Nugs Shot Quality Difference

Insights/Analysis:

• 66% of games can be predicted by shot quality difference (postive = win, negative = loss)

• Nuggets had a positive shot quality difference in 63% of games.

  • Nuggets won 76%(35) of those games, which accounts for 71% of total team wins.
  • Nuggets won 75% of games it lead shot quality difference by more than 1 percentage point.
  • Nuggets won 83% of games it lead shot quality difference by more than 2 percentage points.
  • Nuggets won all nine games it lead shot quality difference by more than 3 percentage points.

• Nuggets won 52%(14) of games they trailed in shot quality difference.

• Nuggets only won 40%(8) of games they trailed in shot quality by more than 1 percentage point.

  • Trail Blazers, Celtics, Knicks, Nets, and Wolves beat Nuggets twice (no team did it more than twice) in shot quality difference by more than 1 percentage point.
    • 50% of matchups with both Blazers and Wolves
    • 100% of matchups with Celtics, Knicks, and Nets.

library(tidyverse)
library(jsonlite)
library(janitor)
library(dplyr)
library(nbastatR)
library(reactable)
library(reactablefmtr)

pbp_url_opp <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Regular%2BSeason&EntityId=1610612743&EntityType=Opponent"

pbp_den_23_opp <- read_json(pbp_url_opp)

den_23_opp <- pbp_den_23_opp[["multi_row_table_data"]] %>%
  bind_rows() %>%
  clean_names() 
opp_sq <- den_23_opp %>%
  select(date,
         shot_quality_avg) %>%
  mutate(opp_shot_quality_avg = shot_quality_avg) %>%
  select(opp_shot_quality_avg)

rf_opp <- den_23_opp %>%
  select(date,
         at_rim_frequency) %>%
  mutate(opp_at_rim_freq = at_rim_frequency) %>%
  select(opp_at_rim_freq)

pbp_url <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Regular%2BSeason&EntityId=1610612743&EntityType=Team"

pbp_den_23 <- read_json(pbp_url)

den_23 <- pbp_den_23[["multi_row_table_data"]] %>%
  bind_rows() %>%
  clean_names()
sq <- den_23 %>%
  select(date,
         shot_quality_avg)

rf <- den_23 %>%
  select(date,
         at_rim_frequency)

sq_anal <- cbind(sq, opp_sq) %>%
  mutate( shot_qual_diff = (100*shot_quality_avg - 100*opp_shot_quality_avg) ) %>%
  mutate_at(vars(shot_qual_diff), funs(round(.,4)))

nug_23 <- game_logs(
  seasons = 2023,
  league = "NBA",
  result_types = "team",
  season_types = "Regular Season"
) %>%
  filter(nameTeam == "Denver Nuggets")

## Acquiring NBA basic team game logs for the 2022-23 Regular Season

nugs_wl <- nug_23 %>%
  select(outcomeGame,
         slugOpponent)

cbind(sq_anal, nugs_wl) %>%
  select(date,
         shot_quality_avg,
         opp_shot_quality_avg,
         shot_qual_diff,
         outcomeGame,
         slugOpponent) %>%
  mutate( 'Team SQ' = shot_quality_avg,
          'Opp SQ' = opp_shot_quality_avg,
          'SQ Diff' = shot_qual_diff,
          Outcome = outcomeGame,
          Opponent = slugOpponent) %>%
  select( date,
          'Team SQ',
          'Opp SQ',
          'SQ Diff',
          Outcome,
          Opponent) %>%
  mutate_at(vars('Team SQ', 'Opp SQ'), funs(round(.,4))) %>%
  reactable( theme = espn(),
             defaultPageSize = 20,
             sortable = TRUE,
             filterable = TRUE,
             searchable = TRUE)

• Team SQ = Team Shot Quality

• Opp SQ = Opponent Shot Quality

• SQ Diff = Difference in Shot Quality

• Table is sortable, searchable, and filterable.