Welcome to episode 3 of “Balls Deep”, where I will be introducing some advanced statistics for those who share my same passion for numbers. Keep in mind, these numbers are the result of a fairly small sample size (18 games out of a 60 game seasons, or 30% of the total season’s length). I have always found statistics interesting, especially when you can really dig down and find some underlining correlations that aren’t necessarily evident at initial glance. So, within this edition, I shall try to illuminate a few statistics that I have found of particular interest thus far. Firstly, I must emphasize a general disclaimer that stats can often be misinterpreted, and in no way is this an attempt to denounce anyone (or toot my own horn). I have to thank the Collective’s Mike Connor for his unparalleled expertise with Excel and coding to make these analyses possible. Let’s begin.
Points Per Game
Points per game (henceforth referred to as PPG) is one of the most used statistics to assess individual player performance. It is particularly useful because it takes into consideration missed games, whereas a gross point total does not. For those unaware, PPG is a simple division of total points by number of games played. In the table below, you will find ten players with the highest PPG.
| Rank | Team | Name | GP | G | 1A | 2A | Pts | GPG | 1APG | 2APG | PPG |
| 1 | Sasquatches | Marc | 12 | 17 | 18 | 4 | 39 | 1.42 | 1.50 | 0.33 | 3.25 |
| 2 | Baton Rouge | Ray | 15 | 25 | 19 | 4 | 48 | 1.67 | 1.27 | 0.27 | 3.20 |
| 3 | Flying Elbows | Troy | 15 | 16 | 14 | 8 | 38 | 1.07 | 0.93 | 0.53 | 2.53 |
| 4 | Sasquatches | Bobby | 18 | 27 | 14 | 4 | 45 | 1.50 | 0.78 | 0.22 | 2.50 |
| 5 | Flying Elbows | Justin | 18 | 22 | 14 | 6 | 42 | 1.22 | 0.78 | 0.33 | 2.33 |
| 6 | Baton Rouge | Brent | 18 | 21 | 15 | 5 | 41 | 1.17 | 0.83 | 0.28 | 2.28 |
| 7 | Collective | Mike M. | 15 | 14 | 10 | 7 | 31 | 0.93 | 0.67 | 0.47 | 2.07 |
| 8 | Flying Elbows | Jamie | 18 | 21 | 8 | 8 | 37 | 1.17 | 0.44 | 0.44 | 2.06 |
| 9 | Flying Elbows | Tim | 18 | 14 | 16 | 6 | 36 | 0.78 | 0.89 | 0.33 | 2.00 |
| 10 | Big D | Andrew | 12 | 13 | 7 | 3 | 23 | 1.08 | 0.58 | 0.25 | 1.92 |
To no surprise, perennial MVP Marc Guitard currently sets the PPG standard. Year after year, Guitard seems to find a way to be the frontrunner in nearly all offensive categories. Troy Doyle is off to a fantastic start as a dedicated defenceman for Tim’s Flying Elbows.
Goals Per Game
Goals per game (GPG) is another common means of determining individual player performance. Again, it takes into consideration missed games. Due to its sensitivity to games played, the statistic can sometimes be inflated; however, it is safe to assume that our sample size is adequately large to interpret the results. In the table below, you will find the league’s top ten players in GPG.
| Rank | Team | Name | GP | G | 1A | 2A | Pts | GPG | 1APG | 2APG | PPG |
| 1 | Baton Rouge | Ray | 15 | 25 | 19 | 4 | 48 | 1.67 | 1.27 | 0.27 | 3.20 |
| 2 | Sasquatches | Bobby | 18 | 27 | 14 | 4 | 45 | 1.50 | 0.78 | 0.22 | 2.50 |
| 3 | Sasquatches | Marc | 12 | 17 | 18 | 4 | 39 | 1.42 | 1.50 | 0.33 | 3.25 |
| 4 | Baton Rouge | Sly | 9 | 12 | 2 | 3 | 17 | 1.33 | 0.22 | 0.33 | 1.89 |
| 5 | Sasquatches | Sean | 15 | 19 | 7 | 1 | 27 | 1.27 | 0.47 | 0.07 | 1.80 |
| 6 | Flying Elbows | Justin | 18 | 22 | 14 | 6 | 42 | 1.22 | 0.78 | 0.33 | 2.33 |
| 7 | Baton Rouge | Brent | 18 | 21 | 15 | 5 | 41 | 1.17 | 0.83 | 0.28 | 2.28 |
| 8 | Flying Elbows | Jamie | 18 | 21 | 8 | 8 | 37 | 1.17 | 0.44 | 0.44 | 2.06 |
| 9 | Big D | Andrew | 12 | 13 | 7 | 3 | 23 | 1.08 | 0.58 | 0.25 | 1.92 |
| 10 | Flying Elbows | Troy | 15 | 16 | 14 | 8 | 38 | 1.07 | 0.93 | 0.53 | 2.53 |
Although this table has some similar names, the order has indeed shuffled. It’s also worth pointing out that two rookies have cracked the top ten in GPG, as Sean (Sasquatches) and Sly (Baton Rouge) both find themselves off to hot starts.
