- For Module 4/5 Project I, let us take a look at the “Ultimate UFC Dataset”
- Sourced from Kaggle, this set all comes from the official UFC site
- Overview: This set contains data from every Ultimate Fighting Championship fight that has occurred from November ’93 to June ’19.
- Specifically, we are provided fighter stats, wins, losses, referees, date, location, weight-class, etc.
- Link to Kaggle dataset: https://www.kaggle.com/datasets/rajeevw/ufcdata?search=fight
2023-03-27
Dataset Information & Overview
Problem to Address
- Which of the provided factors/variables are most influential on the probability of winning a UFC fight?
- Specifically, we will perform data exploration and analysis to determine which of these variables have a large impact on the probability of winning a fight.
Loading our Libraries and Primary Dataset
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.0 ✔ readr 2.1.4 ## ✔ forcats 1.0.0 ✔ stringr 1.5.0 ## ✔ ggplot2 3.4.1 ✔ tibble 3.1.8 ## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0 ## ✔ purrr 1.0.1 ## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ── ## ✖ dplyr::filter() masks stats::filter() ## ✖ dplyr::lag() masks stats::lag() ## ℹ Use the ]8;;http://conflicted.r-lib.org/conflicted package]8;; to force all conflicts to become errors
library(car)
## Loading required package: carData ## ## Attaching package: 'car' ## ## The following object is masked from 'package:dplyr': ## ## recode ## ## The following object is masked from 'package:purrr': ## ## some
library(ggplot2)
ufc_data <- read.csv("/Users/scarlettevans/Desktop/ufc_data.csv")
Data Structure & Summary
- So, we see that there are a total of 1514 observations with 147 total variables
## 'data.frame': 6012 obs. of 144 variables: ## $ R_fighter : chr "Adrian Yanez" "Trevin Giles" "Tai Tuivasa" "Cheyanne Buys" ... ## $ B_fighter : chr "Gustavo Lopez" "Roman Dolidze" "Harry Hunsucker" "Montserrat Conejo" ... ## $ Referee : chr "Chris Tognoni" "Herb Dean" "Herb Dean" "Mark Smith" ... ## $ date : chr "2021-03-20" "2021-03-20" "2021-03-20" "2021-03-20" ... ## $ location : chr "Las Vegas, Nevada, USA" "Las Vegas, Nevada, USA" "Las Vegas, Nevada, USA" "Las Vegas, Nevada, USA" ... ## $ Winner : chr "Red" "Red" "Red" "Blue" ... ## $ title_bout : chr "False" "False" "False" "False" ... ## $ weight_class : chr "Bantamweight" "Middleweight" "Heavyweight" "WomenStrawweight" ... ## $ B_avg_KD : num 0 0.5 NA NA 0.125 ... ## $ B_avg_opp_KD : num 0 0 NA NA 0 0 0.125 0 NA NA ... ## $ B_avg_SIG_STR_pct : num 0.42 0.66 NA NA 0.536 ... ## $ B_avg_opp_SIG_STR_pct : num 0.495 0.305 NA NA 0.579 ... ## $ B_avg_TD_pct : num 0.33 0.3 NA NA 0.185 ... ## $ B_avg_opp_TD_pct : num 0.36 0.5 NA NA 0.166 ... ## $ B_avg_SUB_ATT : num 0.5 1.5 NA NA 0.125 ... ## $ B_avg_opp_SUB_ATT : num 1 0 NA NA 0.188 ... ## $ B_avg_REV : num 0 0 NA NA 0.25 ... ## $ B_avg_opp_REV : num 0 0 NA NA 0 ... ## $ B_avg_SIG_STR_att : num 50 65.5 NA NA 109.2 ... ## $ B_avg_SIG_STR_landed : num 20 35 NA NA 57.9 ... ## $ B_avg_opp_SIG_STR_att : num 84 50 NA NA 50.6 ... ## $ B_avg_opp_SIG_STR_landed : num 45 16.5 NA NA 28.4 ... ## $ B_avg_TOTAL_STR_att : num 76.5 113.5 NA NA 170.4 ... ## $ B_avg_TOTAL_STR_landed : num 41 68.5 NA NA 105.6 ... ## $ B_avg_opp_TOTAL_STR_att : num 114 68.5 NA NA 74.4 ... ## $ B_avg_opp_TOTAL_STR_landed : num 64 29 NA NA 44.2 ... ## $ B_avg_TD_att : num 1.5 2.5 NA NA 5.38 ... ## $ B_avg_TD_landed : num 1 1.5 NA NA 1.5 ... ## $ B_avg_opp_TD_att : num 9 0.5 NA NA 2 ... ## $ B_avg_opp_TD_landed : num 6.5 0.5 NA NA 0.625 ... ## $ B_avg_HEAD_att : num 39.5 46 NA NA 77.4 ... ## $ B_avg_HEAD_landed : num 11 20 NA NA 31.4 ... ## $ B_avg_opp_HEAD_att : num 63 36 NA NA 41.6 ... ## $ B_avg_opp_HEAD_landed : num 27.5 7.5 NA NA 22.6 ... ## $ B_avg_BODY_att : num 7.5 12 NA NA 31.2 ... ## $ B_avg_BODY_landed : num 7 8 NA NA 26.2 ... ## $ B_avg_opp_BODY_att : num 12 8 NA NA 7.69 ... ## $ B_avg_opp_BODY_landed : num 9 3 NA NA 4.94 ... ## $ B_avg_LEG_att : num 3 7.5 NA NA 0.625 ... ## $ B_avg_LEG_landed : num 2 7 NA NA 0.375 ... ## $ B_avg_opp_LEG_att : num 9 6 NA NA 1.38 ... ## $ B_avg_opp_LEG_landed : num 8.5 6 NA NA 0.875 ... ## $ B_avg_DISTANCE_att : num 35 58 NA NA 33.6 ... ## $ B_avg_DISTANCE_landed : num 12.5 30 NA NA 11 ... ## $ B_avg_opp_DISTANCE_att : num 43.5 48 NA NA 32.1 ... ## $ B_avg_opp_DISTANCE_landed : num 17.5 15.5 NA NA 13.9 ... ## $ B_avg_CLINCH_att : num 10.5 0.5 NA NA 39.1 ... ## $ B_avg_CLINCH_landed : num 4.5 0.5 NA NA 28.8 ... ## $ B_avg_opp_CLINCH_att : num 4 0.5 NA NA 13.3 ... ## $ B_avg_opp_CLINCH_landed : num 3 0.5 NA NA 10.8 ... ## $ B_avg_GROUND_att : num 4.5 7 NA NA 36.6 ... ## $ B_avg_GROUND_landed : num 3 4.5 NA NA 18.1 ... ## $ B_avg_opp_GROUND_att : num 36.5 1.5 NA NA 5.25 ... ## $ B_avg_opp_GROUND_landed : num 24.5 0.5 NA NA 3.75 ... ## $ B_avg_CTRL_time.seconds. : num 34 220 NA NA 390 ... ## $ B_avg_opp_CTRL_time.seconds.: num 277.5 24.5 NA NA 156.3 ... ## $ B_total_time_fought.seconds.: num 532 578 NA NA 764 ... ## $ B_total_rounds_fought : int 4 4 0 0 11 10 28 23 0 0 ... ## $ B_total_title_bouts : int 0 0 0 0 1 0 0 0 0 0 ... ## $ B_current_win_streak : int 0 2 0 0 3 4 0 0 0 0 ... ## $ B_current_lose_streak : int 1 0 0 0 0 0 1 1 0 0 ... ## $ B_longest_win_streak : int 1 2 0 0 3 4 1 5 0 0 ... ## $ B_wins : int 1 2 0 0 4 4 4 8 0 0 ... ## $ B_losses : int 1 0 0 0 1 0 6 2 0 0 ... ## $ B_draw : int 0 0 0 0 0 0 0 0 0 0 ... ## $ B_win_by_Decision_Majority : int 0 0 0 0 0 0 1 0 0 0 ... ## $ B_win_by_Decision_Split : int 0 1 0 0 0 0 0 2 0 0 ... ## $ B_win_by_Decision_Unanimous : int 0 0 0 0 1 2 1 1 0 0 ... ## $ B_win_by_KO.TKO : int 0 1 0 0 2 0 2 3 0 0 ... ## $ B_win_by_Submission : int 1 0 0 0 1 2 0 2 0 0 ... ## $ B_win_by_TKO_Doctor_Stoppage: int 0 0 0 0 0 0 0 0 0 0 ... ## $ B_Stance : chr "Orthodox" "Orthodox" "Orthodox" "Southpaw" ... ## $ B_Height_cms : num 165 188 188 152 180 ... ## $ B_Reach_cms : num 170 193 190 155 183 ... ## $ B_Weight_lbs : num 135 205 241 115 135 145 170 185 135 125 ... ## $ R_avg_KD : num 1 1.031 0.547 NA 0 ... ## $ R_avg_opp_KD : num 0 0.0625 0.1875 NA 0.000977 ... ## $ R_avg_SIG_STR_pct : num 0.5 0.577 0.539 NA 0.403 ... ## $ R_avg_opp_SIG_STR_pct : num 0.46 0.381 0.599 NA 0.555 ... ## $ R_avg_TD_pct : num 0 0.406 0 NA 0.512 ... ## $ R_avg_opp_TD_pct : num 0 0.116 0.312 NA 0.629 ... ## $ R_avg_SUB_ATT : num 0 0.25 0 NA 0.231 ... ## $ R_avg_opp_SUB_ATT : num 0 1.1875 0.25 NA 0.0312 ... ## $ R_avg_REV : num 0 0.375 0 NA 0.0312 ... ## $ R_avg_opp_REV : num 0 0.25 0 NA 0.5 0.5 0.25 0 0 0.5 ... ## $ R_avg_SIG_STR_att : num 34 77.6 59.2 NA 109.3 ... ## $ R_avg_SIG_STR_landed : num 17 43.2 30.4 NA 44.4 ... ## $ R_avg_opp_SIG_STR_att : num 13 69.2 43.8 NA 148.8 ... ## $ R_avg_opp_SIG_STR_landed : num 6 27.6 24.8 NA 84.6 ... ## $ R_avg_TOTAL_STR_att : num 35 93.1 70.5 NA 137.2 ... ## $ R_avg_TOTAL_STR_landed : num 18 57.2 41.4 NA 70.2 ... ## $ R_avg_opp_TOTAL_STR_att : num 16 98.3 50.2 NA 172.5 ... ## $ R_avg_opp_TOTAL_STR_landed : num 9 52.5 30.9 NA 106.7 ... ## $ R_avg_TD_att : num 0 1.2812 0.0312 NA 2.2617 ... ## $ R_avg_TD_landed : num 0 0.781 0 NA 1.262 ... ## $ R_avg_opp_TD_att : num 3 4.69 2.84 NA 3.14 ... ## $ R_avg_opp_TD_landed : num 0 0.438 1.75 NA 1.771 ... ## $ R_avg_HEAD_att : num 32 71.1 42.5 NA 86.4 ... ## $ R_avg_HEAD_landed : num 15 38.1 16.8 NA 26 ... ## [list output truncated]
## R_fighter B_fighter Referee date ## Length:6012 Length:6012 Length:6012 Length:6012 ## Class :character Class :character Class :character Class :character ## Mode :character Mode :character Mode :character Mode :character ## ## ## ## ## location Winner title_bout weight_class ## Length:6012 Length:6012 Length:6012 Length:6012 ## Class :character Class :character Class :character Class :character ## Mode :character Mode :character Mode :character Mode :character ## ## ## ## ## B_avg_KD B_avg_opp_KD B_avg_SIG_STR_pct B_avg_opp_SIG_STR_pct ## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000 ## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.3765 1st Qu.:0.3510 ## Median :0.0156 Median :0.0000 Median :0.4500 Median :0.4275 ## Mean :0.2475 Mean :0.1768 Mean :0.4533 Mean :0.4343 ## 3rd Qu.:0.5000 3rd Qu.:0.2500 3rd Qu.:0.5275 3rd Qu.:0.5100 ## Max. :5.0000 Max. :3.0000 Max. :1.0000 Max. :1.0000 ## NA's :1427 NA's :1427 NA's :1427 NA's :1427 ## B_avg_TD_pct B_avg_opp_TD_pct B_avg_SUB_ATT B_avg_opp_SUB_ATT ## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000 ## 1st Qu.:0.0312 1st Qu.:0.0332 1st Qu.:0.0000 1st Qu.:0.0000 ## Median :0.2500 Median :0.2000 Median :0.1485 Median :0.0984 ## Mean :0.2926 Mean :0.2687 Mean :0.4789 Mean :0.4093 ## 3rd Qu.:0.5000 3rd Qu.:0.4228 3rd Qu.:0.7500 3rd Qu.:0.5312 ## Max. :1.0000 Max. :1.0000 Max. :8.0000 Max. :7.0000 ## NA's :1427 NA's :1427 NA's :1427 NA's :1427 ## B_avg_REV B_avg_opp_REV B_avg_SIG_STR_att B_avg_SIG_STR_landed ## Min. :0.0000 Min. :0.0000 Min. : 0.00 Min. : 0.00 ## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.: 38.26 1st Qu.: 17.00 ## Median :0.0000 Median :0.0000 Median : 66.50 Median : 29.69 ## Mean :0.1567 Mean :0.1413 Mean : 76.29 Mean : 33.34 ## 3rd Qu.:0.1250 3rd Qu.:0.1250 3rd Qu.:104.75 3rd Qu.: 45.50 ## Max. :4.0000 Max. :3.0000 Max. :456.00 Max. :186.00 ## NA's :1427 NA's :1427 NA's :1427 NA's :1427 ## B_avg_opp_SIG_STR_att B_avg_opp_SIG_STR_landed B_avg_TOTAL_STR_att ## Min. : 0.00 Min. : 0.00 Min. : 0.00 ## 1st Qu.: 36.41 1st Qu.: 15.56 1st Qu.: 55.48 ## Median : 64.31 Median : 27.34 Median : 89.75 ## Mean : 73.09 Mean : 31.05 Mean : 97.64 ## 3rd Qu.: 99.88 3rd Qu.: 42.00 3rd Qu.:132.47 ## Max. :403.00 Max. :202.00 Max. :524.00 ## NA's :1427 NA's :1427 NA's :1427 ## B_avg_TOTAL_STR_landed B_avg_opp_TOTAL_STR_att B_avg_opp_TOTAL_STR_landed ## Min. : 0.00 Min. : 0.00 Min. : 0.00 ## 1st Qu.: 28.94 1st Qu.: 52.99 1st Qu.: 26.88 ## Median : 48.00 Median : 85.53 Median : 44.41 ## Mean : 52.28 Mean : 92.72 Mean : 48.50 ## 3rd Qu.: 70.00 3rd Qu.:125.73 3rd Qu.: 65.19 ## Max. :242.00 Max. :433.00 Max. :232.00 ## NA's :1427 NA's :1427 NA's :1427 ## B_avg_TD_att B_avg_TD_landed B_avg_opp_TD_att B_avg_opp_TD_landed ## Min. : 0.000 Min. : 0.0000 Min. : 0.000 Min. : 0.000 ## 1st Qu.: 0.625 1st Qu.: 0.0625 1st Qu.: 1.000 1st Qu.: 0.125 ## Median : 2.000 Median : 0.7500 