Trading card games have captured a multitude of enthusiasts’ imaginations worldwide with their engrossing fusion of strategy and fantastical lore. Amongst the host of these games, one in particular, known as Legends of Elysium or simply LoE, has been garnering considerable attention in the trading card game community. Of late, the burgeoning prices of trading cards have sparked conversations not only amongst avid players but among prospective investors too. In today’s blog post, we shall examine decision tree analysis – a technique that might just enable us to forecast these escalating prices.
The allure of trading card games for a myriad of people, from casual players to dedicated gamers and even aficionados of fantasy literature, can be attributed to their sophisticated game mechanics, immersive backstories and compelling graphics. Their collectable nature, where the scarcity and demand for specific cards dictate their value, has not only drawn more participants but has also painted them as a canvas for investment opportunities. However, predicting price surges has been an elusive skill to acquire – until perhaps now. We’re set to delve into the notion of decision tree analysis and how it could be our clandestine ally in anticipating those unpredictable price rises.
A study conspicuously titled “Prediction Soaring Price by Decision Tree Dealing” found its way to publication in the International Journal of Digital Society in 2023, and it’s packed with rich detail about the trading card game market. This research centres on the use of decision tree models to predict price inflations. Its authors present a solution to the conundrum posed by imbalanced data, which has the potential to drastically skew the price prognoses of TCG markets.
This research initiated with a preliminary trial, underlining the importance of rightly managing imbalanced data for predicting TCG market prices. Failure to address this data accurately led to predominantly inaccurate models. This formed the crux of the study, focusing on how to effectively tackle imbalanced data.
The researchers collated data for some 43,535 TCG cards, with prices ascertained up to 18th June 2022. Game-specific and selected special cards were omitted from their dataset to avoid skewing the outcome. Cards were classified as “soaring” if their prices shot up by 1.5 times or more compared to their minimal price, however, only within the price bracket of 1 to 150 USD, to diminish the distortion from excessively high-priced cards. They put forward three principal techniques for managing imbalanced data, including Synthetic Minority Over-sampling Technique (SMOTE) for oversampling, random undersampling, and a cost-sensitive approach.
Interestingly, all three methodologies bolstered the recall score and accurately predicted prices considering the imbalanced data. The research evidenced that the undersampling and cost-aware strategies yielded more precise forecasts, prompting the authors to vouch for these approaches for subsequent research and price prediction in this realm. They further advised tailor-made strategies to each distinct price bracket and particular models for diversified price ranges to achieve more spot-on predictions.
In juxtaposition, Legends of Elysium offers a contrasting viewpoint on the TCG market. While LoE entices players with its beguiling fantasy domain and strategic game manoeuvring, the aforementioned study underscores the importance of data analysis and predictive modelling to understand and foresee market trends. Both angles have their indispensable significance; the enchanting narrative and strategic play in LoE contribute to its popularity and, as a result, could influence market values. Contrarily, analytical models like decision tree analysis provide perceptions to untangle and presage market price fluctuations.
In summary, this insightful study sheds light on the TCG market, especially in terms of predicting price escalations. The proposed methods for mitigating imbalanced data can hold significant advantage for all stakeholders within the TCG sphere, including players, collectors, and traders. Moreover, when considered alongside LoE, it spotlights the interplay between game dynamics and market propensities, thereby underscoring the salience of each within the broad TCG ecosystem.