Login

juke · 07-14-2022, 05:06 PM

Heads up, I would probably not try to load this page on mobile

With the FHM6 at a close and the site moving on to the new FHM8 sim, I thought I would compile some team and player stats from the past 13 seasons of our beloved sim. I was hoping I could explore some niche random stats, like what player had the highest ratio of shots blocked compared to shot attempts against (Troy McClure III in S53 with 27.1%), or who had the highest career shooting percentage for players with more than 500 SOG (Jimmy Larkin-Conway at 14.3%) or the best takeaway to giveaway differential (Collin Gibbles with 596, 403, +193). But in the end this just wound up being a bunch of glorified top 10 lists, and I ended up too burnt out to look into anything more in depth. But feel free to suggest any sort of random stat for a team/player/in general and I can get around to looking it up. I’m not trying to write too much so just gonna jump straight to the graphs.

As a side note, I could make these same graphs for SMJHL, and in theory IIHF and WJC, so if anyone wants to write up a version for those, shoot me a message on discord and I’ll send them to you and you can have all the money for it.

Team stats

The first graph is essentially a running tally of each team’s record throughout the entirety of the 13 seasons of FHM. The dotted lines represent the actual season breaks. The average team got 1.064 points per game (more than 1 due to OT points). So basically, after 100 games, the average team would have 106 points, after 200 games, 212 points, etc. So this is just a visualization of how many games above/below league average each team was along each game. Keep in mind that this is over the entire duration of FHM, so teams could have put together very strong individual seasons, but still be below the line due to past records. I don’t think the results will really be surprising to anyone who’s paid attention to the standings at all. Also I’d like to thank like half the league for having nearly identical primary colors and making this graph harder to follow.

[Image: unknown.png?width=950&height=586]

I also made the following graph, which is the same thing except it starts the expansion teams at the same origin at the rest of the teams, which gives a better idea of how their trends stack up to the league for their existence.

[Image: unknown.png?width=950&height=586]

The next graph is similar to the above ones, but I prefer it more since you can kind of digest season-by-season results of each team. Each tiny line is one game for each team, and its value is the goal differential for that game. I think it’s better because you can isolate team success without having to account for past results. You can start to see where rebuilds started and teams turned the corner more.

[Image: unknown.png?width=794&height=586]

[Image: unknown.png?width=794&height=586]

The highest single game differential was 12 which happened 5 times: BUF vs. TBB in S56, CHI vs. WPG in S62, HAM vs. WPG in S61, BAP vs. WPG in S61, and NOL vs. MIN in S62. The most goals scored by a team in one game was 13 (CHI vs. WPG in S62). The most combined goals in one game was 17 in a MIN 12-5 victory over WPG in S63. On the opposite end of the spectrum, there were 9 games that ended with no goals scored; 0-0 throughout both regulation and OT and were only decided in a shootout.

The next 3 graphs show a few team underlying stats over time. Corsi-for vs. corsi-against, CF% vs. PDO, and a standard goals for vs. goals against. The corsi stat averages are a best-guess estimation, since the index doesn’t have team stats for those but rather only player stats. And it’s impossible to tell if a corsi event was even strength or special teams which affects the final calculation. And also if a player was traded, all their corsi events on their old team count for their new team on the index. But it’s close enough over the course of 13 seasons I think. And instead of grouping them by the FHM6 era in general, they’re segmented by season, so you can pick a team and watch its dot fly around for 13 seasons. In each case, the dotted lines represent league average for each season.

[Image: corsi_chart.gif]

One thing that always stuck out to me in these graphs is that there was little to no distinction between offensive and defensive specialties. I was hoping there may be some sort of scatter going on, where certain terms scored a lot of goals but also let a lot in, or teams that played boring trap low-event games. But in the end, the reality was that the teams that scored a lot of goals also let in less goals and won more games. It was all mostly linear.

I also compiled each team’s GF and GA per game over the course of FHM6 into one graph below.

This isn’t as informative or specific as the season-by-season version above, but it does show a bit more of the scatter I was hoping for. For example, that middle grouping of teams has distinctions between offensive leaning vs. defensive leaning teams. And TEX scored goals at a rate basically equal to PHI/ATL/EDM, but let up 0.5 less goals per game. But at the end of the day, it’s still not overly helpful when it’s a lot of grouped data that’s averaged together, since season to season results for each team can vary significantly.

And to wrap up our FHM6 team stats, this is a heatmap below that shows every team’s record against the rest of the league. To read it, pick a team listed on the left side, find a corresponding team on the top, then the color of the tile represents the team on the left’s combined points percentage vs. the team on the top.

[Image: unknown.png?width=726&height=587]

The highest inter-team points percentages throughout FHM6 were:

HAM vs. MIN (26-1-0, 96.3%)

BUF vs. WPG (25-1-1, 94.4%)

TBB vs. MTL (22-1-1, 93.8%)

BUF vs. MTL (33-2-1, 93.1%)

4 matchups were tied for 5th (12-1, 92.3%)

Skater career stats

Moving on, I took a look at the league leaders in a few of our counting stats (points, goals, assists, hits, SB, takeaways, and fantasy scoring) throughout the course of the last 13 seasons. For each season, a new top 10 is generated based on the current leaders and is separated by position group.

A few notes about the graphs. I had to separate career stats by positional group. So for example, only goals scored by a player during a season they were a defenseman would count towards their defensive career totals/leaders. Without doing this, there were some players that switched from F to D, and instantly became the ‘defenseman’ leader in points/goals. And the opposite for some D -> F that became the instant SB leaders. So the number by a player’s totals might not reflect their actual career totals if they position swapped.

