Tartarus Sorceror
Posts: 1774
Joined: Tuesday, 23rd December 2014, 23:39
CBoE stats
It's handled by the _ball_of_energy() function in
https://github.com/crawl/crawl/blob/be3 ... e/evoke.cc
I wrote a short program to see the probabilities of the different outcomes. These are randomized over 10k trials rather than exact, because there are a lot of dice rolls involved and calculating all the possible dice outcomes would be tricky/time consuming.
The first row of output tells you the best case scenario (average mp gain if you succeed).
Each subsequent row tells you the likely outcomes for a given percentage of MP. For instance, here's a row from the evocations = 10 table:
That means that if you're at 10% mp and evoke CBOE, you have a 3.5%% chance of int drain, an 87% chance of losing all your MP, an 8.5% chance of confusion, a 1.3% chance of success, and on average, a single use of CBOE will result in you losing 4.2 MP, assuming your max MP is 50. Note that your max MP only affects that last column - all the other columns are unchanged if your max MP is not 50. All other things equal, the average MP gain goes up as your max MP goes down, because you have the potential to lose less MP on a failure.
Here's the table for 10 evocations.
- Code:
Average mp gain if success: 9.5
MP: 10% int drain: 0.0348 mp loss: 0.8669 confusion: 0.0854 success: 0.0129 avg net mp: -4.21195
MP: 20% int drain: 0.0318 mp loss: 0.7365 confusion: 0.0822 success: 0.1495 avg net mp: -5.94475
MP: 30% int drain: 0.033 mp loss: 0.3896 confusion: 0.0847 success: 0.4927 avg net mp: -1.16335
MP: 40% int drain: 0.0326 mp loss: 0.1326 confusion: 0.087 success: 0.7478 avg net mp: 4.4521
MP: 50% int drain: 0.0325 mp loss: 0.0856 confusion: 0.0798 success: 0.8021 avg net mp: 5.47995
MP: 60% int drain: 0.0334 mp loss: 0.0807 confusion: 0.0814 success: 0.8045 avg net mp: 5.22175
MP: 70% int drain: 0.0315 mp loss: 0.0819 confusion: 0.085 success: 0.8016 avg net mp: 4.7487
MP: 80% int drain: 0.0323 mp loss: 0.0862 confusion: 0.0811 success: 0.8004 avg net mp: 4.1558
MP: 90% int drain: 0.0335 mp loss: 0.0818 confusion: 0.0845 success: 0.8002 avg net mp: 3.9209
Here's the table for 15 evocations.
- Code:
Average mp gain if success: 12.0
MP: 10% int drain: 0.0271 mp loss: 0.8832 confusion: 0.059 success: 0.0307 avg net mp: -4.0476
MP: 20% int drain: 0.0188 mp loss: 0.6095 confusion: 0.0558 success: 0.3159 avg net mp: -2.3042
MP: 30% int drain: 0.0206 mp loss: 0.1903 confusion: 0.054 success: 0.7351 avg net mp: 5.9667
MP: 40% int drain: 0.0214 mp loss: 0.0711 confusion: 0.0553 success: 0.8522 avg net mp: 8.8044
MP: 50% int drain: 0.0237 mp loss: 0.0714 confusion: 0.0553 success: 0.8496 avg net mp: 8.4102
MP: 60% int drain: 0.0232 mp loss: 0.0653 confusion: 0.0574 success: 0.8541 avg net mp: 8.2902
MP: 70% int drain: 0.0226 mp loss: 0.0677 confusion: 0.0549 success: 0.8548 avg net mp: 7.8881
MP: 80% int drain: 0.0226 mp loss: 0.0721 confusion: 0.0585 success: 0.8468 avg net mp: 7.2776
MP: 90% int drain: 0.0233 mp loss: 0.0704 confusion: 0.0537 success: 0.8526 avg net mp: 7.0632
Here's the table for 20 evocations.
- Code:
Average mp gain if success: 14.5
MP: 10% int drain: 0.0167 mp loss: 0.8614 confusion: 0.0396 success: 0.0823 avg net mp: -3.11365
MP: 20% int drain: 0.016 mp loss: 0.3518 confusion: 0.0443 success: 0.5879 avg net mp: 5.00655
MP: 30% int drain: 0.0162 mp loss: 0.0686 confusion: 0.0402 success: 0.875 avg net mp: 11.6585
MP: 40% int drain: 0.0159 mp loss: 0.0606 confusion: 0.0452 success: 0.8783 avg net mp: 11.52335
MP: 50% int drain: 0.0172 mp loss: 0.0605 confusion: 0.0443 success: 0.878 avg net mp: 11.2185
MP: 60% int drain: 0.0154 mp loss: 0.0594 confusion: 0.0398 success: 0.8854 avg net mp: 11.0563
MP: 70% int drain: 0.0164 mp loss: 0.0635 confusion: 0.0434 success: 0.8767 avg net mp: 10.48965
MP: 80% int drain: 0.0169 mp loss: 0.0667 confusion: 0.0444 success: 0.872 avg net mp: 9.976
MP: 90% int drain: 0.0179 mp loss: 0.0621 confusion: 0.0414 success: 0.8786 avg net mp: 9.9452
Here's the table for 27 evocations.
- Code:
Average mp gain if success: 18.0
MP: 10% int drain: 0.0101 mp loss: 0.5506 confusion: 0.0323 success: 0.407 avg net mp: 4.573
MP: 20% int drain: 0.0119 mp loss: 0.0589 confusion: 0.0305 success: 0.8987 avg net mp: 15.5876
MP: 30% int drain: 0.0132 mp loss: 0.0526 confusion: 0.0292 success: 0.905 avg net mp: 15.501
MP: 40% int drain: 0.0111 mp loss: 0.0567 confusion: 0.0319 success: 0.9003 avg net mp: 15.0714
MP: 50% int drain: 0.0107 mp loss: 0.0536 confusion: 0.0309 success: 0.9048 avg net mp: 14.9464
MP: 60% int drain: 0.0131 mp loss: 0.0575 confusion: 0.0273 success: 0.9021 avg net mp: 14.5128
MP: 70% int drain: 0.0139 mp loss: 0.0569 confusion: 0.0308 success: 0.8984 avg net mp: 14.1797
MP: 80% int drain: 0.0106 mp loss: 0.0582 confusion: 0.0318 success: 0.8994 avg net mp: 13.8612
MP: 90% int drain: 0.0116 mp loss: 0.0539 confusion: 0.0316 success: 0.9029 avg net mp: 13.8267
(Actually, the "avg net mp" column is slightly inaccurate - an overestimate - b/c it doesn't account for not having enough max MP to gain the full amount. Shouldn't make too much difference except for MP near full, when you wouldn't want to use it anyway).
251 total wins Berder hyperborean + misc
83/108 recent wins (76%)
guides: safe tactics value of ac/ev/sh forum toxicity
- For this message the author Berder has received thanks: 6
- duvessa, mopl, Rast, Sprucery, ThreeInvisibleDucks, xentronium