1. Tsinghua (Win: 40%, Gold: 90%, Medal: 100% after some rounding)
- CF max: 3441, 3203, 2967 (agg = 3516)
- Open Cup: 1, 1, 11, 9 (median = 5)
- China Final: 1
- MIPT: 1, 1, 1, 2, 4, 1, 4
2. Warsaw (Win: 15%, Gold: 75%, Medal: 95%)
- CF max: 3122, 2962, 2826 (agg = 3237)
- Open Cup: 2, 3 (median = 2.5)
- Petrozavodsk: 4, 2, 4, 3, 2, 2, 1, 2
3. SPb ITMO (Win: 15%, Gold: 50%, Medal: 90%)
- CF max: 2880, 2870, 2860 (agg = 3104)
- Open Cup: 7, 3, 2, 1, 13, 1, 2, 1, 3, 7, 13, 8, 8, 12, 3, 2, 1, 12 (median = 3)
- Petrozavodsk: 4, 1, 3, 1, 6, 5, 3, 7, 5
- MIPT: 6, 2, 3, 1, 5, 2, 1
4. SPb SU (Win: 10%, Gold: 40%, Medal: 85%)
- CF max: 3170, 2951, 2936 (agg = 3281)
- Open Cup: 9, 21, 18, 5, 3, 4, 9, 9, 6, 1, 2, 2, 7, 1, 4, 23, 20, 4 (median = 5.5)
- Petrozavodsk: 7, 3, 6, 5, 8, 1, 4, 5, 1
- MIPT: 2, 4, 2, 3, 1, 10, 8
5. Seoul (Win: 5%, Gold: 40%, Medal: 85%)
- CF max: 3174, 2919, 2760 (agg = 3250)
- Open Cup: 4, failed, 4 (median = 4)
6. MIPT (Win: 5%, Gold: 30%, Medal: 75%)
- CF max: 2928, 2757, 2756 (agg = 3063)
- Open Cup: 16, 29, 27, 28, 7, 24, 17, 15, 9, 15, 17, 3, 9, 4, 10 (median = 15)
- Petrozavodsk: 1, 5, 5, 5, 1, 6, 6, 1
- MIPT: 3, 6, 5, 4, 6, 3
7. MIT (Win: 5%, Gold: 30%, Medal: 75%)
- CF max: 2900, 2637, 2540 (agg = 2981)
- Open Cup: Equivalent to 2.5 in NAIPC
8. KTH (Gold: 10%, Medal: 60%)
- CF max: 2761, 2637, 2273 (agg = 2870)
- Open Cup: 2, 17, failed, 7 (median = 12)
- MIPT: 5, 5, 16, 7, 7, 2
9. Fudan (Gold: 5%, Medal: 55%)
- CF max: 2543, 2367, 2327 (agg = 2667)
- Open Cup: 6, 13, 9, 6, 13, 18 (median = 11)
- China Final: 5
- MIPT: 12, 3, 7, 15, 13, 4, 5
10. New South Wales (Gold: 5%, Medal: 50%)
- CF max: 3073, 2429, 2006 (agg = 3082)
- Open Cup: 6, 8, 16 (median = 8)
- MIPT: 14, 9, 10, 16, 2, 5, 7
11. Tokyo (Medal: 50%)
- CF max: 2762, 2694, 2424 (agg = 2903)
- Open Cup: 29, 5, 10, 12, 14, 29 (median = 13)
- MIPT: 11, 10, 6, 8, 15, 6, 6
- Barcelona: 1, 1, 1, 2, 3, 1, 1
12. SJTU (Medal: 50%)
- CF max: 2707, 2609, 2582 (agg = 2874)
- Open Cup: 26, 3, 18, failed, 21, 12, 10, 20, 26, 14 (median = 19)
- China Final: 2
- MIPT: 8, 7, 4, 10, 3, 9, 10
I won't be surprised if the following teams get a medal:
13. NTU (Medal: 45%)
- CF max: 2772, 2341, 2220 (agg = 2808)
- Open Cup: 11, 15, 21, 10, 2 (median = 11)
14. Waterloo (Medal: 45%)
- CF max: 2925, 2908, 2703 (agg = 3100)
- Open Cup: Equivalent to 12.5 in NAIPC
- Barcelona: 3, 2, 4, 1, 1, 3, 2
15. Perm SU (Medal: 40%)
- CF max: 3037, 2850, 2578 (agg = 3127)
- Open Cup: 6, 18, failed, 3, failed, 9, 18, 7, 24, 15, 14, 16, 16, 7, 21, 16, 21, 17 (median = 16)
- Petrozavodsk: 8, 12, 10, 14, 10, 10, 2, 6, 6
- MIPT: 4, 8, 11, 5, 20, 7, 9
16. Peking (Medal: 40%)
- CF max: 2920, 2566, 2338 (agg = 2965)
- Open Cup: 21, 3 (median = 12)
- China Final: 6
17. Helsinki (Medal: 35%)
- CF max: 2721, 2280, 1516 (agg = 2745)
- Open Cup: 15, failed, 9, failed, 16, 4, 17, 11, 30, 18, 2, failed, 8 (median = 16)
- Petrozavodsk: 3, 26, 25, 11, 11, 7, 10, 2, 9
- MIPT: 10, 16, 14, 6, 23, 17, 3
18. BSUIR (Medal: 30%)
- CF max: 2825, 2625, 2466 (agg = 2943)
- MIPT: 7, 13, 8, 11, 9, 13, 12
===
- Expected win of top 7 = 0.95
- Expected gold of top 10 = 3.75
- Expected medal of top 18 = 11.05
And I guess Tokyo Institute of Technology will be around 25th, Keio will be around 40th.
Is there any mirror contest for ICPC World Finals?
IMHO, one of the best predictions, which I see for this year's final. Btw, high probability that Perm SU and SJTU reach top 12.
Auto comment: topic has been updated by rng_58 (previous revision, new revision, compare).
How do you calculate the probability? :D
Btw, I'm very surprised when I see SpbSU ranked relatively low in this prediction and many other predictions:
So IMHO this team has very high chance of winning WF this year. Is there any reason you put them at 4th? Is it because of performance on OpenCup and Petrozavodsk?
Probabilities are just my intuition.
CF rating is a good indicator, but CF is an individual contest and uses different format. Previous ICPC and NEERC are important, but they are only two contests. When we have the results of 28(!) ICPC-style contests like SPb ITMO or SPb SU, the prediction can be quite accurate.
Anyway, if we include NEERC, ITMO vs SU = 17 vs 11, so they are quite close.
When we don't have much data like Seoul, I mainly depended on ratings.
Actually just one month ago there was a pre-final workshop in Moscow, I guess the result will also be helpful: Moscow Pre-final Workshop
Yes, I added and modified my prediction a bit.
How do you compute the agg(regations?) of the CF max ratings of team members?
I can't check right now but I assumed it was the way cf does team ratings? http://mirror.codeforces.com/blog/entry/16986
Auto comment: topic has been updated by rng_58 (previous revision, new revision, compare).
Auto comment: topic has been updated by rng_58 (previous revision, new revision, compare).