And secondly, I had to put blank seasons before S53 or else the loop back to the start got really weird, and I also put two blank seasons at the end so the final results would stay on the screen for more than a few frames. But I had to call them an actual season, which is why the graphs start on S52 and end on S66/67, despite those seasons not being FHM6 seasons. Just ignore those labels.

[Image: points.gif?width=880&height=587]

[Image: assists.gif?width=880&height=587]

[Image: takeaways.gif?width=880&height=587]

[Image: fantasy.gif?width=880&height=587]

I didn’t realize the margins on some of these got messed up until now and I’m too lazy to fix at this point. Not really much for me to explain that the graphs don’t do for me. Not overly shocking to see a lot of HAM/BUF/CHI players in the top 10 lists for the scoring stats, as they were the teams with the 3 best records and 3 highest GF/game. I would assume most of the FHM6 leaders aren’t really new information, especially with the Asron bot command in every LR, but it’s fun to see it over time. Maybe you lead the league in a stat for a few seasons before you retired or regressed too hard and wouldn’t have otherwise known.

Skater single season stats

And to highlight some of the players who popped off for a single season but might not have sustained it throughout their careers, or maybe just don’t have the longevity to crack the career FHM leaders, here are the top 10 single-season highs for the same above stats.

Note: Since there were a few seasons played with only 50 games, the single-season highs were normalized per game, and adjusted to the 66 game pace that we played the majority of FHM6 in.

Again, not a ton of surprises in a lot of the top 10 scoring lists, but it’s nice to give some of the 50 game era players their adjusted paces. Fluw just barely beat Wilson for the single season assist record this past season, but he needed one more to pass former teammate Westbroek’s S54 total for the assists/game record. Juni Panda will go down as FHM6’s most feared hitter, securing the #1 and #2 single season ranking by over 50 hits, as well as another season where he had the 9th most hits among forwards. I already briefly mentioned that Gibbles had FHM6’s best takeaway to giveaway differential, which is not surprising after seeing that he has the 4 of the 5 highest single season takeaways among forwards, as well as 8th most too. His adjusted pace of nearly 90 takeaways in 66 games in S55 is over 20 more takeaways than any other single season amount.

Goalie career stats

I’ve often not included goalie stats in past media, so decided to give them some attention in this one too. Basically the same thing, running career stats of some of the main counting stats; wins, saves, shutouts. I also tried to do a running tally of top 10 career save percentage since that’s the goalie stat the majority of people would agree is the most team-independent in FHM. I couldn’t figure out how to get the axis for it to be specific to the save percentage range, so ignore the bar sizes and just pay attention to the order. This one was kind of weird since unlike all the other stats, career save percentage can actually go down each season. As a note, I think I had a filter for GP above 30 in each season which is probably too exclusive in hindsight, but oh well.

[Image: savepct.gif?width=880&height=587]

Goalie single season stats

And finally to wrap up the regular season section, the single season goalie leaders for the same categories. Same 30 game filter applies.

I’m getting tired of writing at this point, so just going to point out that Redacted is a machine who holds the 1, 3, 4, 5, 6, and 7th spots for most saves in a season, as well as the goalie duel in S58 between Soonika and Doyle who both had 13 shutouts, nearly one shutout in every 4 GP.

Team playoff stats

There wasn’t much I felt was worth doing for team stats for the playoffs, since the results would be a bit skewed based on some teams playing way more/less playoff games than others, and stats would be matchup dependent. Teams that consistently made deep runs would have also played a higher percentage of the best teams as well. In the end, I settled for a similar ‘points percentage’ matrix, and the team average playoffs GF and GA per game.

To read the matchup heatmap, it’s similar to the regular season one. Take a team from the left side, find an opponent at the top, and the color indicates how many playoff series wins the team on the left has against the team at the top. If you wanted to find their overall record against that team, you would then have to do the opposite, switch the teams from the left and top and then find out how many wins the opponent had. The teams should be sorted from top to bottom/left to right based on total number of FHM6 playoff series wins.

[Image: unknown.png?width=694&height=587]

It’s no surprise that our #1 and #2 FHM6 teams (via combined regular season records) ended up with the most and 2nd most playoff series wins as well. In fact, their consistently deep playoff runs had them meeting 11 times in the postseason – 85% of all FHM6 seasons. The #1 Steelhawks came out ahead of the #2 Stampede to a final post-season record of 8-3. However BUF then in turn vented their frustrations out of the #3 Syndicate (again via combined regular season records), to a tune of a 5-1 post-season record, including a reverse sweep and a 1-3 cup finals comeback. While there were overall a few playoff upsets throughout the 13 seasons, the overall order and ranking of total playoff series wins matches the regular season records very closely. It’s not surprising, but I think a bit more playoff chaos would’ve been exciting.

The average playoff scoring graph was probably not worth making. A lot of the teams have similar rankings to their regular season trends, but also the graph isn’t super fair to some of the rebuilding teams, who snuck into playoffs for a year or two just to have to face a 50+ win #1 seed. And then due to sample size they didn’t get enough series to try to normalize their stats a bit. But here it is regardless.

Playoff skater career stats

At this point I’m sick of writing, so I’m going to just drop the rest of the graphs without talking about them. They’re the same career stats over time, as well as single-season highs from the regular season. The same rules apply to the career stats – they were only counted for a player while they were playing within that positional group, and they have the same blank seasons before and after the actual stats.

[Image: po_points.gif?width=880&height=587]

[Image: po_goals.gif?width=880&height=587]

[Image: po_assists.gif?width=880&height=587]

[Image: po_hits.gif?width=880&height=587]

[Image: po_takeaways.gif?width=880&height=587]

Playoff skater single-season stats

Single-season highs this time were raw values and not normalized to GP – I figured we wouldn’t be that interested in someone who got 3 goals in a 4 game sweep being called the single season playoff goal leader.