Median : 2.055 Median : 0.750 ## Mean : 2.727 Mean : 1.1091 Mean : 2.861 Mean : 1.073 ## 3rd Qu.: 4.000 3rd Qu.: 1.5625 3rd Qu.: 4.000 3rd Qu.: 1.500 ## Max. :19.000 Max. :10.9688 Max. :20.000 Max. :11.500 ## NA's :1427 NA's :1427 NA's :1427 NA's :1427 ## B_avg_HEAD_att B_avg_HEAD_landed B_avg_opp_HEAD_att B_avg_opp_HEAD_landed ## Min. : 0.00 Min. : 0.00 Min. : 0.00 Min. : 0.00 ## 1st Qu.: 29.30 1st Qu.: 10.50 1st Qu.: 27.88 1st Qu.: 9.00 ## Median : 51.19 Median : 18.34 Median : 49.61 Median : 16.28 ## Mean : 59.98 Mean : 21.39 Mean : 57.06 Mean : 19.40 ## 3rd Qu.: 81.50 3rd Qu.: 28.82 3rd Qu.: 77.33 3rd Qu.: 26.50 ## Max. :397.00 Max. :138.00 Max. :373.00 Max. :126.00 ## NA's :1427 NA's :1427 NA's :1427 NA's :1427 ## B_avg_BODY_att B_avg_BODY_landed B_avg_opp_BODY_att B_avg_opp_BODY_landed ## Min. : 0.000 Min. : 0.000 Min. : 0.00 Min. : 0.000 ## 1st Qu.: 3.586 1st Qu.: 2.375 1st Qu.: 3.50 1st Qu.: 2.250 ## Median : 7.500 Median : 5.077 Median : 7.50 Median : 5.000 ## Mean : 9.684 Mean : 6.682 Mean : 9.37 Mean : 6.352 ## 3rd Qu.:13.500 3rd Qu.: 9.297 3rd Qu.:13.00 3rd Qu.: 8.781 ## Max. :71.000 Max. :64.000 Max. :71.00 Max. :64.000 ## NA's :1427 NA's :1427 NA's :1427 NA's :1427 ## B_avg_LEG_att B_avg_LEG_landed B_avg_opp_LEG_att B_avg_opp_LEG_landed ## Min. : 0.000 Min. : 0.000 Min. : 0.000 Min. : 0.000 ## 1st Qu.: 1.876 1st Qu.: 1.438 1st Qu.: 2.000 1st Qu.: 1.625 ## Median : 4.500 Median : 3.625 Median : 4.984 Median : 3.938 ## Mean : 6.620 Mean : 5.268 Mean : 6.667 Mean : 5.298 ## 3rd Qu.: 9.250 3rd Qu.: 7.282 3rd Qu.: 9.125 3rd Qu.: 7.356 ## Max. :62.830 Max. :51.636 Max. :69.000 Max. :58.000 ## NA's :1427 NA's :1427 NA's :1427 NA's :1427 ## B_avg_DISTANCE_att B_avg_DISTANCE_landed B_avg_opp_DISTANCE_att ## Min. : 0.00 Min. : 0.00 Min. : 0.00 ## 1st Qu.: 23.00 1st Qu.: 8.00 1st Qu.: 22.50 ## Median : 48.69 Median : 17.00 Median : 47.12 ## Mean : 60.06 Mean : 22.31 Mean : 58.57 ## 3rd Qu.: 84.72 3rd Qu.: 31.57 3rd Qu.: 83.00 ## Max. :422.00 Max. :161.00 Max. :391.00 ## NA's :1427 NA's :1427 NA's :1427 ## B_avg_opp_DISTANCE_landed B_avg_CLINCH_att B_avg_CLINCH_landed ## Min. : 0.00 Min. : 0.00 Min. : 0.000 ## 1st Qu.: 7.75 1st Qu.: 2.50 1st Qu.: 1.516 ## Median : 16.50 Median : 5.75 Median : 3.750 ## Mean : 21.29 Mean : 8.07 Mean : 5.514 ## 3rd Qu.: 29.75 3rd Qu.:11.08 3rd Qu.: 7.625 ## Max. :159.00 Max. :87.00 Max. :68.000 ## NA's :1427 NA's :1427 NA's :1427 ## B_avg_opp_CLINCH_att B_avg_opp_CLINCH_landed B_avg_GROUND_att ## Min. : 0.000 Min. : 0.000 Min. : 0.000 ## 1st Qu.: 2.456 1st Qu.: 1.445 1st Qu.: 1.960 ## Median : 5.312 Median : 3.438 Median : 5.062 ## Mean : 7.477 Mean : 5.046 Mean : 8.159 ## 3rd Qu.: 10.250 3rd Qu.: 7.000 3rd Qu.:11.004 ## Max. :105.000 Max. :84.000 Max. :88.000 ## NA's :1427 NA's :1427 NA's :1427 ## B_avg_GROUND_landed B_avg_opp_GROUND_att B_avg_opp_GROUND_landed ## Min. : 0.000 Min. : 0.000 Min. : 0.0000 ## 1st Qu.: 1.141 1st Qu.: 1.094 1st Qu.: 0.7539 ## Median : 3.500 Median : 3.875 Median : 2.5000 ## Mean : 5.510 Mean : 7.042 Mean : 4.7195 ## 3rd Qu.: 7.625 3rd Qu.: 9.000 3rd Qu.: 6.0000 ## Max. :48.000 Max. :141.000 Max. :84.0000 ## NA's :1427 NA's :1427 NA's :1427 ## B_avg_CTRL_time.seconds. B_avg_opp_CTRL_time.seconds. ## Min. : 0.00 Min. : 0.00 ## 1st Qu.: 36.00 1st Qu.: 35.09 ## Median : 99.21 Median : 94.12 ## Mean : 137.28 Mean :132.59 ## 3rd Qu.: 200.19 3rd Qu.:192.38 ## Max. :1020.20 Max. :835.00 ## NA's :1427 NA's :1427 ## B_total_time_fought.seconds. B_total_rounds_fought B_total_title_bouts ## Min. : 7.0 Min. : 0.000 Min. : 0.0000 ## 1st Qu.: 419.0 1st Qu.: 1.000 1st Qu.: 0.0000 ## Median : 638.5 Median : 5.000 Median : 0.0000 ## Mean : 611.4 Mean : 9.442 Mean : 0.2773 ## 3rd Qu.: 846.4 3rd Qu.:13.000 3rd Qu.: 0.0000 ## Max. :1500.0 Max. :94.000 Max. :16.0000 ## NA's :1427 ## B_current_win_streak B_current_lose_streak B_longest_win_streak ## Min. : 0.0000 Min. :0.0000 Min. : 0.000 ## 1st Qu.: 0.0000 1st Qu.:0.0000 1st Qu.: 0.000 ## Median : 0.0000 Median :0.0000 Median : 1.000 ## Mean : 0.9473 Mean :0.3972 Mean : 1.631 ## 3rd Qu.: 1.0000 3rd Qu.:1.0000 3rd Qu.: 3.000 ## Max. :16.0000 Max. :5.0000 Max. :16.000 ## ## B_wins B_losses B_draw B_win_by_Decision_Majority ## Min. : 0.000 Min. : 0.00 Min. :0 Min. :0.00000 ## 1st Qu.: 0.000 1st Qu.: 0.00 1st Qu.:0 1st Qu.:0.00000 ## Median : 1.000 Median : 1.00 Median :0 Median :0.00000 ## Mean : 2.585 Mean : 1.54 Mean :0 Mean :0.01613 ## 3rd Qu.: 4.000 3rd Qu.: 2.00 3rd Qu.:0 3rd Qu.:0.00000 ## Max. :23.000 Max. :16.00 Max. :0 Max. :2.00000 ## ## B_win_by_Decision_Split B_win_by_Decision_Unanimous B_win_by_KO.TKO ## Min. :0.0000 Min. : 0.0000 Min. : 0.0000 ## 1st Qu.:0.0000 1st Qu.: 0.0000 1st Qu.: 0.0000 ## Median :0.0000 Median : 0.0000 Median : 0.0000 ## Mean :0.2184 Mean : 0.8382 Mean : 0.8957 ## 3rd Qu.:0.0000 3rd Qu.: 1.0000 3rd Qu.: 1.0000 ## Max. :5.0000 Max. :10.0000 Max. :11.0000 ## ## B_win_by_Submission B_win_by_TKO_Doctor_Stoppage B_Stance ## Min. : 0.0000 Min. :0.00000 Length:6012 ## 1st Qu.: 0.0000 1st Qu.:0.00000 Class :character ## Median : 0.0000 Median :0.00000 Mode :character ## Mean : 0.5695 Mean :0.04208 ## 3rd Qu.: 1.0000 3rd Qu.:0.00000 ## Max. :14.0000 Max. :2.00000 ## ## B_Height_cms B_Reach_cms B_Weight_lbs R_avg_KD ## Min. :152.4 Min. :147.3 Min. :115.0 Min. :0.0000 ## 1st Qu.:172.7 1st Qu.:177.8 1st Qu.:145.0 1st Qu.:0.0000 ## Median :180.3 Median :182.9 Median :170.0 Median :0.0472 ## Mean :179.0 Mean :183.2 Mean :170.6 Mean :0.2435 ## 3rd Qu.:185.4 3rd Qu.:190.5 3rd Qu.:185.0 3rd Qu.:0.4375 ## Max. :210.8 Max. :213.4 Max. :770.0 Max. :4.0000 ## NA's :10 NA's :891 NA's :8 NA's :712 ## R_avg_opp_KD R_avg_SIG_STR_pct R_avg_opp_SIG_STR_pct R_avg_TD_pct ## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000 ## 1st Qu.:0.0000 1st Qu.:0.3762 1st Qu.:0.3472 1st Qu.:0.0666 ## Median :0.0000 Median :0.4500 Median :0.4218 Median :0.2500 ## Mean :0.1880 Mean :0.4572 Mean :0.4253 Mean :0.3009 ## 3rd Qu.:0.2525 3rd Qu.:0.5300 3rd Qu.:0.5000 3rd Qu.:0.5000 ## Max. :3.0000 Max. :1.0000 Max. :1.0000 Max. :1.0000 ## NA's :712 NA's :712 NA's :712 NA's :712 ## R_avg_opp_TD_pct R_avg_SUB_ATT R_avg_opp_SUB_ATT R_avg_REV ## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000 ## 1st Qu.:0.0371 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 ## Median :0.1917 Median :0.1875 Median :0.1250 Median :0.0000 ## Mean :0.2544 Mean :0.4635 Mean :0.3939 Mean :0.1414 ## 3rd Qu.:0.4026 3rd Qu.:0.7267 3rd Qu.:0.5156 3rd Qu.:0.1250 ## Max. :1.0000 Max. :9.0000 Max. :8.0000 Max. :3.0000 ## NA's :712 NA's :712 NA's :712 NA's :712 ## R_avg_opp_REV R_avg_SIG_STR_att R_avg_SIG_STR_landed R_avg_opp_SIG_STR_att ## Min. :0.0000 Min. : 0.00 Min. : 0.00 Min. : 0.00 ## 1st Qu.:0.0000 1st Qu.: 41.88 1st Qu.: 18.93 1st Qu.: 38.66 ## Median :0.0000 Median : 69.50 Median : 30.50 Median : 66.98 ## Mean :0.1432 