Data scientist builds price prediction model to find OVERVALUED & UNDERVALUED Pokémon cards

Why are some Pokémon cards SO EXPENSIVE? Are the prices justified? What causes some cards to skyrocket and some to flatline for so long? As a professional data analyst and avid Pokémon collector, I dug deep to find out what are the driving factors that affect these ever increasing, sometimes insane prices. And what I found is not only can we accurately predict prices, but we can use this information to see which cards are UNDERVALUED and OVERVALUED as well. Buckle up, if you like data science, and/or you like collecting Pokémon, this is a must-watch. Don't forget to check out https://mycollectrics.com. I'm continuing development of this site and expect to launch some HUGE updates before the summer. Thanks as always, please like and subscribe!