General Information
As of February 8, 2024
r/sportsanalytics
Sports Analytics: for nerds who love sports
en
We're a subreddit for quantitative nerds who love sports. Our goal is to showcase and discuss interesting links regarding the use of data and analytics in sports. Think of us like /r/sabermetrics, but not specific to baseball. We have a preference for articles that show their work, especially if they include links to their source data.
Welcome to /r/sportsanalytics: a subreddit for quantitative nerds who love sports.
Guidelines
Submissions should seek to understand sports through the use of objective, empirical analysis. Specifically, submissions should focus on understanding player/team performance or game strategy through ...
9,458
February 3, 2011
public
all_ads
Total Submissions
2,712
Total Comments
5,160
Earliest Submission
February 3, 2011
Earliest Comment
March 5, 2011
Metrics
Activity Over Time
Submission Flags
Comment Flags
Submission Score Distribution
Comment Score Distribution
Title Length
Submission Text Length
Comments per Submission
Most Distinctive Words
Rank↕ | Word↕ | Occurrences in Subreddit | Total Occurrences | Rate in Subreddit (per 1M words) | Rate in Reddit (per 1M words) | Ratio (Sub Rate / Reddit Rate) |
|---|---|---|---|---|---|---|
| #1 | 137 | 58,116 | 1351.3 | 0.5 | 2788.51 | |
| #2 | 121 | 83,660 | 1193.5 | 0.7 | 1710.86 | |
| #3 | 51 | 93,860 | 503.0 | 0.8 | 642.74 | |
| #4 | 294 | 589,809 | 2899.9 | 4.9 | 589.64 | |
| #5 | 32 | 79,941 | 315.6 | 0.7 | 473.51 | |
| #6 | 49 | 168,427 | 483.3 | 1.4 | 344.14 | |
| #7 | 81 | 318,836 | 799.0 | 2.7 | 300.51 | |
| #8 | 128 | 595,325 | 1262.6 | 5.0 | 254.33 | |
| #9 | 35 | 169,618 | 345.2 | 1.4 | 244.09 | |
| #10 | 54 | 270,374 | 532.6 | 2.3 | 236.25 | |
| #11 | 39 | 298,187 | 384.7 | 2.5 | 154.71 | |
| #12 | 46 | 374,163 | 453.7 | 3.1 | 145.43 | |
| #13 | 199 | 2,046,451 | 1962.9 | 17.1 | 115.03 | |
| #14 | 60 | 666,273 | 591.8 | 5.6 | 106.52 | |
| #15 | 55 | 614,132 | 542.5 | 5.1 | 105.94 | |
| #16 | 50 | 647,581 | 493.2 | 5.4 | 91.33 | |
| #17 | 45 | 591,584 | 443.9 | 4.9 | 89.98 | |
| #18 | 33 | 439,537 | 325.5 | 3.7 | 88.81 | |
| #19 | 30 | 399,805 | 295.9 | 3.3 | 88.76 | |
| #20 | 429 | 5,893,635 | 4231.5 | 49.1 | 86.10 | |
| #21 | 91 | 1,405,766 | 897.6 | 11.7 | 76.57 | |
| #22 | 203 | 3,150,144 | 2002.3 | 26.3 | 76.23 | |
| #23 | 64 | 1,029,628 | 631.3 | 8.6 | 73.53 | |
| #24 | 47 | 770,389 | 463.6 | 6.4 | 72.17 | |
| #25 | 49 | 818,075 | 483.3 | 6.8 | 70.85 | |
| #26 | 39 | 651,547 | 384.7 | 5.4 | 70.81 | |
| #27 | 762 | 14,091,265 | 7516.1 | 117.5 | 63.97 | |
| #28 | 99 | 1,884,719 | 976.5 | 15.7 | 62.14 | |
| #29 | 32 | 639,367 | 315.6 | 5.3 | 59.20 | |
| #30 | 94 | 1,933,359 | 927.2 | 16.1 | 57.51 | |
| #31 | 161 | 3,389,200 | 1588.1 | 28.3 | 56.19 | |
| #32 | 50 | 1,065,004 | 493.2 | 8.9 | 55.53 | |
| #33 | 67 | 1,429,297 | 660.9 | 11.9 | 55.45 | |
| #34 | 48 | 1,033,734 | 473.5 | 8.6 | 54.93 | |
| #35 | 42 | 963,502 | 414.3 | 8.0 | 51.56 | |
| #36 | 50 | 1,160,992 | 493.2 | 9.7 | 50.94 | |
| #37 | 226 | 5,300,217 | 2229.2 | 44.2 | 50.44 | |
| #38 | 77 | 1,818,324 | 759.5 | 15.2 | 50.09 | |
| #39 | 53 | 1,360,694 | 522.8 | 11.3 | 46.07 | |
| #40 | 52 | 1,350,785 | 512.9 | 11.3 | 45.54 | |
| #41 | 60 | 1,611,648 | 591.8 | 13.4 | 44.04 | |
| #42 | 35 | 951,247 | 345.2 | 7.9 | 43.52 | |
| #43 | 177 | 4,929,300 | 1745.9 | 41.1 | 42.48 | |
| #44 | 39 | 1,104,217 | 384.7 | 9.2 | 41.78 | |
| #45 | 55 | 1,573,800 | 542.5 | 13.1 | 41.34 | |
| #46 | 48 | 1,458,417 | 473.5 | 12.2 | 38.93 | |
| #47 | 40 | 1,324,672 | 394.5 | 11.0 | 35.72 | |
| #48 | 37 | 1,235,316 | 365.0 | 10.3 | 35.43 | |
| #49 | 43 | 1,456,475 | 424.1 | 12.1 | 34.92 | |
| #50 | 112 | 3,849,247 | 1104.7 | 32.1 | 34.42 |