers and practitioners alike. In essence, ladder predictions are generated through the execution of numerous simulated seasons, typically exceeding 10,000, based on a range of criteria, including extant ladder standings, team ratings, and the remaining fixture.

Of the two primary simulation approaches, cold or static simulations are utilised by The Footycast, wherein team ratings are not updated after each match simulation during the season. The alternative hot or dynamic simulation method involves updating team ratings throughout each hypothetical season, although there is ongoing discussion within the footy prediction community regarding its utility. Matter of Stats has explored this topic extensively, in this exceptional piece on the subject.

While hot simulations have certain merits, cold simulations remain the preference of The Footycast for several reasons. Firstly, they offer speed and computational efficiency, thereby providing an expeditious means of generating predictions. Additionally, while hot simulations are acknowledged to offer some variability, this can also be achieved by tweaking variables that impact the randomness of each game, rendering the cold approach a viable alternative. Thus, while ongoing debate persists regarding the superiority of cold versus hot simulations, The Footycast maintains its use of the former method.