I wanted to take some time to take a “big picture” view of each of the leagues as we crest the halfway point and into the later parts of the Summer Season. I’ll be breaking down the LCK today.

Check out the LPL Mid-Season Macro Trends Breakdown here.


League Total Matches Total Games Favorites Favorite Spreads (-1.5 maps) Underdogs Underdog Spreads

(+1.5 maps)

UND 2-0 FAV 2-1
LCK 50 125 29 14 21 36 11 15

 

Favorites are 29-21 outright in the LCK so far this season through five weeks. This is obviously much closer to even than the lopsided LPL where favorites were 52-24 outright. It also makes some sense given the overall parity in the league at the moment with some of the top teams taking a slight step backward and just about everyone else besides DRX taking a huge step forward in overall quality. Half of the series have gone to a third game. Perhaps the most surprising trend here is that of the 21 underdog wins, more than half (11) have been 2-0 sweeps.

The 25 underdog wins are accounted for by the following:

Afreeca (5), Liiv Sandbox (4), Brion (3), Nongshim (3), KT Rolster (2), T1 (1), DRX (1), DWG (1, lol), HLE (1)

The 11 underdog 2-0 sweeps are accounted for by the following:

Brion (2), AF (2), Liiv Sandbox (2), Afreeca (2), Nongshim (2), DWG (1)

My pre-season evaluation of the LCK was that the entire league outside of the elite three (maybe four) were just playing horrible League of Legends, especially for the LCK and that wasn’t something I expected to continue. As I predicted the entire table has taken a noticeable step forward (besides DRX, more on them in a bit) and even with the top teams taking very slight steps back, I think this is more a case of genuine parity than anything else. A lot of the younger rosters are growing into themselves, a lot of them are now running, in my opinion, better lineups and ones that they should have been running in Spring and it’s paying dividends.

There really aren’t that many true “upsets” that I’ve seen unless you want to counter DAMWON’s overall underperformance on the season.

Calling it a stark contrast would be an understatement when comparing the overall picture of the LCK to that of the LPL. It’s a dogs paradise in the LCK. Below is a table measuring the results of a one unit wager on every LCK match in the following markets.  “Blind” betting a “trend” is a stupid idea most of the time but it is interesting to see the overall picture just in terms of shopping around for value to see if things are going to adjust or not. With 11 underdog sweeps accounting for more than half of the 21 underdog outright wins, it’s not surprise that the underdog sweep has been an absurdly high ROI on the season.

As of 7/13 Every FAV Spread (-1.5) as % Every FAV Moneyline as % Every UND Moneyline as % Every UND Spread (+1.5) as % Every UND -1.5 as %
LCK -44.95 -89.90 -14.77 -29.55 -5.88 -11.77 -26.40 -52.81 +14.65 +29.30

 

How can we apply this information? Well let’s compare it to some of the derivative markets and then we’ll compare the results to the performance ratings we’ve seen so far through the use of the model.

LCK Kill Spread Winner? Kill Total Winner? Time Total Winner? FAV Team Total UND Team Total Dragons 4.5 Winner? Towers 11.5 Winner? First Game Kill Spread First Game Spread >= 6.5 First Game Spread >=8.5 First game kill total First Game time total
Over / Fav 55 56 63 58 68 61 56 18 18 1 15 29
Under / Dog 70 69 62 67 57 64 68 32 36 2 35 21
Average 5.10 23.36 32.32 13.52 9.32
Total Games
125

 

A few things stick out here. First game unders and underdog spreads are absolutely destroying it in the LCK this season especially bigger kill spreads. A vast majority of game ones are going OVER the time total, UNDER the kill total and underdogs are covering in the vast majority of them win or lose. 35 out of 50 game ones have gone under the kill total. Interestingly, tower totals have remained relatively low in the LCK even with longer game times on average.

None of this is particularly surprising given the propensity of underdogs to cover in the LCK historically. It’s a lot like in the NFL when you have low game total and a high spread, very little margin for error for the favorites. Low kill totals, mid to high spreads, makes sense.

Below is the breakdown of the distribution of how series overall have turned out with the kill total results with different iterations (O is over, U is under, the bottom row is the total):

Totals U then O Totals UU Totals OO Totals O then U
9 6 5 5
6 6 2 3
4 4 0 0
19 16 7 8

 

As expected the least commonly seen opening to a series is over in game one regardless of what follows. In short, game one unders in the LCK folks.

