I just discovered a bug in my benchmark calculation: if the player's board was not found in the list of best-five rolled out boards in the benchmarks, it was assuming an equity error of zero instead of the worst equity error in the list. So it was making those edge cases look much better than they should have, and skewing the average ERs a bit better.
Below is a table of the corrected benchmark results for the nine players in the original results, plus four new ones:
Redoing the one-variable regressions on the corrected & expanded data:
Redoing the multivariate linear regression:
The main conclusion: Contact ER mostly determines cubeless money play score. The single regression of score against Crashed ER has a relatively high R^2, but that is only because Crashed ER is highly correlated with Contact ER. When properly separated with the multivariate regression it becomes clear that Contact ER is the only measure that really matters.
Below is a table of the corrected benchmark results for the nine players in the original results, plus four new ones:
Player
|
GNUbg Contact ER
|
GNUbg Crashed ER
|
GNUgb Race ER
|
PubEval Avg Ppg
|
Benchmark 2 Avg Ppg
|
---|---|---|---|---|---|
10.5
|
11.0
|
1.01
|
-
| ||
14.0
|
12.6
|
2.08
|
0.547
|
0.131
| |
33.7
|
26.8
|
2.40
|
0.146
|
-0.282
| |
14.9
|
14.2
|
2.08
|
0.548
|
0.106
| |
14.9
|
14.2
|
2.67
|
0.550
|
0.108
| |
18.2
|
19.3
|
1.98
|
0.480
|
0.072
| |
38.3
|
41.1
|
4.70
|
0.119
|
-0.283
| |
18.7
|
19.8
|
2.01
|
0.460
|
0.069
| |
20.5
|
30.0
|
2.09
|
0.442
|
0.021
| |
21.5
|
23.7
|
5.44
|
0.432
|
0
| |
Benchmark 2 (10)
|
42.7
|
37.5
|
13.20
|
0.064
|
-0.418
|
Benchmark 2 (40)
|
26.2
|
25.9
|
5.94
|
0.330
|
-0.067
|
23.0
|
24.5
|
9.66
|
0.351
|
-0.101
| |
PubEval
|
44.1
|
49.7
|
3.54
|
0
|
-0.437
|
Redoing the one-variable regressions on the corrected & expanded data:
Metric | PubEval Ppg vs Contact ER | PubEval Ppg vs Crashed ER | PubEval Ppg vs Race ER | BM2 Ppg vs Contact ER | BM2 Ppg vs Crashed ER | BM2 Ppg vs Race ER |
---|---|---|---|---|---|---|
Slope | -0.0182 | -0.0161 | -0.0268 | -0.0189 | -0.0165 | -0.0275 |
Intercept | 0.8065 | 0.7638 | 0.4631 | 0.3969 | 0.3468 | 0.0362 |
R-Squared | 98.8% | 83.5% | 22.5% | 98.0% | 80.6% | 22.3% |
Redoing the multivariate linear regression:
Benchmark
|
Intercept
|
Contact ER Slope
|
Crashed ER Slope
|
Race ER Slope
|
R-Squared
|
---|---|---|---|---|---|
PubEval
| 0.8037 |
-0.01980
|
+0.00133
|
+0.00202
|
98.9%
|
Benchmark 2
|
0.3945
|
-0.02049
| +0.00209 |
-0.00246
|
98.4%
|
Benchmark 2 (only good players)
|
0.4102
|
-0.01756
| -0.00063 |
-0.00694
|
98.5%
|
The main conclusion: Contact ER mostly determines cubeless money play score. The single regression of score against Crashed ER has a relatively high R^2, but that is only because Crashed ER is highly correlated with Contact ER. When properly separated with the multivariate regression it becomes clear that Contact ER is the only measure that really matters.
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