Mean : 79.35 Mean : 34.81 Mean : 76.07 ## 3rd Qu.:0.1250 3rd Qu.:106.00 3rd Qu.: 46.00 3rd Qu.:103.50 ## Max. :4.0000 Max. :419.32 Max. :212.14 Max. :454.00 ## NA's :712 NA's :712 NA's :712 NA's :712 ## R_avg_opp_SIG_STR_landed R_avg_TOTAL_STR_att R_avg_TOTAL_STR_landed ## Min. : 0.00 Min. : 0.00 Min. : 0.00 ## 1st Qu.: 16.03 1st Qu.: 58.27 1st Qu.: 30.94 ## Median : 27.85 Median : 94.00 Median : 48.54 ## Mean : 31.89 Mean :100.59 Mean : 53.69 ## 3rd Qu.: 43.00 3rd Qu.:133.74 3rd Qu.: 70.00 ## Max. :175.00 Max. :440.34 Max. :248.12 ## NA's :712 NA's :712 NA's :712 ## R_avg_opp_TOTAL_STR_att R_avg_opp_TOTAL_STR_landed R_avg_TD_att ## Min. : 0.00 Min. : 0.00 Min. : 0.000 ## 1st Qu.: 54.25 1st Qu.: 27.50 1st Qu.: 0.750 ## Median : 88.50 Median : 44.75 Median : 2.000 ## Mean : 95.55 Mean : 49.26 Mean : 2.944 ## 3rd Qu.:128.48 3rd Qu.: 65.50 3rd Qu.: 4.271 ## Max. :461.00 Max. :202.86 Max. :30.000 ## NA's :712 NA's :712 NA's :712 ## R_avg_TD_landed R_avg_opp_TD_att R_avg_opp_TD_landed R_avg_HEAD_att ## Min. : 0.0000 Min. : 0.000 Min. : 0.0000 Min. : 0.00 ## 1st Qu.: 0.1875 1st Qu.: 1.000 1st Qu.: 0.1328 1st Qu.: 32.08 ## Median : 0.8125 Median : 2.016 Median : 0.6641 Median : 54.00 ## Mean : 1.1841 Mean : 2.823 Mean : 1.0187 Mean : 62.28 ## 3rd Qu.: 1.7344 3rd Qu.: 4.000 3rd Qu.: 1.5000 3rd Qu.: 83.00 ## Max. :11.0000 Max. :22.000 Max. :13.0000 Max. :368.18 ## NA's :712 NA's :712 NA's :712 NA's :712 ## R_avg_HEAD_landed R_avg_opp_HEAD_att R_avg_opp_HEAD_landed R_avg_BODY_att ## Min. : 0.00 Min. : 0.00 Min. : 0.00 Min. : 0.000 ## 1st Qu.: 11.61 1st Qu.: 29.11 1st Qu.: 9.50 1st Qu.: 4.000 ## Median : 19.02 Median : 51.48 Median : 16.94 Median : 7.918 ## Mean : 22.34 Mean : 59.78 Mean : 20.16 Mean :10.019 ## 3rd Qu.: 29.38 3rd Qu.: 81.73 3rd Qu.: 27.15 3rd Qu.:13.750 ## Max. :173.16 Max. :400.00 Max. :139.00 Max. :71.000 ## NA's :712 NA's :712 NA's :712 NA's :712 ## R_avg_BODY_landed R_avg_opp_BODY_att R_avg_opp_BODY_landed R_avg_LEG_att ## Min. : 0.000 Min. : 0.000 Min. : 0.000 Min. : 0.000 ## 1st Qu.: 2.717 1st Qu.: 3.750 1st Qu.: 2.500 1st Qu.: 2.000 ## Median : 5.431 Median : 7.750 Median : 5.062 Median : 4.781 ## Mean : 6.871 Mean : 9.552 Mean : 6.442 Mean : 7.046 ## 3rd Qu.: 9.377 3rd Qu.:13.500 3rd Qu.: 8.982 3rd Qu.: 9.997 ## Max. :54.000 Max. :75.000 Max. :43.350 Max. :71.570 ## NA's :712 NA's :712 NA's :712 NA's :712 ## R_avg_LEG_landed R_avg_opp_LEG_att R_avg_opp_LEG_landed R_avg_DISTANCE_att ## Min. : 0.000 Min. : 0.000 Min. : 0.000 Min. : 0.00 ## 1st Qu.: 1.500 1st Qu.: 2.147 1st Qu.: 1.688 1st Qu.: 25.69 ## Median : 3.937 Median : 4.899 Median : 3.844 Median : 51.03 ## Mean : 5.593 Mean : 6.737 Mean : 5.291 Mean : 62.68 ## 3rd Qu.: 7.948 3rd Qu.: 9.161 3rd Qu.: 7.333 3rd Qu.: 87.81 ## Max. :62.352 Max. :77.387 Max. :55.427 Max. :396.11 ## NA's :712 NA's :712 NA's :712 NA's :712 ## R_avg_DISTANCE_landed R_avg_opp_DISTANCE_att R_avg_opp_DISTANCE_landed ## Min. : 0.00 Min. : 0.00 Min. : 0.00 ## 1st Qu.: 9.00 1st Qu.: 24.97 1st Qu.: 8.00 ## Median : 18.40 Median : 50.52 Median : 17.50 ## Mean : 23.46 Mean : 61.61 Mean : 22.19 ## 3rd Qu.: 32.75 3rd Qu.: 86.50 3rd Qu.: 31.50 ## Max. :192.65 Max. :440.00 Max. :169.00 ## NA's :712 NA's :712 NA's :712 ## R_avg_CLINCH_att R_avg_CLINCH_landed R_avg_opp_CLINCH_att ## Min. : 0.000 Min. : 0.000 Min. : 0.000 ## 1st Qu.: 2.688 1st Qu.: 1.692 1st Qu.: 2.620 ## Median : 5.750 Median : 3.750 Median : 5.500 ## Mean : 7.923 Mean : 5.409 Mean : 7.545 ## 3rd Qu.:10.750 3rd Qu.: 7.048 3rd Qu.:10.034 ## Max. :82.000 Max. :61.000 Max. :82.000 ## NA's :712 NA's :712 NA's :712 ## R_avg_opp_CLINCH_landed R_avg_GROUND_att R_avg_GROUND_landed ## Min. : 0.000 Min. : 0.000 Min. : 0.000 ## 1st Qu.: 1.562 1st Qu.: 2.000 1st Qu.: 1.404 ## Median : 3.500 Median : 5.375 Median : 3.688 ## Mean : 5.061 Mean : 8.746 Mean : 5.942 ## 3rd Qu.: 6.675 3rd Qu.: 11.594 3rd Qu.: 8.000 ## Max. :51.000 Max. :141.000 Max. :68.000 ## NA's :712 NA's :712 NA's :712 ## R_avg_opp_GROUND_att R_avg_opp_GROUND_landed R_avg_CTRL_time.seconds. ## Min. : 0.000 Min. : 0.000 Min. : 0.00 ## 1st Qu.: 1.156 1st Qu.: 0.750 1st Qu.: 38.28 ## Median : 4.000 Median : 2.656 Median :104.87 ## Mean : 6.912 Mean : 4.640 Mean :144.22 ## 3rd Qu.: 9.250 3rd Qu.: 6.225 3rd Qu.:211.14 ## Max. :104.000 Max. :68.000 Max. :996.75 ## NA's :712 NA's :712 NA's :712 ## R_avg_opp_CTRL_time.seconds. R_total_time_fought.seconds. ## Min. : 0.0 Min. : 7.0 ## 1st Qu.: 34.0 1st Qu.: 438.5 ## Median : 89.5 Median : 655.8 ## Mean :125.1 Mean : 633.3 ## 3rd Qu.:176.5 3rd Qu.: 851.1 ## Max. :812.0 Max. :1500.0 ## NA's :712 NA's :712 ## R_total_rounds_fought R_total_title_bouts R_current_win_streak ## Min. : 0.00 Min. : 0.0000 Min. : 0.000 ## 1st Qu.: 3.00 1st Qu.: 0.0000 1st Qu.: 0.000 ## Median : 9.00 Median : 0.0000 Median : 1.000 ## Mean :13.67 Mean : 0.5822 Mean : 1.315 ## 3rd Qu.:20.00 3rd Qu.: 1.0000 3rd Qu.: 2.000 ## Max. :88.00 Max. :16.0000 Max. :16.000 ## ## R_current_lose_streak R_longest_win_streak R_wins R_losses ## Min. :0.0000 Min. : 0.000 Min. : 0.000 Min. : 0.000 ## 1st Qu.:0.0000 1st Qu.: 1.000 1st Qu.: 1.000 1st Qu.: 0.000 ## Median :0.0000 Median : 2.000 Median : 3.000 Median : 1.000 ## Mean :0.3891 Mean : 2.313 Mean : 3.757 Mean : 2.071 ## 3rd Qu.:1.0000 3rd Qu.: 3.000 3rd Qu.: 6.000 3rd Qu.: 3.000 ## Max. :4.0000 Max. :16.000 Max. :23.000 Max. :17.000 ## ## R_draw R_win_by_Decision_Majority R_win_by_Decision_Split ## Min. :0 Min. :0.00000 Min. :0.0000 ## 1st Qu.:0 1st Qu.:0.00000 1st Qu.:0.0000 ## Median :0 Median :0.00000 Median :0.0000 ## Mean :0 Mean :0.02794 Mean :0.3069 ## 3rd Qu.:0 3rd Qu.:0.00000 3rd Qu.:0.0000 ## Max. :0 Max. :2.00000 Max. :5.0000 ## ## R_win_by_Decision_Unanimous R_win_by_KO.TKO R_win_by_Submission ## Min. : 0.000 Min. : 0.000 Min. : 0.0000 ## 1st Qu.: 0.000 1st Qu.: 0.000 1st Qu.: 0.0000 ## Median : 1.000 Median : 1.000 Median : 0.0000 ## Mean : 1.251 Mean : 1.298 Mean : 0.7962 ## 3rd Qu.: 2.000 3rd Qu.: 2.000 3rd Qu.: 1.0000 ## Max. :10.000 Max. :11.000 Max. :13.0000 ## ## R_win_by_TKO_Doctor_Stoppage R_Stance R_Height_cms ## Min. :0.00000 Length:6012 Min. :152.4 ## 1st Qu.:0.00000 Class :character 1st Qu.:172.7 ## Median :0.00000 Mode :character Median :180.3 ## Mean :0.06919 Mean :179.0 ## 3rd Qu.:0.00000 3rd Qu.:185.4 ## Max. :2.00000 Max. :210.8 ## NA's :4 ## R_Reach_cms R_Weight_lbs B_age R_age ## Min. :152.4 Min. :115.0 Min. :18.00 Min. :19.0 ## 1st Qu.:177.8 1st Qu.:145.0 1st Qu.:26.00 1st Qu.:27.0 ## Median :182.9 Median :170.0 Median :29.00 Median :29.0 ## Mean :183.6 Mean :170.7 Mean :29.29 Mean :29.6 ## 3rd Qu.:190.5 3rd Qu.:185.0 3rd Qu.:32.00 3rd Qu.:32.0 ## Max. :213.4 Max. :345.0 Max. :51.00 Max. :47.0 ## NA's :406 NA's :2 NA's :172 NA's :63
Data Exploration
- Delving deeper into the number of unique winners, we see that there are a total of 1058 unique winners.