 


LCK After Week 5
Team Power # Rank
T1 0.9492695746 1
DWG 0.5282728023 2
GEG 0.4822390039 3
AF 0.4720234594 4
NS 0.0259947155 5
KT 0.000242782389 6
HLE -0.1718169871 7
LSB -0.4745182355 8
BRO -0.4852768231 9
DRX -1.326430292 10

 

This is the model’s power ratings up to and including week five. Keep in mind the model uses a composite blend of trending and season long performance across a variety of metrics.

Below are your current standings:

LCK 2021 Summer Standings
Team Series Games Str
1 ⁠⁠Gen.G 8 – 2 80% 16 – 9 64% +7 1W
2 ⁠⁠DWG KIA 7 – 3 70% 16 – 8 67% +8 3W
3 ⁠⁠Nongshim RedForce 7 – 3 70% 16 – 10 62% +6 2W
4 ⁠⁠Afreeca Freecs 6 – 4 60% 13 – 12 52% +1 1W
5 ⁠⁠T1 5 – 5 50% 12 – 11 52% +1 1L
6 ⁠⁠Liiv SANDBOX 5 – 5 50% 13 – 13 50% 0 2L
7 ⁠⁠KT Rolster 4 – 6 40% 14 – 13 52% +1 1W
8 ⁠⁠Hanwha Life Esports 4 – 6 40% 9 – 15 38% -6 1L
9 ⁠⁠Fredit BRION 3 – 7 30% 11 – 15 42% -4 4L
10 ⁠⁠DRX 1 – 9 10% 5 – 19 21% -14 1L

(from Leaguepedia)

 

In a league with as much parity as the LCK has there’s a lot of interesting comparisons between the model rating and the standings currently. Let’s take a look at some of the biggest divergences:

  • T1 are currently sitting in 5th place with a 5-5 match, 12-11 game record but rank 1st overall in the model. Why is the model so bullish? T1 rank first or second in the league in the following metrics; Gold differentials at 10, 15, AND 20, post-20 minute gold differential per minute, gold per minute, gold differential per minute, gold percent rating (GPR), kill agnostic gold per minute, kill agnostic gold differential per minute, gold per minute in losses. That’s fairly impressive. The problem that T1 is having is that they’re struggling with objective control where their composite objective control rating is 7th. This is backed up by the film to some extent. They’ve had a few barons and dragons stolen which is bad luck but Keria and the team overall have not been thorough enough in clearing vision and directing fights around neutrals. I expect T1 to be able to fix this issue especially if the game trends away from these more high variance, multiple melee setups.
  • GenG were soaring but have picked up a few losses recently to T1 and DAMWON, classic Gen.G struggling against the other top dogs right? Gen.G are still very good but unlike 2020, have been one of the weaker early game teams in the LCK with below league average performance in differentials and overall economy in the first twenty minutes. Where they make up for it is having the far and away best post-twenty economy and excellent objective control (3rd). For awhile Gen.G were miscast as a scaling team, they weren’t, but now they are. I expect they’ll be fine but they’ll need to shore up their early game.
  • Nongshim and Afreeca are the other big divergences when comparing their game record to their overall rating. Afreeca have been the better team overall despite not winning as many games. Nongshim have definitely stolen a few games off the back of some heroic individual performances and while I think this team is significantly improved, I don’t think that’s a reliable way to have continued, repeatable success. If the fundamentals are lacking that will eventually bite you.
  • DRX are the only truly bad team in the LCK now that Hanwha Life seem to at least somewhat be getting themselves in gear. This is largely just a square peg round hole situation. DRX are still trying to play Spring League of Legends and the game is significantly different now. They’ll probably remain bad without some adaptation. The new bottom lane has been an improvement but they need an overall philosophy change. Pressure on cvMax at this point.

I believe in accountability. For years I’ve tracked all of my picks publicly. 2021’s selections will be via this spreadsheet but it isn’t updated until AFTER the games have started. The Esports Department subscribers get the first look.

Check out The Gold Card Podcast and you can find me on Twitter @GelatiLOL

(all lines from Nitrogen unless noted otherwise)

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