Lucky or Good? Analyzing NPL Teams by Circle Favor

Figure 1: Total points per match for each NPL team based on circle favor.

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Following the NPL this year, I’ve noticed a lot of interesting discussion of circle favor. We know that the circle can drive the outcome of matches, because its random placement benefits some teams over others just by chance, but we don’t know what the impact really is.

I’ve also seen people saying that luck, and primarily circle luck, plays too much of a role in this esport for it to be viable long-term – and others saying that good teams still reliably rise to the top.

I was curious about the actual impact of circle favor on competitive matches, so I did some number-crunching for the Phase 2 matches so far, to figure out:

1) how much of a role circle favor plays in determining the outcome of matches, and

2) which teams consistently outperform or underperform their circle favor.

At the end I discuss some of the limitations of what I’ve done here – I haven’t taken into account the plane path, for example, and I’d welcome other comments or suggestions. If people find this interesting, I can update it as the weeks go on.

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QUESTIONS AND RESULTS ​ 1) What effect does circle favor actually have on the outcome of matches? First, I want to make sure that team performance actually is related to circle favor. For every team in every match in Phase 2 so far, I compared the points they earned to the proportion of circles that favored them (see below for how I recorded the data). Circle favor is significantly but weakly positively correlated with average points per match (Pearson’s r = 0.32, p < 1 x 10-6) Cool, we’re all right that luck does play a role in match outcomes. Next, I ran a linear regression to find the actual effect of circle favor on points in a match. Circle favor is responsible for ~10% of the variation between teams in points earned per match (R2 = 0.0993, p < 1 x 10-6). Put another way, around one tenth of the differences in team success can be explained by circle favor alone. If a team goes out in circle 5, like most teams do, getting just one more good circle out of those 5 (so 3 favorable circles instead of 2, or 2 instead of 1), translates to 1.2 more points on average. Because it’s a proportional measure, if they go out in circle 9 they need ~2 more circles to get the same boost in points. ​ 2) Which teams consistently do better than expected given their circle luck? To find which teams tend to outperform or underperform their luck, I visualized the relationship between teams’ average points in a match and their circle favor. Figure 2: Changes in total points per match for each NPL team based on circle favor from Week 1 to Week 2. Figure 3: Kill points per match for each NPL team based on circle favor. Figure 4: Placement points per match for each NPL team based on circle favor. How to interpret these graphs? The x axis is the proportion of circles which were favorable out of all the circles a team was alive for, and the y axis is the average points per match, both overall (figures 1 and 2) and subdivided into kill points (3) and placement points (4). Teams with low circle favor can be found on the left; teams with high circle favor are on the right. The horizontal line is the mean points per match (5.6) in figures 1 and 2, and mean kill points (3.6) and placement points (2.0) per match in figures 3 and 4. The vertical line is the mean proportion of favorable circles – the circle tends to favor teams 42% of the time on average. The line running diagonally through the graph is the linear model of the relationship between these variables – the expected points for each level of circle favor for all teams in all matches. Teams that are above this line are performing better than expected for their circle favor, relative to the other teams. Teams below this line are underperforming. The gray lines running parallel to this line represent half a standard deviation in points per match from the expected value of points per match. Teams that are above or below this line are really over- or underperforming. Some interesting takeaways: C9 has had the most circle favor, and BMG the least. The teams which are performing best and worst overall have absolutely average circle favor, which illustrates the limited role of circle luck. Endemic is getting way better placement than their circle favor would predict (figure 3), which might reflect good positioning skill. C9 are underperforming their circle luck in terms of placement, but overperforming in terms of kill points, which seems to be a reflection of a more aggressive play style that leads to more kills but also to more lost team members. A lot of credit for these charts goes to Micah Blake McCurdy of hockeyviz, whose Corsi For charts for the NHL were the inspiration for this. I don’t mean to imply that what I’m doing is on the same level, but I think his charts really clearly convey the information graphically, so I used a lot of the same elements. ​