% Goals and % Total Contribution
Alright, alright. I know I said in my introduction that these would be “advanced” statistics, and I have hardly given anything advanced to date. Well, let’s delve into something a little more complex. Mike and I have come up with two statistics that further explain a player’s worth to his team. Firstly, we have % Goals, which is the ratio of an individual’s total goals scored to his team’s total goals scored. This statistic basically sums up the player’s goal contribution to his team. Additionally, % Total Contribution refers to a player’s total points in relation to the total number of goals his team has scored. In other words, % Total Contribution expresses how often a player is involved in a goal (as the scorer, or an assister) that his team has scored. Obviously, the higher the number, the better. Let’s take a look at the top ten players in both of these statistical categories.
| Rank | Team | Name | GP | G | 1A | 2A | Pts | GPG | 1APG | 2APG | PPG | % Goal | % Total |
| 1 | Barrage | Collin | 18 | 19 | 9 | 1 | 29 | 1.06 | 0.50 | 0.06 | 1.61 | 36.54% | 55.7692% |
| 2 | Warriors | Denis | 18 | 18 | 7 | 2 | 27 | 1.00 | 0.39 | 0.11 | 1.50 | 32.14% | 48.2143% |
| 3 | Sasquatches | Bobby | 18 | 27 | 14 | 4 | 45 | 1.50 | 0.78 | 0.22 | 2.50 | 30.68% | 51.1364% |
| 4 | Baton Rouge | Ray | 15 | 25 | 19 | 4 | 48 | 1.67 | 1.27 | 0.27 | 3.20 | 29.76% | 57.1429% |
| 5 | Collective | Mike M. | 15 | 14 | 10 | 7 | 31 | 0.93 | 0.67 | 0.47 | 2.07 | 25.45% | 56.3636% |
| 6 | Baton Rouge | Brent | 18 | 21 | 15 | 5 | 41 | 1.17 | 0.83 | 0.28 | 2.28 | 25.00% | 48.8095% |
| 7 | Flying Elbows | Justin | 18 | 22 | 14 | 6 | 42 | 1.22 | 0.78 | 0.33 | 2.33 | 22.92% | 43.7500% |
| 8 | Shooters | Joel | 15 | 11 | 6 | 2 | 19 | 0.73 | 0.40 | 0.13 | 1.27 | 22.92% | 39.5833% |
| 9 | Flying Elbows | Jamie | 18 | 21 | 8 | 8 | 37 | 1.17 | 0.44 | 0.44 | 2.06 | 21.88% | 38.5417% |
| 10 | Sasquatches | Sean | 15 | 19 | 7 | 1 | 27 | 1.27 | 0.47 | 0.07 | 1.80 | 21.59% | 30.6818% |
| Rank | Team | Name | GP | G | 1A | 2A | Pts | GPG | 1APG | 2APG | PPG | % Goal | % Total |
| 1 | Baton Rouge | Ray | 15 | 25 | 19 | 4 | 48 | 1.67 | 1.27 | 0.27 | 3.20 | 29.76% | 57.1429% |
| 2 | Warriors | James | 18 | 12 | 9 | 11 | 32 | 0.67 | 0.50 | 0.61 | 1.78 | 21.43% | 57.1429% |
| 3 | Collective | Mike M. | 15 | 14 | 10 | 7 | 31 | 0.93 | 0.67 | 0.47 | 2.07 | 25.45% | 56.3636% |
| 4 | Barrage | Collin | 18 | 19 | 9 | 1 | 29 | 1.06 | 0.50 | 0.06 | 1.61 | 36.54% | 55.7692% |
| 5 | Collective | Rick B. | 18 | 10 | 12 | 8 | 30 | 0.56 | 0.67 | 0.44 | 1.67 | 18.18% | 54.5455% |
| 6 | Sasquatches | Bobby | 18 | 27 | 14 | 4 | 45 | 1.50 | 0.78 | 0.22 | 2.50 | 30.68% | 51.1364% |
| 7 | Baton Rouge | Brent | 18 | 21 | 15 | 5 | 41 | 1.17 | 0.83 | 0.28 | 2.28 | 25.00% | 48.8095% |
| 8 | Warriors | Denis | 18 | 18 | 7 | 2 | 27 | 1.00 | 0.39 | 0.11 | 1.50 | 32.14% | 48.2143% |
| 9 | Shooters | Harold | 18 | 7 | 11 | 4 | 22 | 0.39 | 0.61 | 0.22 | 1.22 | 14.58% | 45.8333% |
| 10 | Sasquatches | Marc | 12 | 17 | 18 | 4 | 39 | 1.42 | 1.50 | 0.33 | 3.25 | 19.32% | 44.3182% |
Let’s discuss the findings. In terms of % Goals, Collin Sleep of the Barrage is the most influential player in his team’s success. Collin scores over 36% of the team’s goals by himself, and when assists are factored in, he finds himself involved in 56% of the Barrage’s goals. Some other impactful players are Denis Loubert (32% of the Warriors’ goals), Bobby Woods (31% of the Sasquatches’ goals), and Mike Moore (25% of Collective’s goals).
