A Season with LearnedLeague

I recently finished playing in my first (and probably only, the reason for which I’ll explain shortly later) season of LearnedLeague, an online trivia league. I’d say it was a fun experience, and that the ideas behind how competition in LearnedLeague works are generally good ideas.

Each round (of which there are 25 in a season, at least in the one I participated in) consists of a head-to-head match between two league players, that involves answering trivia questions (called “offense”), and assigning numbers of points each question is worth for your opponent (called “defense”), for which one is allowed to consult their history to know what one’s opponent tends to be good at.

And this gets to why I don’t think I’ll be back for another season. LearnedLeague has failed to deviate from a problem I find in most trivia competitions: an excessive favoring of generalists. Frankly, there are four categories of LearnedLeague trivia (Film, Lifestyle, Pop Music, and Television) than not only am I terrible at but also I honestly have less than zero interest in getting better at (really, four and half, given the Games/Sport category; it’s a really easy exercise for the reader to figure out which half of that I don’t care about). But there are categories of trivia I am definitely extremely interested in. Overall, my trivia knowledge is terribly category-polar, and this makes me ridiculously easy to defend against. As much as I like the assigning-points-for-opponent mechanic, the resulting effects of the such for highly non-generalist people like me make it something I’m not willing to give money for. A second factor lies in excessive references to alcoholic drinks, which many may know I find elevated discomfort in. There’s quite a few questions for which it looks like the writer specifically wanted to force an association with alcohol. Yes, it turns out unfortunately trivia is often associated with bars. *Sigh*.

Anyway, my category stats:

ll_categories

Below I’ll make some notes on specific items in some categories.

Some of these questions have images that are part of the item when you click ‘Click here’. I’m too lazy to copy those over, so I’ll leave it to your imagination what those items were.

Art

art

MD15Q3 was the least-correctly-answered item in the entire season, with only 5% answering correctly.

MD06Q2 was a guess. They all looked like portraits. Might as well guess that they were of the self variety.

Business/Economics

bus_econ

I only got MD13Q1 because of knowing where Qaanaaq is and knowing there’s a military base named Thule nearby, and thus just guessing “Thule” off of only this information, possibly the most distant answer derivation I’ve underwent this entire season. Does this count as love towards Sweden via proxy?

I entered “Hand of God” instead of “Invisible Hand” for MH08Q5. Oops.

Current Events

curr_events

I’m fairly ashamed of having not been able to name the new UN Secretary-General. Apparently, neither could most of LearnedLeague, so shame on everyone else too.

Games/Sport

games_sport

MD12Q5: Booo Othello. I can’t believe the world accepted the game of Reversi getting a second name.

What is sportsball.

Geography

geography

Apparently the most frequently incorrectly guessed answer to MD20Q2 was “Washington”. I guess that’s what “Bellevue” tipped people off to?

I was not actually sure of the answer to MD12Q6; I based my guess off of understanding the Central American isthmus as gradually less inhabitable as one moves south and east.

American History

amer_hist

I don’t really have many comments to make here.

World History

world_hist

I really should’ve gotten MD24Q5, but didn’t answer “Peloponnesian League” because of the inclusion of Corinth, which I recalled as not-all-that-Peloponnesian, although maybe I should’ve still considered the isthmus Pelopennesian. I guessed “Dorian League”.

For MD15Q4, I knew where relatively chronologically the House of Saxe-Coburg and Gotha was; I just couldn’t exactly remember where it was delimited and wasn’t exactly sure which monarchs came between Victoria and Edward $LARGE_NUM. I ended up deciding I had the best chances with guessing Victoria, which it turns out was too early.

For MD12Q3, I made the rather hilarious-in-retrospect mistake of calling the Ostrogoths the “Orthogoths”. Herpity derp.

MD07Q5 was the most-correctly-answered item in the entire season, with 88% answering correctly. Fortunately, I was in the 88% for this case.

I was wondering whether MD01Q2 wanted the real (legal) name of Kim Il-Sung, since that is not it, but ended up deciding they probably just want “Kim Il-Sung” for the purposes of the question. It turns out that was a good assumption.

Language

language

I consider the FANBOYS question a bad question.

MD02Q4 was an item I really should’ve gotten, but I mind-blanked a bit much and put “al-“.

Literature

literature

Maybe if I thought a little harder on MD18Q4 I would’ve gotten it.

Math

math

*snicker*

MD08Q1 was the second-most-correctly-answered item in the entire season, with 87% answering correctly.

Classical Music

class_music

MD19Q4 was the second-least-correctly-answered item in the entire season, with only 14% answering correctly.

