How does forecast work mtg

It's like each card has its own buyback spell built right in! We can all envision the stereotypical White-Blue control player sitting smugly behind a full grip, and that's the feel we wanted to capture with the mechanic. We didn't want to make things too easy, however. If there's one thing narrow-minded control players don't want to do, it's commit. Ideally they'll never tap a mana on their own turns, instead staying reactive and doing everything at the last minute.

I can remember playing against some of Randy Buehler's more famous Blue decks from back in the day, and he could actually win without ever tapping a land for mana on his own turn; he just countered everything and then eventually activated Stalking Stones and won. So if you want to forecast something, you'll have to commit some of your mana on your own turn. Now each decision is crucial, and better players will learn when the right time to forecast something is and when it's better to hold back.

Even with all these constraints which were all set up in design , development still had huge concerns about the mechanic. It had two big problems—one, it basically couldn't be stopped short of discard you can't counterspell a forecast effect , and two, if they're too powerful, they lead to repetitive games wherein nothing either player draws matters much as one player will simply forecast over and over again until the game ends.

The card developers liked pointing to as evidence against forecast was Capsize , which was a buyback Boomerang from Tempest. Capsize was a powerful card that elicits strong emotions of both love and hate from our players. People that like powerful effects, annoying their opponents, and winning, all love Capsize. Once the Capsize player hits six mana, assuming he's winning, it's pretty clear how the game is going to play out.

Bounce your thing. People that are just playing the game for fun really don't like cards like Capsize , and tend to avoid them. I've been on both sides of that fence—playing in Tempest block PTQs, where the goal was to win, I had no problem putting Awakening into play and removing my opponent's entire board from the table. But in fun games in my apartment, my roommates and I usually cajoled each other until we took the Capsize s out of our decks. Ante Divvy Rhystic. Bury Landhome Substance.

List of obsolete terminology List of deprecated mechanics List of silver-bordered mechanics List of unreleased mechanics Storm Scale. Cancel Save. Universal Conquest Wiki.

Forecast [cost] Activate this ability only during your upkeep and only once each turn. Forecast Detain Addendum. Transmute Cipher Surveil. Hellbent Unleash Spectacle. Bloodthirst Bloodrush Riot.

Convoke Populate. Haunt Extort Afterlife. Dredge Scavenge Undergrowth. Next, as we want to predict price change we will use the differential time-series, which is the difference between the current price and the previous one sometimes called returns , and standardize the data to speed up training of the network. This is standard pracitce, but if you want to see the details of this, see the Jupyter notebook here. We do the predictions using a very simple neural network implemented using Keras, which is an excellent Python library for quickly prototyping ideas.

See the Keras documentation , and also this example , for details. So far we made some data that looks like the daily price time-series for a typical Magic: The Gathering card, as it undergoes several reprints. From the training loss above, things are looking quite positive, but neural networks can easily overfit to the training data and so we need to see how well our model generalizes to unseen data.

Sanity check. When conducting regression on a continuous time-series the squared loss metric, using the current known value of the price as a guess for the next price is always going to be a pretty reasonable choice.

Fortunately, the plots below show that our simple network is able to correctly predict one step into the future for our very simple model! We built a model of the price of a ficticious Magic: The Gathering playing card, over time, as it undergoes several reprints in our simple model, each reprint leads to a small drop in price for the subsequent days.