When looking at % Total Contribution, we are greeted by an absolutely astounding statistic. In an extreme example of unlikelihood, we find that Ray Chase (Baton Rouge) and James Campbell (Warriors) find their names on the score sheet in exactly 57.1429% (yes, identical to the 4th decimal point) of their respective teams’ goals. Some other players, league-wide, that play significant offensive roles on their teams are Mike Moore (56%), Rick Bartlett (55%), and Bobby Woods (51%). Basically, this statistic reveals some primary targets on teams to shut down. There appear to be a good chunk of players that are involved on half of their teams’ goals!
% of Goals With 2As
In an act of sheer boredom, we decided to analyze the proportion of each team’s total goals scored that involved both primary and secondary assists. This statistic is useful in determining which teams tend to move the ball around well (a high percentage of their goals involve secondary assists), and which teams tend to score on transition (a low percentage of goals that include secondary assists). To create this stat, we took the total number of goals a team has scored, and divided it by the sum of all corresponding players’ secondary assists. The results are summarized below.
| Team | Secondary Assists | Goals For | % Goals w/ 2A |
| Collective | 28 | 55 | 51% |
| Flying Elbows | 47 | 96 | 49% |
| Warriors | 27 | 56 | 48% |
| Barrage | 23 | 52 | 44% |
| Big D | 27 | 62 | 44% |
| Baton Rouge | 33 | 84 | 39% |
| Shooters | 15 | 48 | 31% |
| Sasquatches | 24 | 88 | 27% |
The results suggest the Collective (51%), the Flying Elbows (49%), and the Warriors (48%) are the savviest teams, in terms of ball movement. They include secondary assists on half of their team’s total goals, which indicates the ball changes player possession several times before scoring attempts are made. These teams are difficult to defend against, due to the variety of players involved in each scoring play. It is no surprise that the top two teams include well-known playmakers such as Rick Bartlett (Collective), and Tim O’Leary (Flying Elbows). Coincidentally, these two players enjoy their stats, as well.
Well that about sums up the third rendition of “Balls Deep.” Hopefully these statistics provided some more detail to the current league scoring situation. For everyone’s enjoyment, I have included the statistics for everyone in the league in the table below.