- Interestingly, the fighter with the most number of wins is Georges St-Pierre with 20 total wins, with a quick Google search we can see this aligns with the actual UFC results
## # A tibble: 3 × 3 ## Winner n percent ## <chr> <int> <dbl> ## 1 Red 3979 66.2 ## 2 Blue 1923 32.0 ## 3 Draw 110 1.83
Corner of the Winner Distribution
- Starting with a variable that likely does not directly influence the winner probability: which corner is winning (red v blue)
- So, we create a plot to further analyze and, we can conclude that the RED corner wins more UFC fights
Fighter Statistics
- Now, let us look at the variables that are more likely to directly affect a fighter’s performance / ability to win a fight
- These include the fighter’s WEIGHT, HEIGHT, & AGE
Age vs. Winner Outcome
- Looking at the relationship between age & the outcome of the fight
- Implement a density plot that displays the age difference by winner
## Warning: Removed 63 rows containing non-finite values (`stat_density()`).
* Through this density plot, we can conclude there is not a significant difference between the age of winning fighters and losing fighters
Weight vs Winner Outcome
- Next, let us look at the relationship between weight and the winning/losing fighters
- Again, we are doing so via a density plot of the weight differences
## Warning: Removed 2 rows containing non-finite values (`stat_density()`).
Height vs Winner Outcome
- Lastly, we are looking at the relationship between height and outcome
- Analyzing the density plot, there does not seem to be a large difference between these two factors
## Warning: Removed 4 rows containing non-finite values (`stat_density()`).
Creating Binary Winner Column
- As part of data wrangling and cleanup, I found it necessary to mutate the data to ensure our winner data conformed to being binary, as shown:
ufc_data <- ufc_data %>% mutate(R_wins = ifelse(Winner == "Red", 1, 0))
Logistic Regresion Model - Factors for Fighter Win Chances
- Using the glm function, let’s create a logistic regression model to analyze the specific fight statistics to include strike attempts, landed strikes, knockdowns, significant strikes, etc.
- Our goal is to determine which of these are higher predictors for a fight win utilizing a p-value of 0.05 as our basis
- Thus, the significant predictors of the winner of a fight are having a higher average number of significant landed strikes, hhigher distance strikes, and higher average ground strikes.
- Interestingly, on the opposite end, fighters with a higher number of clinch strikes and body strikes are somewhat associated with a lesser probability of winning
Code Snippets from Logistic Regression Model
## ## Call: ## glm(formula = R_wins ~ R_Height_cms + R_Reach_cms + R_Weight_lbs + ## B_Height_cms + B_Reach_cms + B_Weight_lbs, family = binomial, ## data = ufc_data) ## ## Deviance Residuals: ## Min 1Q Median 3Q Max ## -1.6855 -1.3547 0.9192 0.9931 1.2096 ## ## Coefficients: ## Estimate Std. Error z value Pr(>|z|) ## (Intercept) 0.3730358 1.0107260 0.369 0.71207 ## R_Height_cms -0.0063266 0.0081691 -0.774 0.43867 ## R_Reach_cms 0.0190443 0.0063512 2.999 0.00271 ** ## R_Weight_lbs 0.0088164 0.0029413 2.997 0.00272 ** ## B_Height_cms -0.0007267 0.0081875 -0.089 0.92928 ## B_Reach_cms -0.0132359 0.0064091 -2.065 0.03891 * ## B_Weight_lbs -0.0069766 0.0029757 -2.345 0.01905 * ## --- ## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 ## ## (Dispersion parameter for binomial family taken to be 1) ## ## Null deviance: 6591.6 on 4961 degrees of freedom ## Residual deviance: 6556.8 on 4955 degrees of freedom ## (1050 observations deleted due to missingness) ## AIC: 6570.8 ## ## Number of Fisher Scoring iterations: 4
Real-World Application
- Now, having data analysis and exploration like this is beneficial to fight watchers who want to predict fight outcomes, however, this is also beneficial to the fighters themselves
- Knowing which types of factors increase their likelihood of winning is essential to formulating better training strategies and identifying which variables are within their control