Introduction

This primary goal of this project is to calculate Regularized Adjusted Plus-Minus (RAPM)—an “advanced statistic”—for NBA players. The calculated values can be found in the set of metrics_join CSVs in the project’s repository.

I plan to write about this project in more detail on my blog. so I encourage the reader to read more about it there.

Usage

If you were to fork this project and try to run it from scratch, below shows the required order of function calls.

First, download all of the data needed.

# pre-process ----
# Note that `overwrite = FALSE` is the default, but setting it explciitly here to remind
# the user that it is an option.
# This goes to the
download_pbp_raw_files(overwrite = FALSE)

download_nbastatr(overwrite = FALSE)
download_rpm_espn(overwrite = FALSE)
download_rapm_sz(overwrite = FALSE)

Next, run the “main” function. This is what is run with the command-line interface (CLI) that also comes with the project.

# This reads from the config.yml files.
auto_main()

Highlights

Below is a visual comparison of various RAPM-related metrics, either calculated in this project (i.e. calc) or retrieved from an external source.

The data behind this visual

y	apm_calc	bpm_nbastatr	dbpm_nbastatr	drapm_calc	drapm_sz	drpm_espn	obpm_nbastatr	orapm_calc	orapm_sz	orpm_espn	pm_nbastatr	rapm_both_calc	rapm_calc	rapm_sz	rpm_espn
apm_calc	NA	0.0857897	0.0068202	0.3504192	0.1118109	0.0059843	0.0863602	0.4191907	0.0972412	0.0633819	0.1194202	0.5170582	0.6750558	0.2135919	0.0727325
bpm_nbastatr	0.0857897	NA	0.2852047	0.0273031	0.0027746	0.0471514	0.8274349	0.1482843	0.0453781	0.1901469	0.0437862	0.1743086	0.1600988	0.0418785	0.2560962
dbpm_nbastatr	0.0068202	0.2852047	NA	0.0912274	0.0503027	0.2727653	0.0168123	-0.0024059	-0.0017948	-0.0018229	0.0191676	0.0321596	0.0191713	0.0189409	0.1234330
drapm_calc	0.3504192	0.0273031	0.0912274	NA	0.3322217	0.0765407	-0.0020656	0.0098078	-0.0003777	-0.0027973	0.1413987	0.4035084	0.3356299	0.1240432	0.0358574
drapm_sz	0.1118109	0.0027746	0.0503027	0.3322217	NA	0.1041948	-0.0009822	-0.0023232	-0.0017017	-0.0006295	0.1791320	0.1442801	0.0756311	0.4384602	0.0256227
drpm_espn	0.0059843	0.0471514	0.2727653	0.0765407	0.1041948	NA	-0.0008774	-0.0029342	-0.0026649	0.0064440	0.0491640	0.0298905	0.0175993	0.0421981	0.3028806
obpm_nbastatr	0.0863602	0.8274349	0.0168123	-0.0020656	-0.0009822	-0.0008774	NA	0.2368059	0.0650393	0.2843836	0.0300633	0.1443483	0.1512988	0.0278430	0.1757929
orapm_calc	0.4191907	0.1482843	-0.0024059	0.0098078	-0.0023232	-0.0029342	0.2368059	NA	0.3812504	0.1694076	0.2074359	0.4420484	0.7619807	0.2037157	0.1178648
orapm_sz	0.0972412	0.0453781	-0.0017948	-0.0003777	-0.0017017	-0.0026649	0.0650393	0.3812504	NA	0.1361238	0.3027395	0.1785147	0.2277643	0.5434344	0.0906094
orpm_espn	0.0633819	0.1901469	-0.0018229	-0.0027973	-0.0006295	0.0064440	0.2843836	0.1694076	0.1361238	NA	0.1209535	0.1041428	0.1121011	0.0596036	0.6037412
pm_nbastatr	0.1194202	0.0437862	0.0191676	0.1413987	0.1791320	0.0491640	0.0300633	0.2074359	0.3027395	0.1209535	NA	0.3326310	0.3124833	0.4888706	0.1893420
rapm_both_calc	0.5170582	0.1743086	0.0321596	0.4035084	0.1442801	0.0298905	0.1443483	0.4420484	0.1785147	0.1041428	0.3326310	NA	0.7345316	0.3308535	0.1489425
rapm_calc	0.6750558	0.1600988	0.0191713	0.3356299	0.0756311	0.0175993	0.1512988	0.7619807	0.2277643	0.1121011	0.3124833	0.7345316	NA	0.2980069	0.1374234
rapm_sz	0.2135919	0.0418785	0.0189409	0.1240432	0.4384602	0.0421981	0.0278430	0.2037157	0.5434344	0.0596036	0.4888706	0.3308535	0.2980069	NA	0.1136859
rpm_espn	0.0727325	0.2560962	0.1234330	0.0358574	0.0256227	0.3028806	0.1757929	0.1178648	0.0906094	0.6037412	0.1893420	0.1489425	0.1374234	0.1136859	NA

Top 20 RAPM players for 2017 (according to my calculations, which are probably off 😆)

name	slug	rank	drapm	orapm	rapm
Dante Exum	UTA	1	2.69	3.43	6.12
Stephen Curry	GSW	2	-0.15	5.04	4.90
Marcus Georges-Hunt		3	-1.07	5.79	4.71
Jordan Bell	GSW	4	1.00	3.39	4.38
Brandan Wright		5	2.66	0.99	3.66
OG Anunoby	TOR	6	1.30	2.33	3.63
Iman Shumpert	SAC	7	2.78	0.79	3.57
Chris Paul	HOU	8	0.32	3.05	3.37
Nene	HOU	9	1.04	2.16	3.20
Mike Conley	MEM	10	2.19	0.94	3.13
Eric Gordon	HOU	11	1.04	2.07	3.11
Torrey Craig	DEN	12	0.83	2.26	3.09
Lucas Nogueira		13	1.14	1.90	3.04
PJ Tucker	HOU	14	0.76	2.22	2.99
Robert Covington	MIN	15	1.09	1.88	2.97
Zaza Pachulia	DET	16	0.31	2.57	2.88
Thabo Sefolosha	UTA	17	1.02	1.83	2.85
Ersan Ilyasova	MIL	18	1.02	1.57	2.59
Joel Embiid	PHI	19	0.97	1.49	2.46
Ekpe Udoh	UTA	20	1.00	1.46	2.46

2017 offensive RAPM coefficients for top 10 players as a function of cross-validated (CV) log-lambda values

2017 defensive RAPM coefficients for top 10 players

Ridge regression CV lambda penalties for 2017 offensive RAPM

Ridge regression CV lambda penalties for 2017 defensive RAPM