| Name | GP | G | 1A | 2A | Pts | GPG | 1APG | 2APG | PPG | % Goals | % Total |
| Marc | 12 | 17 | 18 | 4 | 39 | 1.42 | 1.50 | 0.33 | 3.25 | 19.32% | 44.3182% |
| Ray | 15 | 25 | 19 | 4 | 48 | 1.67 | 1.27 | 0.27 | 3.20 | 29.76% | 57.1429% |
| Troy | 15 | 16 | 14 | 8 | 38 | 1.07 | 0.93 | 0.53 | 2.53 | 16.67% | 39.5833% |
| Bobby | 18 | 27 | 14 | 4 | 45 | 1.50 | 0.78 | 0.22 | 2.50 | 30.68% | 51.1364% |
| Justin | 18 | 22 | 14 | 6 | 42 | 1.22 | 0.78 | 0.33 | 2.33 | 22.92% | 43.7500% |
| Brent | 18 | 21 | 15 | 5 | 41 | 1.17 | 0.83 | 0.28 | 2.28 | 25.00% | 48.8095% |
| Mike M. | 15 | 14 | 10 | 7 | 31 | 0.93 | 0.67 | 0.47 | 2.07 | 25.45% | 56.3636% |
| Jamie | 18 | 21 | 8 | 8 | 37 | 1.17 | 0.44 | 0.44 | 2.06 | 21.88% | 38.5417% |
| Tim | 18 | 14 | 16 | 6 | 36 | 0.78 | 0.89 | 0.33 | 2.00 | 14.58% | 37.5000% |
| Andrew | 12 | 13 | 7 | 3 | 23 | 1.08 | 0.58 | 0.25 | 1.92 | 20.97% | 37.0968% |
| Sly | 9 | 12 | 2 | 3 | 17 | 1.33 | 0.22 | 0.33 | 1.89 | 14.29% | 20.2381% |
| Sean | 15 | 19 | 7 | 1 | 27 | 1.27 | 0.47 | 0.07 | 1.80 | 21.59% | 30.6818% |
| James | 18 | 12 | 9 | 11 | 32 | 0.67 | 0.50 | 0.61 | 1.78 | 21.43% | 57.1429% |
| Matt Vautour | 18 | 14 | 12 | 5 | 31 | 0.78 | 0.67 | 0.28 | 1.72 | 16.67% | 36.9048% |
| Rick B. | 18 | 10 | 12 | 8 | 30 | 0.56 | 0.67 | 0.44 | 1.67 | 18.18% | 54.5455% |
| Bruno | 12 | 12 | 5 | 3 | 20 | 1.00 | 0.42 | 0.25 | 1.67 | 19.35% | 32.2581% |
| Collin | 18 | 19 | 9 | 1 | 29 | 1.06 | 0.50 | 0.06 | 1.61 | 36.54% | 55.7692% |
| Vince | 18 | 11 | 8 | 9 | 28 | 0.61 | 0.44 | 0.50 | 1.56 | 11.46% | 29.1667% |
| Brian | 18 | 8 | 15 | 5 | 28 | 0.44 | 0.83 | 0.28 | 1.56 | 8.33% | 29.1667% |
| Denis | 18 | 18 | 7 | 2 | 27 | 1.00 | 0.39 | 0.11 | 1.50 | 32.14% | 48.2143% |
| Jim | 12 | 7 | 10 | 1 | 18 | 0.58 | 0.83 | 0.08 | 1.50 | 12.73% | 32.7273% |
| Joel | 15 | 11 | 6 | 2 | 19 | 0.73 | 0.40 | 0.13 | 1.27 | 22.92% | 39.5833% |
| Craig | 15 | 11 | 5 | 3 | 19 | 0.73 | 0.33 | 0.20 | 1.27 | 21.15% | 36.5385% |
| Darren | 12 | 8 | 5 | 2 | 15 | 0.67 | 0.42 | 0.17 | 1.25 | 9.09% | 17.0455% |
| Harold | 18 | 7 | 11 | 4 | 22 | 0.39 | 0.61 | 0.22 | 1.22 | 14.58% | 45.8333% |
| Carl | 18 | 11 | 8 | 3 | 22 | 0.61 | 0.44 | 0.17 | 1.22 | 20.00% | 40.0000% |
| Mike D. | 9 | 6 | 3 | 2 | 11 | 0.67 | 0.33 | 0.22 | 1.22 | 12.50% | 22.9167% |
| Rakesh | 9 | 2 | 3 | 6 | 11 | 0.22 | 0.33 | 0.67 | 1.22 | 3.23% | 17.7419% |
| Steve | 18 | 2 | 11 | 8 | 21 | 0.11 | 0.61 | 0.44 | 1.17 | 2.38% | 25.0000% |
| Mike C. | 18 | 8 | 7 | 5 | 20 | 0.44 | 0.39 | 0.28 | 1.11 | 14.55% | 36.3636% |
| Jon | 18 | 10 | 8 | 2 | 20 | 0.56 | 0.44 | 0.11 | 1.11 | 17.86% | 35.7143% |
| Jeremy | 18 | 11 | 8 | 1 | 20 | 0.61 | 0.44 | 0.06 | 1.11 | 17.74% | 32.2581% |
