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Most of the lag that it currently attributed to P2P connections is actually the result of netcode issues, and most of the games are actually played on dedicated servers.Since we know that the host in P2P connections has an advantage compared to the other players, then if the pre-game session leader is actually the game host we should be able to detect the host advantage by accumulating enough post-game performance data to see if the session leader tends to perform better on average. If the pre-game session leader is not the host, then being listed as session leader confers no advantage, and the long-term performance of the session leader should be average. This lets us test both claims at the same time. So our null hypothesis, then, for our statistical test is:Null Hypothesis: Being listed as the pre-game session leader confers no in-game advantage (Frank O'Connor's implied claim).In order to reject the null hypothesis, we will require a confidence interval of 95%, which is fairly standard for engineering and scientific usage. In other words, we will not conclude that Frank's claim is false unless we arethat Frank's claim is, indeed, false.The data we will use comes from 42 consecutive attempts to play matches. No game attempts have been censored (lest we bias our data to the answer we think is "correct"). These 42 consecutive attempts led to 3 games in which P2P was confirmed via the pre-game session leader quitting and causing a host migration, 3 cases in which the pre-game session leader quit prior to the start of the match, but too late for the replacement session leader to be noted, and 3 sets of failed lobbies that required an MCC or Xbox restart to resolve. The data taken during the 33 remaining sessions was pre-game session leader GT, post-game GT score (in kills), post-game GT placement, GT own team kills, and opposing team kills.1. The data was centered such that the median placement was zero, better-than-median placement was positive, and lower-than-median placement was negative. In other words, for a 3v3 game, first place would be "3" and last place would be "-3". This was done to allow combining data from games with a differing number of participants.2. An additional data set was created using #1, but scaling the data such that first place was "1" and last place was "-1". This data set sacrifices sensitivity in favor of ensuring that a single outlier cannot unduly affect the outcome of the analysis.3. The data was centered such that the median number of kills was zero, better-than-median kills were positive, and lower-than-median kills were negative.4. An additional data set was created using #3, but scaling the data by dividing by the maximum number of kills achieved by any player in the match. This gives the player with the most match kills a "1". This was done for the same reason as #2 above.A. T-test: This tests whether the mean of the data is greater than zero with a confidence interval. Since our data is just a sample, the confidence intervals are necessary to avoid us accidentally reaching the wrong conclusion due to purely random factors. This was performed for all 4 data sets.B. Wilcoxon Signed Rank test: Since the data sets are not pulled from a Gaussian population (ask if you want an explanation), the T-test may yield erroneous results. To guard against this, the non-parametric Wilcoxon test was also performed. This test has the advantage that its results are valid for all distributions. It has the disadvantage that it is less sensitive than the T-test.Data set 1:The T-test yielded a 99.99999914% chance that the pre-game session leader has a real in-game advantage in terms of placement on the post-game leaderboard. The mean benefit is 1.75 places higher.The Wilcoxon test yielded a > 99% chance that the pre-game session leader has a real in-game advantage in terms of placement on the post-game leaderboard. The median benefit is also 1.75 places higher.Data set 2:The T-test yielded a 99.9999999306% chance that the pre-game session leader has a real in-game advantage in terms of placement on the post-game leaderboard. The mean benefit is (0.4876 * # players per team) places higher.The Wilcoxon test yielded a > 99% chance that the pre-game session leader has a real in-game advantage in terms of placement on the post-game leaderboard. The median benefit is (0.5000 * # players per team) places higher.Data set 3:The T-test yielded a 99.9% chance that the pre-game session leader has a real in-game advantage in terms of kills achieved in the game. The mean benefit is an additional 3.23 kills per game.The Wilcoxon test yielded a > 99% chance that the pre-game session leader has a real in-game advantage in terms of kills achieved in the game. The median benefit is an additional 2.88 kills per game.Data set 4:The T-test yielded a 99.99% chance that the pre-game session leader has a real in-game advantage in terms of kills achieved in the game. The mean is an additional (0.3527 * highest # of kills) kills per game.The Wilcoxon test yielded a > 99% chance that the pre-game session leader has a real in-game advantage in terms of kills achieved in the game. The median is an additional (0.3500 * highest # of kills) kills per game.It isthat the in-game session leader has no relationship to the host in a P2P game. This is a universal statement, and it applies to anyone who plays MCC. It is alsothat the lag I experience while gaming is due to poor netcode on dedicated servers. Rather, it is a near certainty that the lag I experience is P2P lag. This is a specific statement, that applies only to myself. It does demonstrate, however, that 343i’s statements about dedicated server availability do not necessarily apply to even players in North America who are located next to large population centers (I live about 1:30 from Chicago and 2:00 from Detroit along the I-94 corridor).