45% WIN RATE IN 7.33-- THIS INVOKER WILL GIVE YOU THE SOLUTION - Dota 2 Invoker 13:42 DELETED ALCHEMIST WITH THIS COMBO - EPIC INBOSSIK INVOKER - Dota 2 Invoker 14:27 16MINS VYSE + DAGON BUILD - EPIC INVOKER vs VOID SPIRIT MID - Dota 2 Invoker ...
RegionMatchesWin Rate Europe West 4,651 53.49% Europe East 843 51.96% Other 324 48.46% FriendsThis Week FriendMatchesWin Rate No recent matches with friends AliasesSTEAM_0:1:49802048 NameLast Used professional win ... 2 months ago pma 3 months ago pudge *** 6 months ago dd enjoy...
【Dota 2 Invoker】RAMPAGEE!! EPIC INVOKER vs KUNKKA MID oak_lander 1530 3 SUNSTRIKE GOD!! GRANDMASTER INVOKER DESTROYS RIKI WITH THIS COMBO | Dota 2 Invok oak_lander 231 0 MAX LEVEL 30 INVOKER EPIC MEGA CREEP COMEBACK GAME | Dota 2 Invoker oak_lander 622 7 10K MMR - KIYOTAKA INV...
然后我们一开始在立项的时候把这个称之为“胜率预测器Win Rate Prediction Tool”,所以下文基本上会以胜率预测器或者wrpt来代指项目。 因为文章有点长,准备分两篇发,在这一部分中我会提到: 代码 结果 简单地回顾下制作过程 改进模型过程中的几个比较关键的点 代码 代码见:https://github.com/vpus/dota2-win-...
Win RateThis Week more Dec 08Dec 10Dec 12Dec 1448%50%52%54% Pick RateThis Week more Dec 08Dec 10Dec 12Dec 140%10%20% Meta TrendsThis Week more 0%60% Talent Usage more 25 +1.4% +2 Healing Ward Hits to Kill +1s Omnislash Duration 20 -3s Blade Fury Cooldown +4.2% +50% Blade...
Crusader (1,540 – 2,156 MMR) Crusader is the tier where players start studying the game. You’ll notice more people with meta picks and up-to-date item guides, which are vital aspects that can boost someone’s win rate. The key to moving forward from Crusader to Archon is knowing wh...
50% win rate - but if you get pulled into one of these games, you'll know and remember it since it'swayworse than your normal matches. So what's happening in this screenshot here? You're a very high ranked duo stack, searching on a lower population server, in unranked. We're ...
我们从这个悲伤的故事中走出来,把逻辑放到DOTA2中就是——如果英雄A确实和英雄B比较搭(在一起时战斗力爆表),则需要同时满足: 英雄A搭配英雄B的胜率 > 英雄A没有和英雄B搭配时的胜率,即:A_with_B_win_rate > A_not_with_B_win_rate(需要通过chi-square检验) ...
profession_df['win_rate'] = profession_df['profession_win']/profession_df['select_num'] profession_df.to_csv(time.strftime('%Y-%m-%d',time.localtime(time.time()))+'.csv') 爬到的数据到手,数据的样本有点偏少,但是也能大致反应高分段天梯的趋势,挑选次数多,胜率又高的英雄,应该是值得练一手...
win_cnt, cnt, togather_win_cnt, togather_cnt = query_win_lose(all_matches, MY_ID, TM_ID) print("---all---") print("cnt = ", cnt) print("win_cnt = ", win_cnt) print("winning rate = ", float(win_cnt) / cnt) print("---togather---") print("togather_cnt...