I was re-reading some old threads and came across this post by @SndMndBdy. There is an interesting point here about how the cargo RP threshold should have a direct impact on match strategy. I was wondering if we could identify the effects of the cargo RP threshold on the cargo score distribution to test this hypothesis.
To do this, I collected all 2022 qual match results, I filtered out playoffs because there was no RP in playoff matches. I counted the quintet achieved as a 2 cargo score, to arrive at an adjusted cargo scored for red and for blue in each match. I then took those adjusted cargo scores and made a distribution of occurrences for each cargo count. Here are the raw results:
Adjusted Cargo Scored Distribution
adjusted cargo scored | occurrence count |
---|---|
0 | 524 |
1 | 457 |
2 | 530 |
3 | 620 |
4 | 736 |
5 | 795 |
6 | 812 |
7 | 915 |
8 | 973 |
9 | 987 |
10 | 999 |
11 | 1004 |
12 | 963 |
13 | 945 |
14 | 919 |
15 | 890 |
16 | 782 |
17 | 769 |
18 | 667 |
19 | 607 |
20 | 1078 |
21 | 929 |
22 | 745 |
23 | 618 |
24 | 540 |
25 | 475 |
26 | 444 |
27 | 405 |
28 | 343 |
29 | 299 |
30 | 311 |
31 | 242 |
32 | 226 |
33 | 200 |
34 | 174 |
35 | 168 |
36 | 121 |
37 | 103 |
38 | 119 |
39 | 103 |
40 | 86 |
41 | 57 |
42 | 60 |
43 | 55 |
44 | 48 |
45 | 39 |
46 | 33 |
47 | 27 |
48 | 28 |
49 | 16 |
50 | 17 |
51 | 20 |
52 | 19 |
53 | 8 |
54 | 4 |
55 | 5 |
56 | 4 |
57 | 10 |
58 | 2 |
59 | 4 |
60 | 3 |
61 | 3 |
62 | 2 |
63 | 3 |
64 | 1 |
65 | 0 |
66 | 1 |
67 | 0 |
68 | 0 |
69 | 2 |
70 | 0 |
71 | 2 |
Here are those distributions mapped out for the adjusted cargo scored range between 0 and 40:
This is really cool to see visually, it is very apparent where the RP threshold is just with a quick glance at this graph. We have some solid proof that teams do indeed target the 20 cargo count. Some of this is likely due to teams pursuing cargo more aggressively at the end of the match when the total scored cargo is below but close to 20. Also the flipside of that, teams after achieving 20 cargo likely played more conservatively, lining up for endgames with extra time to make the hangar RP more likely.
Zooming in to the 10-30 adjusted cargo range, I found a trendline to estimate what the distribution might look like without any RP bonus threshold:
Using that line, we can estimate how many additional cargo RPs were achieved this season due to strategy, here are the actual, expected, and difference between actual and expected counts:
Cargo Counts vs Linear Expectation
adjusted cargo scored | occurrence count | linear expectation | actual - expected |
---|---|---|---|
10 | 999 | 1064 | -65 |
11 | 1004 | 1028 | -24 |
12 | 963 | 992 | -29 |
13 | 945 | 955 | -10 |
14 | 919 | 919 | 0 |
15 | 890 | 883 | 7 |
16 | 782 | 847 | -65 |
17 | 769 | 811 | -42 |
18 | 667 | 775 | -108 |
19 | 607 | 739 | -132 |
20 | 1078 | 702 | 376 |
21 | 929 | 666 | 263 |
22 | 745 | 630 | 115 |
23 | 618 | 594 | 24 |
24 | 540 | 558 | -18 |
25 | 475 | 522 | -47 |
26 | 444 | 486 | -42 |
27 | 405 | 449 | -44 |
28 | 343 | 413 | -70 |
29 | 299 | 377 | -78 |
30 | 311 | 341 | -30 |
Depending on how you want to count, we can reasonably say that there were somewhere between 200 and 600 excess cargo RPs achieved this season due to strategy effects. Out of the 24096 half-matches in the dataset, this corresponds to an approximately 400/24096=1.7% rate, or roughly 3 extra RPs per event.
