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@@ -16,13 +16,17 @@ ggplot(allfouls, aes(x=SCOREMARGIN_CORR)) +
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scale_y_log10() +
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xlab("Score Margin") + ylab("N Fouls")
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dev.off()
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-
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+median(allfouls$SCOREMARGIN_CORR)
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+mean(allfouls$SCOREMARGIN_CORR)
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+sd(allfouls$SCOREMARGIN_CORR)
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# histogram of fouls as a function of corrected score margin,
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# ignoring overtime and the final minute of regular play
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earlyfouls <- filter(allfouls,
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PERIOD <= 4,
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!(PERIOD == 4 & PCTIMESTRING < "00:01:00"))
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-
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+median(earlyfouls$SCOREMARGIN_CORR)
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+mean(earlyfouls$SCOREMARGIN_CORR)
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+sd(earlyfouls$SCOREMARGIN_CORR)
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png('figures/foul_histogram-regular_nofinalmin.png')
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ggplot(earlyfouls, aes(x=SCOREMARGIN_CORR)) +
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geom_histogram(binwidth=1, fill="red", alpha=0.5) +
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@@ -32,6 +36,22 @@ ggplot(earlyfouls, aes(x=SCOREMARGIN_CORR)) +
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geom_histogram(data=allfouls, binwidth=1, fill="green", alpha=0.5)
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dev.off()
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+# overtime fouls
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+overtimefouls <- filter(allfouls,
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+ PERIOD > 4)
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+median(overtimefouls$SCOREMARGIN_CORR)
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+mean(overtimefouls$SCOREMARGIN_CORR)
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+sd(overtimefouls$SCOREMARGIN_CORR)
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+png('figures/foul_histogram-overtime.png')
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+ggplot(overtimefouls, aes(x=SCOREMARGIN_CORR)) +
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+ geom_histogram(binwidth=1, fill="red", alpha=0.5) +
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+ theme_bw() +
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+ scale_y_log10() +
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+ xlab("Score Margin") + ylab("N Fouls") +
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+ geom_histogram(data=allfouls, binwidth=1, fill="green", alpha=0.5)
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+dev.off()
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+
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+
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# hexbin plots of fouls as a function of total score and corrected score
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# margin, separated by home and away teams
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png('figures/fouls_totalscore-hexbin-byhomevisitor.png', height=600, width=1200)
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