This post is also available in: 日本語 (Japanese)
Hey there, fellow Ironlanders.
Did you swear your daily oath to iron for better dice luck today?
Because as for me—
the dice have completely abandoned me.
…So yeah.
That’s what pushed me to simulate Ironsworn’s success probabilities using Python.
Action Roll Success Rates
For each total modifier value (Stats + bonuses), I ran one million trials.
Code
Here’s the Python code I used.
# Action Roll
import random as rand
print('Enter your Modifier for Action Roll')
Modifier = int(input())
Stronghit = 0
Weakhit = 0
Miss = 0
for i in range(1, 1000000):
actiondice = rand.randint(1,6)
actionscore = Modifier + actiondice
if actionscore > 10:
actionscore = 10
challengedice1 = rand.randint(1,10)
challengedice2 = rand.randint(1,10)
if actionscore > challengedice1 and actionscore > challengedice2:
Stronghit += 1
elif actionscore <= challengedice1 and actionscore <= challengedice2:
Miss += 1
else:
Weakhit += 1
print('Stronghit ' + str(Stronghit * 0.0001))
print('Weakhit ' + str(Weakhit * 0.0001))
print('Miss ' + str(Miss * 0.0001))
Results
All results are shown as percentages.
Values are rounded down after the second decimal place.
Even though I ran a million trials for each value, this is still a random simulation, so there may be slight deviations from the exact combinatorial probabilities.
Also, since modifiers 9 and 10 are functionally identical under Ironsworn’s rules, any apparent reversal between those rows is just random noise.
| Total Modifier | Miss (%) | Weak Hit (%) | Strong Hit (%) |
|---|---|---|---|
| 1 | 45.1% | 39.6% | 15.2% |
| 2 | 33.1% | 43.6% | 23.2% |
| 3 | 23.1% | 43.6% | 33.1% |
| 4 | 15.1% | 39.7% | 45.0% |
| 5 | 9.3% | 34.6% | 55.9% |
| 6 | 5.3% | 29.3% | 65.3% |
| 7 | 2.8% | 24.2% | 72.8% |
| 8 | 1.4% | 20.2% | 78.2% |
| 9 | 0.9% | 18.0% | 80.9% |
| 10 | 1.0% | 18.0% | 80.9% |
Since starting characters usually have attributes in the 1–3 range, you can see that:
- You’re going to miss a lot
- Weak Hit rates don’t change that much in this range
- Instead, higher modifiers mostly convert Misses into Strong Hits
For reference, the miss rate doesn’t drop below 10% until your total modifier exceeds 5.
Strong Hit probability increases as modifiers go up, but the growth slows down and caps out around 80.9%.
So no—you can’t just stack buffs forever and reach
“lol I only Strong Hit now” territory.
Burning Momentum & Progress Roll Success Rates
For both Momentum values and Progress scores, I ran one million trials each.
Code
Here’s the Python code used for this part.
# Burning Momentum
import random as rand
print('Enter your Momentum')
Momentum = int(input())
Stronghit = 0
Weakhit = 0
Miss = 0
for i in range(1, 1000000):
challengedice1 = rand.randint(1,10)
challengedice2 = rand.randint(1,10)
if Momentum > challengedice1 and Momentum > challengedice2:
Stronghit += 1
elif Momentum <= challengedice1 and Momentum <= challengedice2:
Miss += 1
else:
Weakhit += 1
print('Stronghit ' + str(Stronghit * 0.0001))
print('Weakhit ' + str(Weakhit * 0.0001))
print('Miss ' + str(Miss * 0.0001))
Results
Again, percentages, rounded down after the second decimal.
Since Burning Momentum and Progress Rolls use the same math, I tested them together.
| Momentum / Progress | Miss (%) | Weak Hit (%) | Strong Hit (%) |
|---|---|---|---|
| 1 | 99.9% | 0.0% | 0.0% |
| 2 | 81.0% | 18.0% | 0.9% |
| 3 | 63.9% | 32.0% | 4.0% |
| 4 | 49.0% | 42.0% | 8.9% |
| 5 | 36.0% | 48.0% | 15.9% |
| 6 | 24.9% | 49.9% | 25.0% |
| 7 | 16.0% | 47.9% | 35.9% |
| 8 | 9.0% | 42.0% | 48.9% |
| 9 | 4.0% | 32.0% | 63.9% |
| 10 | 0.9% | 17.9% | 81.0% |
Both Burning Momentum and Progress Rolls are used at decisive moments, so missing here really hurts.
The miss rate only drops below 10% once Momentum value or Progress score reaches 8 or higher.
And around that point, Strong Hit probability suddenly shoots up—eventually hitting 81.0%.
…but even then, no matter how much you stockpile Momentum value or Progress score, there’s still about a 20% chance you won’t get a Strong Hit.
Ironsworn does not let you escape uncertainty that easily.
Conclusion
I love probability math.
Everyone should spin up Python and run simulations.
Seriously.
This work is based on Ironsworn (found at www.ironswornrpg.com), created by Shawn Tomkin, and licensed for our use under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