As a sidenote, I also found a few dozen matches in which there was a discrepancy between the implied RP award based on the match results, and the RP being actually awarded, those matches are shown here:
RP Discrepancies
event key | color | Match | match Cargo Total | cargo Bonus RP Achieved | quintet Achieved | adjusted total cargo | calculated RP achieved |
---|---|---|---|---|---|---|---|
azfl | blue | 60 | 15 | 1 | 0 | 15 | 0 |
utwv | blue | 21 | 0 | 1 | 0 | 0 | 0 |
scan | blue | 15 | 0 | 1 | 0 | 0 | 0 |
azfl | blue | 41 | 23 | 0 | 0 | 23 | 1 |
mitvc | blue | 21 | 20 | 0 | 0 | 20 | 1 |
azfl | blue | 51 | 20 | 0 | 0 | 20 | 1 |
gacol | blue | 22 | 19 | 1 | 0 | 19 | 0 |
gacol | blue | 17 | 19 | 1 | 0 | 19 | 0 |
mibel | blue | 57 | 16 | 1 | 1 | 18 | 0 |
azfl | blue | 56 | 18 | 1 | 0 | 18 | 0 |
gacol | blue | 21 | 17 | 1 | 0 | 17 | 0 |
azfl | blue | 18 | 17 | 1 | 0 | 17 | 0 |
mibel | blue | 58 | 17 | 1 | 0 | 17 | 0 |
txwac | blue | 3 | 0 | 1 | 1 | 2 | 0 |
txwac | blue | 26 | 0 | 1 | 1 | 2 | 0 |
gadal | blue | 39 | 0 | 1 | 1 | 2 | 0 |
txwac | blue | 54 | 0 | 1 | 1 | 2 | 0 |
txwac | blue | 18 | 0 | 1 | 1 | 2 | 0 |
caph | blue | 15 | 0 | 1 | 1 | 2 | 0 |
scan | blue | 4 | 0 | 1 | 0 | 0 | 0 |
va305 | blue | 3 | 0 | 1 | 0 | 0 | 0 |
scan | blue | 8 | 0 | 1 | 0 | 0 | 0 |
casf | blue | 21 | 0 | 1 | 0 | 0 | 0 |
inkok | blue | 5 | 0 | 1 | 0 | 0 | 0 |
tuis3 | blue | 1 | 0 | 1 | 0 | 0 | 0 |
txwac | blue | 1 | 0 | 1 | 0 | 0 | 0 |
mxmo | blue | 33 | 0 | 1 | 0 | 0 | 0 |
txwac | blue | 67 | 0 | 1 | 0 | 0 | 0 |
txwac | blue | 10 | 0 | 1 | 0 | 0 | 0 |
mimil | blue | 31 | 0 | 1 | 0 | 0 | 0 |
txwac | blue | 31 | 0 | 1 | 0 | 0 | 0 |
azfl | red | 60 | 13 | 1 | 0 | 13 | 0 |
utwv | red | 21 | 0 | 1 | 0 | 0 | 0 |
scan | red | 15 | 0 | 1 | 0 | 0 | 0 |
mike2 | red | 38 | 17 | 1 | 0 | 17 | 0 |
azfl | red | 63 | 17 | 1 | 0 | 17 | 0 |
miwal | red | 30 | 19 | 1 | 0 | 19 | 0 |
azfl | red | 29 | 25 | 0 | 0 | 25 | 1 |
azfl | red | 49 | 19 | 1 | 0 | 19 | 0 |
gacol | red | 37 | 19 | 1 | 0 | 19 | 0 |
ausc | red | 56 | 18 | 1 | 0 | 18 | 0 |
txwac | red | 45 | 0 | 1 | 1 | 2 | 0 |
njbri | red | 10 | 0 | 1 | 0 | 0 | 0 |
txwac | red | 38 | 0 | 1 | 1 | 2 | 0 |
txwac | red | 35 | 0 | 1 | 0 | 0 | 0 |
txwac | red | 50 | 0 | 1 | 1 | 2 | 0 |
txwac | red | 48 | 0 | 1 | 1 | 2 | 0 |
scan | red | 5 | 0 | 1 | 1 | 2 | 0 |
scan | red | 14 | 0 | 1 | 0 | 0 | 0 |
txwac | red | 39 | 0 | 1 | 1 | 2 | 0 |
txwac | red | 58 | 0 | 1 | 0 | 0 | 0 |
scan | red | 9 | 0 | 1 | 0 | 0 | 0 |
txwac | red | 8 | 0 | 1 | 1 | 2 | 0 |
txwac | red | 17 | 0 | 1 | 1 | 2 | 0 |
txwac | red | 37 | 0 | 1 | 0 | 0 | 0 |
mndu | red | 17 | 0 | 1 | 0 | 0 | 0 |