The Classical Music section consists of an excess of…I guess I’ll call it “applied” music and way not enough “pure” music, grump, grump. I’m saying “applied”, I guess because terms like “incidental” and “operatic” don’t actually capture the set I’m trying to describe.

Science

science

I was actually quite surprised with how long it took me to recall what Newton’s Second Law was. It turned out my physical knowledge had progressed to a state where I only know if I’m supposed to know things. Fortunately, I did eventually remember the Law. I wonder if I would’ve forgotten it if I hadn’t taken an olympiad qualification test whose name is the equation of the Law.

Anyway, that’s all; ’twas a fun season. I’m going to stay around for some MiniLeagues, but then vanish from LearnedLeague. I did refer a friend to LearnedLeague, though, so maybe he will stay.

Pokémon Go: Most Represented Species by CP

I decided to add up the CPs of each individual for each species as a measure of how represented the species is in my set of Pokémon in Pokémon Go. The chart of the 27 most represented species is below.

pokemon_cp_distr

The total CP of all Pokémon I have is about 353000, so Jolteon represents about 5% of all CP in my Pokémon. I was quite surprised to find out how close the CP shares of my top three species (Jolteon, Vaporeon, and Pidgeot) were.

Meta-Bingo

It’s sometimes fun to make one’s own bingo board for an event and to compete with others’ boards for a bingo. This can often be seen when, for instance, a large set of people watch a debate and make bingo boards for terms they think will certainly or near-certainly pop up during debate.

Here, I propose a couple more interactive games when one has large groups of people.

Cooperative Meta-Bingo

Get a group of n² or (2n-1)²-1 people, for integer n>1 (the latter case corresponds to boards with FREE bingo spaces in the center of the board). Have each person individually design a bingo board for an event, then bring the boards together to strategize placing the boards into the spaces of a bingo board of bingo boards. The Cooperative Meta-Bingo is a success as soon as five bingo boards in the same row, column, or diagonal all reach bingo. Alternatively, have each player fill out the board individually to make the game a competition of who is paying attention. In yet another alternative, show all bingo boards to all players but have each player make their own meta-bingo board out of some permutation of the bingo boards; the player who reaches meta-bingo first wins.

Thinkalike Meta-Bingo

Get a group of people as in the case with Cooperative Meta-Bingo. Have each person individually design a bingo board for an event, then look at the boards. Call the term in a position in a bingo board that corresponds to the position of that bingo board in the meta-bingo board a representative term. The Thinkalike Meta-Bingo is a success if the boards can be arranged such that a row, column, or diagonal of the meta-bingo board has bingo boards all with the same representative terms. For an added challenge, require multiple terms. For a competitive version, give everyone all the boards, and see who is the first to build a correct Thinkalike Meta-Bingo.

Pokémon Go: Stats Upon Level 33

This post is in the format of and an extension of my Level 30 stats post from three months ago.

Around 0100 Eastern Time today, I evolved a Pidgey to reach 3750334 XP, thus levelling up to Level 33.

I started playing Pokémon Go on August 26 last year. Using this baseline, this is when my level-ups occurred:

Day 87: Level 29
Day 92: Level 30
Day 102: Level 31
Day 138: Level 32
Day 181: Level 33

My buddy is currently a Lapras. My buddy has previously been a Dratini, a Bellsprout, and two different Charmanders.

My Pokémon are currently at 383/400.
My eggs are currently at 9/9.
My items are currently at 308/350, specifically:
3x Super Potion
68x Hyper Potion
87x Max Potion
40x Max Revive
2x Incense
11x Great Ball
20x Ultra Ball
1x Lure Module
16x Razz Berry
5x Nanab Berry
39x Pinap Berry
Camera
Egg Incubator ∞
1x Metal Coat
1x Dragon Scale
1x Up-Grade

(I have still only used Max Potions where Hyper Potions would also work. I now have several Pokémon with over 200 HP, but the situation still hasn’t arisen for the two to have different effects from singular use yet.)

(At some point since the Level 30 stats update, I actually accumulated 272=0xGG max potions, and then decided I’m done hoarding them and letting them hog space.)

(Parentheticals in this section show change from last update. For comparison, the XP change from the previous update is +87.5%.)

Pokédex: 146 (+33)
Pokémon Caught: 8794 (+88.3%)
Evolutions: 1358 (+85.0%)
Pokéstop Visits: 11593 (+69.9%)
Distance Walked: 742.9 (+73.3%)
Eggs Hatched: 159 (+43.2%)
Gym Battles Won: 1305 (+35.7%)
Gym Trainings: 365 (+45.4%)

All 383 of my Pokémon are currently fully healed.

