Introduction

The following is an analysis of the video game Super Mario Strikers for Gamecube. Data was obtained by manual input at the conclusion of each individual game on an excel spreadsheet. Data was collected for 2,400 games. 426 games were recorded against the computer while the remaining 1,974 games were human against human games. Each game was set to last two minutes each, for the exception of overtime.

As shown below, some stats have been adjusted in order to represent a two minute average so as to eliminate any bias from games that reached overtime. In overtime, games would continue past the two minute mark until a go-ahead goal was scored to determine a winner. For example, a two minute game could last as long as four minutes since a goal was not scored for two minutes past regulation time. In many instances, this created inflated numbers for shots taken and hits while deflating averages for goals scored.

Data Set

This is the full data set. Here you are able to sort through the data yourself to see exactly what data is being used to create the following analysis.

Summary of Primary Statistics

In order to provide a general baseline of performance in a typical game, this table shows typical expectations from each game.

Goals_2min Shots_2min Shot_Efficiency
Min. :0.0000 Min. : 0.7947 Min. :0.00000
1st Qu.:0.8571 1st Qu.: 6.0000 1st Qu.:0.09091
Median :1.0000 Median : 8.0000 Median :0.18182
Mean :1.5475 Mean : 7.8130 Mean :0.19511
3rd Qu.:2.0000 3rd Qu.: 9.8212 3rd Qu.:0.28571
Max. :8.0000 Max. :18.0000 Max. :1.00000

Stats Created

Stat Formula Explanation
Shot Efficiency Goals/Shots Average number of goals made per shot taken.
Goals_2min (Goals*120)/Time Average number of goals per 2 minute game.
Hits_2min (Hits*120)/Time Average number of hits per 2 min.
Steals_2min (Steals*120)/Time Average number of steals per 2 min.
PerfP_2min (Perfect P*120)/Time Average number of Perfect Passes per 2 min.
GoalsA_2min (GoalsA*120)/Time Average goals allowed per 2 min.
Goal_Diff_2min Goals_2min-GoalsA_2min Average goal differential per 2 min.
Shots_2min (Shots*120)/Time Average number of shots per 2 min.
Shot_Efficiency_Against GoalsA/ShotsA Shot efficiency by opposing team(s).

Human vs. Human Analysis

Matchup Analysis

Below is a table of individual player stats against one another.

Player Opponent Games Wins Losses Win_Perc GoalsPG Shot_Eff GAgainst Goal_Differential
Preston Josh 16 15 1 0.938 2.640 0.230 0.729 1.911
Preston Matt 631 431 200 0.683 2.067 0.227 1.270 0.797
Preston Brandon 22 14 8 0.636 1.614 0.186 1.059 0.555
Brandon Matt 136 86 50 0.632 1.510 0.182 1.108 0.402
Matt Josh 182 114 68 0.626 1.603 0.179 1.169 0.434
Josh Matt 182 68 114 0.374 1.169 0.175 1.603 -0.434
Matt Brandon 136 50 86 0.368 1.108 0.148 1.510 -0.402
Brandon Preston 22 8 14 0.364 1.059 0.142 1.614 -0.555
Matt Preston 631 200 431 0.317 1.270 0.173 2.067 -0.797
Josh Preston 16 1 15 0.062 0.729 0.120 2.640 -1.911

This table shows, simply based on Win Percentage, that Preston is the most dominant player. Preston claims the top 3 spots for Win Percentage against each of his opponents. In fact, he has some of the best stats of any player with data available.

Individual Stats

This next table shows individual stats regardless of opponent, which also shows Preston’s dominance.

Player Games Wins Losses Win_Perc GoalsPG Shot_Eff GAgainst Goal_Differential
Preston 669 460 209 0.688 2.065 0.226 1.250 0.815
Brandon 158 94 64 0.595 1.447 0.177 1.178 0.269
Matt 949 364 585 0.384 1.310 0.171 1.815 -0.504
Josh 198 69 129 0.348 1.133 0.171 1.687 -0.553

Overall, it is pretty clear, simply from numbers, that Preston is the better player.

Human vs. CPU Analysis

CPU’s provide a fairly consistent gameplay that help to show how strong certain players are. In this case, we only have two players that have played against the CPU to provide accurate data. But the evidence still shows how much better Preston is than any individual.

Player Opponent Games Wins Losses Win_Perc GoalsPG ShotsPG Shot_Eff GAgainst Goal_Differential
CPU Preston 78 3 75 0.038 0.540 3.631 0.152 2.983 -2.443
CPU Matt 135 42 93 0.311 0.941 5.558 0.169 1.750 -0.809

Stadium Analysis

Stadium Scatter

During gameplay, it strongly appears that some goals are different sizes than others. This analysis was designed to show if there really was any statistically significant difference in each stadium.

Disappointingly, there was no significant difference by stadium when comparing goals and shots per two minutes. Although, there is some variance to be aware of when comparing their goal averages.

Stadium Stats

Stadium Games GoalsPerGame Shot_Efficiency ShotsPerGame
Crater 202 1.961 0.227 8.556
Pipeline 212 1.700 0.222 7.632
Underground 344 1.569 0.188 8.187
Konga 418 1.534 0.190 7.926
Bowser 322 1.497 0.183 8.092
Battle Dome 158 1.486 0.182 8.041
Palace 318 1.333 0.171 7.716

Using this table, it does appear there is some variance between the stadiums. Crater easily has the best shot efficiency and goals per game while Palace has the lowest in both categories. It may be interesting to test this theory further with longer length games to gain a better picture of the difference in the stadiums.

Wins vs. Losses

Players that win have different ways of playing to those that lose. Let’s look at how shot per two minutes and goals relate for games where a player wins vs when a player loses. The first visual shows losses while the second shows a graphic for wins based.

Losses

Wins

While wins show some consistency, losses, particularly between 0 and 1 goal per minute, show significant differences in how goals are scored. There appears to be little relationship between shots and goals in this interval.

Summary of Analysis

Based on the research conducted thus far, there is little to conclude on the influence of goals. We have been able to determine that stadiums have no statistically significant impact on goal scoring. The stat most connected with goal scoring throughout research was shown to be shot efficiency, but it has yet to be determined what makes an individual more efficient with their shots.

Other Graphics Created During Analysis

Goal Frequency

This bar graph shows the frequency of goals scored in a game.

Wins Goal Frequency

This bar graph shows the frequency of goals based on wins.

Losses Goal Frequency

This bar graph shows the frequency of goals based on losses.

Player Goals Box

The following shows a box plot of goals scored by players. Unsurprisingly, Preston’s box extends much further than the other players due to his goal scoring prowess.

Stadium Goals Box

This boxplot shows the data of goals scored by stadium. Interesting, the box plot for Crater field extends much further than any of the other boxes shown indicating there may be some impact on number of goals scored in that stadium.