| Tyson | 9 | 4 | 2 | 4 | 10 | 0.44 | 0.22 | 0.44 | 1.11 | 6.45% | 16.1290% |
| Ian | 12 | 9 | 4 | 0 | 13 | 0.75 | 0.33 | 0.00 | 1.08 | 14.52% | 20.9677% |
| Mike L. | 15 | 3 | 9 | 4 | 16 | 0.20 | 0.60 | 0.27 | 1.07 | 5.36% | 28.5714% |
| Matt Vaillanc. | 15 | 8 | 5 | 3 | 16 | 0.53 | 0.33 | 0.20 | 1.07 | 9.52% | 19.0476% |
| Wayne | 18 | 10 | 8 | 1 | 19 | 0.56 | 0.44 | 0.06 | 1.06 | 19.23% | 36.5385% |
| Mike C. | 10 | 7 | 3 | 0 | 10 | 0.70 | 0.30 | 0.00 | 1.00 | 12.50% | 17.8571% |
| Rob | 3 | 2 | 1 | 0 | 3 | 0.67 | 0.33 | 0.00 | 1.00 | 4.17% | 6.2500% |
| Jamie | 18 | 2 | 9 | 6 | 17 | 0.11 | 0.50 | 0.33 | 0.94 | 3.85% | 32.6923% |
| Ben | 13 | 2 | 4 | 6 | 12 | 0.15 | 0.31 | 0.46 | 0.92 | 3.23% | 19.3548% |
| Wyatt | 18 | 6 | 5 | 5 | 16 | 0.33 | 0.28 | 0.28 | 0.89 | 11.54% | 30.7692% |
| Scott | 18 | 3 | 7 | 6 | 16 | 0.17 | 0.39 | 0.33 | 0.89 | 3.41% | 18.1818% |
| Darryl | 12 | 3 | 5 | 2 | 10 | 0.25 | 0.42 | 0.17 | 0.83 | 5.77% | 19.2308% |
| Larry | 15 | 4 | 5 | 3 | 12 | 0.27 | 0.33 | 0.20 | 0.80 | 7.14% | 21.4286% |
| Travis | 18 | 4 | 5 | 4 | 13 | 0.22 | 0.28 | 0.22 | 0.72 | 4.17% | 13.5417% |
| Scott M. | 15 | 2 | 6 | 2 | 10 | 0.13 | 0.40 | 0.13 | 0.67 | 4.17% | 20.8333% |
| Bryan | 18 | 2 | 5 | 5 | 12 | 0.11 | 0.28 | 0.28 | 0.67 | 2.27% | 13.6364% |
| Chris | 15 | 6 | 2 | 1 | 9 | 0.40 | 0.13 | 0.07 | 0.60 | 12.50% | 18.7500% |
| Phil | 18 | 1 | 4 | 5 | 10 | 0.06 | 0.22 | 0.28 | 0.56 | 1.79% | 17.8571% |
| Rick H. | 9 | 2 | 2 | 1 | 5 | 0.22 | 0.22 | 0.11 | 0.56 | 3.64% | 9.0909% |
| Yvon | 18 | 2 | 3 | 4 | 9 | 0.11 | 0.17 | 0.22 | 0.50 | 4.17% | 18.7500% |
| Rene | 18 | 1 | 2 | 5 | 8 | 0.06 | 0.11 | 0.28 | 0.44 | 1.19% | 9.5238% |
| Greg | 15 | 2 | 2 | 2 | 6 | 0.13 | 0.13 | 0.13 | 0.40 | 2.27% | 6.8182% |
| Evan | 18 | 2 | 2 | 3 | 7 | 0.11 | 0.11 | 0.17 | 0.39 | 3.64% | 12.7273% |
| Trevor | 15 | 0 | 1 | 4 | 5 | 0.00 | 0.07 | 0.27 | 0.33 | 0.00% | 9.6154% |
| Jeff | 15 | 0 | 1 | 4 | 5 | 0.00 | 0.07 | 0.27 | 0.33 | 0.00% | 8.0645% |
| Dave | 17 | 0 | 0 | 1 | 1 | 0.00 | 0.00 | 0.06 | 0.06 | 0.00% | 1.9231% |
| Tony | 18 | 0 | 1 | 0 | 1 | 0.00 | 0.06 | 0.00 | 0.06 | 0.00% | 1.7857% |
| Brandon | 18 | 0 | 0 | 1 | 1 | 0.00 | 0.00 | 0.06 | 0.06 | 0.00% | 1.0417% |
| Frederik | 18 | 0 | 0 | 0 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00% | 0.0000% |
| Christian | 2 | 0 | 0 | 0 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00% | 0.0000% |
| Mark | 15 | 0 | 0 | 0 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00% | 0.0000% |
| Rick | 18 | 0 | 0 | 0 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00% | 0.0000% |
| Paul | 18 | 0 | 0 | 0 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00% | 0.0000% |
