A Lazy Sequence

Gumshoe: antagonist spends

Last time in this series I had a look at player character competency in Gumshoe. This time I want to look the antagonist spends. While much of Gumshoe can leverage existing GMing skills from other games, this is something I found took a bit of thought and practice to become comfortable with.

As with the spends players make for their characters, ultimately the GM should be making spends that are narratively interesting. Use your instinct about drama above all, and fall back on the math when in doubt. The rest of this post will cover that math, as well as some suggestions and heuristics for spending narratively.

Unlike a player character, most GMC’s and monsters wont hang around longer than a single fight. Where a player is always balancing efficacy now with efficacy later, there is rarely such a dilemma for the GM. Instead, the threat of the antagonist is ideally maximized by spending all the points before they expire. For big ticket enemies like named vampires in Night’s Black Agents you will want to find a balance between this and spending like a player character.

Philosophically, Gumshoe games tend not to concern themselves with balance between players and antaongists. Player’s are expected to flee in the face over powering odds.

The basic formula

The basic math I use is based on determining the duration of the fight (e.g. till one side dies). This is done by multiplying the number of attacks each side delivers by the probability of hitting, and the average damage from a hit, and using that to divide the health of the target by that damage to determine rounds.

The basic formula for a single character is:

average damage per round = average damage × probability of hitting
rounds till ko = target health ÷ average damage per round

The trick is of course figuring out the average damage and the probability of hitting.

We calculate the average damage by offsetting 3.5 (the average roll on a d6) by the attacks damage modifier. Remember to clamp this value’s lower bound to 0 or 1, depending on how you interpret the minimum damage for the game you are playing.

The probability to hit is based on the target’s hit threshold. Here’s the formula:

probability to hit = (6 - max(0, (hit threshold - 1) - spend)) / 6

It’s a bit of a mouthful; that -1 is to adjust for the greater or equal nature of tests.

Do this for both the player characters and the antagonists. You may find that you will be summing all the health pools, and dividing it by the sum of the average damage per round. I find it helpful to do both sides with passive (0 points) and aggressive (3 points) spending to figure out the bounds, and I don’t worry too much about pool sizes messing the numbers up as they become exhausted. You could of course get fancy and figure out the mix of each characters aggressive attacks (till the run out of points) and passive attacks.

The baseline numbers

Let’s first examine the baseline of combat: never spending.

Our antagonist is going to be rolling an unmodified d6 against a target number of 4 (or 3 for characters with a low athletics). That’s a 50% chance (or 66%) of hitting. By the formulas above, our antagonists will therefore be doing (3.5 + damage modifier) × 0.5 (or (3.5 + damage modifier) × 0.66) damage per attack. So for an example weak antagonist with no damage modifier, and only one attack against athletic protagonists, thats 1.75 damage ((3.5 + 0) × 0.5) a round.

So for example, with 3 PCs each at 10 health will have a total pool of (10 + 12) × 3 = 66. To use a group of 6 of the the example weak antagonist, they would require around 66 ÷ (1.75 × 6) = 6.2 rounds to kill all 3 PCs.

The aggressive numbers

For our upper bound, let’s assume the antagonist is spending 3 points an attack. The only difference to the baseline math is the probability of a hit: it goes to 100%. Thats 3.5 damage a round now for our example antagonist. Damage has doubled so survival time is halved: 66 ÷ (3.5 × 6) = 3.1 rounds.

Do this for the PCs against the antagonists too. Use the minimum baseline (the upper bound) and minimum aggressive numbers (the lower bound) as the approximate range for how long might last. E.g. if you have calculated the players baseline is 5 rounds, and the antagonists is 4 rounds, then your upper bound is 4. Likewise the players aggressive is 2 rounds and the antagonists is 1 then the lower bound would be 1 round.

Applying the bounds to the available pools

For optimal pool usage, divide your antagonists pool by those bounds, and that will tell you how much to spend to ensure you are maximizing their utility. E.g. a fighting pool of 8, with bounds of 1 and 4 would be 8 and 2 points respectively. You would clamp that 8 to 3 knowing any other points are wasted.

Making the numbers narratively meaningful

It’s all well and good knowing how you can maximize your available pools, but it’s important to also play them in a way that is befitting the character.

Here are some basic patterns to consider, what they might convey.

  • High constant spend: An alert, dangerous threat.
  • Low constant spend: Lacks awareness, or doesn’t acknowledge PCs as a risk.
  • Ramping down spends: Fatiguing, or reassessing threat.
  • Ramping up spends: Panicking, or reassessing threat.
  • Punctuated spends: Default to 0 or 1 point spends, and use 3 point spends intermittently to mix up the rhythm of the fight. This enemy needs some time to recharge, or perhaps responds to a surge of adrenaline when hit.

Further, here are some heuristics you can employ:

  • Monsters/inhuman enemies who can’t distinguish between a professor and a soldier should spend the same amount per target regardless of what you the GM know about hit thresholds.
  • Adjust for cover for tactically aware enemies.
  • High hit threshold or heavily armoured enemies gave the luxury of frugal spending.
  • Human enemies who have not been in a proper fight should spend less by a point (at least). They aren’t familiar with high threshold targets.

Next time, we will leave the numbers behind and look at the use of investigative abilities in some more detail.

3 July 2019