Mod Tutorial: Part 6

This part will explain answer effects - the kinds of effects, how to use them, and where.

Step 18. Understanding Answer Scores - and using them

As you may already know, the whole point of the game is that the answers you give effect your polling. Since elections are complicated, there's three main mechanics that can help effect polling - and a good scenario makes use of all of them.

A. Global Effects

As evident by the name, these answer scores affect a candidate's polling nationwide (or statewide). For PA Gov 2022, I used a lot of these global answer score to affect your polling statewide. My advise for presidential election mods is to use global answer scores when a nationally popular (or unpopular) position is taken - or a decently sized gaffe. Of course, it all depends on what you feel is best. I can tell you that Dan Bryan didn't use many global answer scores in making 2020 (he used a ton of state answer scores instead).

{\"model\": \"campaign_trail.answer_score_global\", \"pk\": 3086, \"fields\": {\"answer\": 5153, \"candidate\": 201, \"affected_candidate\": 200, \"global_multiplier\": -0.003}}

So, what does this mean? Well, each answer score has to have its own, unique PK. "answer" checks the answer the score will activate for. "candidate" checks the candidate you have to be playing as to activate. So in order for this score to go off, select answer 5153 as candidate 201 (Clinton). "affected_candidate" is who will gain the increase/decrease, and the global multiplier is how it'll help/hurt globally. So it'll make Trump's polling go down -0.003 globally.

State Multipliers are not an exact science - that's why playtesting and time is crucial to making a good mod. For example - look at other mods via BIGSHOT's benefit checker and see how their scores look. Find out what numbers work best for you - remember, you can set as many scores to activate for an answer. You can mix global with issue scores and state scores too.

B. Issue Scoring

As you'll remember from Part 4, you probably set up about 5 issue scores. The score is how the answer, just like the candidates and states, lean towards a certain issue, ranging from -1 to 1. The "issue_importance" is, as the name implies, how important the issue is to the nation. If, say, one of the issues is the economy, and there's a depression or recession, the issue importance would be high. A scenario like 1896 has high importance at the start, but it goes down as you define yourself on the issues.

I did something similar with 2016 Democratic Primaries - at the start, you can either mount a primary challenge against Obama in 2012 as Sanders - or leave the office of Secretary of State in late 2010 as Clinton. Doing both of these affects the issue score of 'Opinion of Obama' with a high importance. It'll help you in statess that dislike Obama, but hurt your candidacy in states where he is well-liked.

{\"model\": \"campaign_trail.answer_score_issue\", \"pk\": 2639, \"fields\": {\"answer\": 5139, \"issue\": 100, \"issue_score\": 0.3, \"issue_importance\": 2.0}},

For example - Issue 100 here is Ideology. Since the score is 0.3, it'll boost you in states that have the stances 'Moderate' and 'Leans Liberal', but hurt you elsewhere. Importance, of course, amplifies this.

I can't stress this enough - do not ignore issue scoring. There's a reason the Dan Bryan scenarios are still, despite all the mods, considered some of the best to replay - issue scoring makes it so easy to put together different maps depending on your decisions.

C. State Scoring

These work similar to global scores, except you specify the state (or states, if you add multiple) that the effect is applied to. Like last time, "candidate" must be the candidate you're playing as, "affected candidate" is who you want to have the answer effect, and the "global multiplier" is the increase or decrease you want said candidate to have.

State scores are valuable for situations like the New Hampshire energy question in 2000, gaining the endorsement of a popular statewide figure, or earning the backing of machines like Tammany Hall. Of course, answers can have multiple state scores, so if you want to focus on a region for an answer, this is how you'd do it.

{\"model\": \"campaign_trail.answer_score_state\", \"pk\": 20515, \"fields\": {\"answer\": 5196, \"state\": 1047, \"candidate\": 201, \"affected_candidate\": 201, \"state_multiplier\": 0.01575}},

As shown here, answer 5196 when playing as Clinton will boost her in state 1047 (Washington, DC) with a multiplier of 0.01575.

How to use Answer Scores

Answer effects are clearly one of the most crucial aspects for gameplay. Good writing and pacing can only get a mod so far if the answer effects are minimal and every question has one, clear, definitive answer. Issue and State scores are crucial for adding replayability, since they enable you to prevent 'correct' answers and let players discover the right strategy.

Dan Bryan makes heavy use of issue scores in scenarios like 1896, and uses tons of answer scores in scenarios like 2020. Again, I can't understate how useful benefit checking is for digging through the game to understand why replayable scenarios/mods are so well done. A lot of that is internally.

Step 19: Endings

There's 2 ways to do endings screens for New Campaign Trail. If you simply wish to do a win, loss, and tie/no majority screen, you can easily find that info for each candidate under their respective PK in code 1 (near their bio). If your mod is on the simpler side, there's nothing wrong with this option.

Some of the more complicated endings aren't options in Jet's Modding Tool, so even if you're using that, I would reccomend you take a look at these templates. Edit them to your liking and put them at the bottom of your Code 2.

I have some ending code templates here, along with comments labeled across.

I'd love to include templates for endings that we see in the Netherlands mods, but some of that is more advanced and much more manual. All the mod files are public in the GitHub, and I invite you to take a look at my ending Codes if you so wish.