Strongest Pokémon:
Gyarados (CP 2945)
Vaporeon (CP 2766)
Vaporeon (CP 2650)
Flareon (CP 2499)
Snorlax (CP 2393)
Flareon (CP 2339)

(Strongest Pokémon at last update)
Gyarados (CP 2805)
Vaporeon (CP 2351)
Vaporeon (CP 2288)
Flareon (CP 2177)
Vaporeon (CP 2158)
Vaporeon (CP 2138)

Pokémon Caught by Type
(Parentheticals in this section show change from last update. For comparison, the XP change from the previous update is +87.5%, and the Pokémon caught change from the previous update is +88.3%.)
Normal: 6510 (+102.2%)
Flying: 4059 (+104.2%)
Poison: 1922 (+70.8%)
Bug: 1547 (+69.4%)
Water: 896 (+56.1%)
Psychic: 327 (+52.1%)
Ghost: 202 (+32.0%)
Electric: 169 (+116.7%)
Fairy: 157 (+241.3%)
Ground: 155 (+40.9%)
Grass: 109 (+73.0%)
Steel: 92 (+130.0%)
Fire: 86 (+100.0%)
Rock: 49 (+88.5%)
Ice: 43 (+79.2%)
Fighting: 38 (+26.7%)
Dark: 15 (+∞%)
Dragon: 13 (+8.3%)

Continue reading “Pokémon Go: Stats Upon Level 33”

Ingress: Stats Upon Level 10

Just a few a minutes ago, I reached Level 10 in Ingress, by glyph hacking the portal ‘Sonia McGee Tree’, in the southwest of MIT’s Building 26.

One of the great aspects of Ingress as a game is that it comes with a comprehensive dashboard of statistics; I don’t even need to make one myself!

(Since leveling up, I have performed one recharge.)

180 FFAs of generals.io

The following are my placing results of the last 180 FFA games of generals.io I played, in forward chronological order (monospaced to be in a nice array)

1 6 1 1 2 1 4 1 7 1 5 5 1 1 3 7 1 6 1 1 2 2 5 4 6 2 6 6 2 2
7 1 8 1 2 7 4 1 4 1 4 1 1 1 1 1 1 1 5 1 1 1 1 1 4 5 1 1 5 1
1 1 1 1 8 1 8 1 4 7 2 1 4 1 7 2 1 5 1 3 1 1 1 1 1 1 1 8 1 1
7 4 7 1 1 1 1 4 1 1 1 1 1 1 5 1 1 1 1 1 1 1 1 1 8 1 8 4 2 3
8 1 3 1 1 6 2 1 1 2 4 6 5 1 1 1 1 1 3 2 1 1 4 1 2 2 4 1 2 4
2 1 2 3 4 8 1 4 8 8 1 5 1 2 1 1 1 2 1 2 3 1 1 1 4 1 1 1 1 5

Here’s a distribution:

1: 98
2: 21
3: 7
4: 18
5: 11
6: 7
7: 8
8: 10

As of now (at the end of this sequence), I’m ranked 22nd in FFA. At peak during this sequence, I was ranked 4th.

My favorite game in the batch? It’d have to be

http://generals.io/replays/rtUO4L28x

.

Zer(0)-(x)cost (G)amin(G)

When I first selected 0xGG to be my username for the gaming world, I intended it to represent the intersection of a piece of gaming jargon with the idea of taking things to eleven in hexadecimal. But just like ‘dzaefn’, I’ve since first use decided to reassign meaning to the handle.

I grew up with two parents that both universally condemned (video) gaming as only possibly a waste of time, and thus my childhood exposure to video games was extraordinarily limited (that is, exclusively underground). The entire corpus of games I could play are free games from the internet that I could play when parents weren’t home. Throughout my childhood, my gaming budget was zero.

And what I have decided was that I will continue this. Of course, now, I actually have money that I could decide to spend on games, but I’ve decided to carry momentum for the purpose of meaning. I will be a zero-cost gamer.

I will continue on the gaming frugality of my childhood and not spend a cent on gaming recreation, not on paid games, not on in-game purchases. I will only use what’s free. (And what I specifically mean is that I’m not precluding donating to game developers; I’m saying I won’t pay money to get something in gaming I otherwise wouldn’t get.) By doing so, I still have a vast palette of gaming options to choose from (because there are awesome-enough developers to provide that), and I want to highlight and showcase how far one could go without pouring money into a game, to seek what there is that those without the financial resources to pre-emptively get ahead still have a fighting chance on, given sufficiently well-thought-out strategic approach to the game. I will continue playing games like Pokémon Go, Ingress, and StarColony that are free but with in-app purchases, and will try to maintain competitiveness with those that pay actual money. This is my new generalized goal and stand in gaming: to attain the most that can be with the least of money.