Cheap DIY Infinity Barrels & Terminals

I saw a bag of wooden spools at the craft store earlier this summer and decided that they would make great barrels for infinity.  The plan was to sticker them with patterns maybe from the containers I printed out and built.

First some primer.

Now I needed some art.  I looked through some downloads of various DIY terrain and found some good candidates.  I opened the PDFs in a graphics program and then scaled the images and cropped them to fit the dimensions I needed.

Here is the PDF I ended up with.  Print page 1 on full-page, peel-and-stick label paper.  Print page 2 on a card stock.

• DIY Infinity Barrels PDF (see the bottom of the post for art credits)
• Avery 8465 Shipping Labels (to print page 1 on)
• Wooden Spools (1" x 3/4")

Next step was to paint the parts of the spools that will not be covered by stickers -- the top and bottom edges.  Most got a coat of metallic paint.  Four got brown.

Next I cut out the stickers and applied them.  Plus a special touch for the four I wanted to turn into holo-terminals.


Here are some stills of the final results.

Huge thanks to TommyGun for developing the art I used for most of this.  I tried to reach out to him, but his presence is illusive online.  Best I can do is suggest that if you like the art, check out his paper craft terrain files on this OneDrive folder.

Also a big thanks to Stone Edges... from whom I got the wooden crate art.  I tried to reach out to them as well, but their web site has been down for a while.

Check out my other DIY Infinity projects:

• Woods and a Short Haul Space Truck
• Custom Infinity Army Box Build

Finding A Game's Broken Bits

I have finished reading chapter 4 of Games of Strategy by Dixit, Skeath, and Reiley.  Before I provide my thoughts, again here are Messrs. Aaron, Austin, and Paul with their conversation.

Reading this book as a game designer is both fascinating and a little odd.  Chapters 3 and 4 have both taken the same basic approach: analyzing the best way to "solve" a specific type of game.

My knee jerk reaction to this approach is concern.  If you tell a game designer that you solved their game I suspect you are breaking their heart.  It would certainly break mine.  To me, solved games are broken games.

But I think designers can take this a step further.  We can't stick our heads in the sand and pretend our games aren't broken.  Instead we should use the tools Dixit, Skeath, and Reiley discuss to discover the specific bits that are broken so they can be fixed.

So what are we looking for? In chapters 3 and 4 the authors have focused on finding three different things that would make your game broken: Dominating Strategies -- the strategy that always wins, Dominated Strategies -- the strategies that never win, and Nash Equilibria.

In the hobby game environment a Nash Equilibrium feel to me like those odd ruts you get into where Player A feels obliged to do X and Player B feels obliged to do Z in response and they never really have a good reason to do anything different.  In fact, every other action they could take seems less optimal.  I suppose this is just a redefinition of a Nash Equilibrium -- a combination of strategies or choices where each player gets the best value given the variety of each others' responses.

And how do we find them?  In chapter 3 the authors discussed decision trees. In this chapter they introduce the decision matrix.  Where trees helped analyze sequential move games (I take a turn, you take a turn, ...) matrix help analyze simultaneous move games.

Above is a matrix for Rock-Paper-Scissors.  The results are expressed from the perspective of the Right Hand.  RPS is a 0-sum game so we only need one set of results.  In non-zero-sum games you would list a number for each player showing their reward in each situation.

One thing you can say about RPS is that it does not have a dominant or dominated strategy.  Below we change the rules of the game to say that rock always wins but still ties against another rock.  And the matrix clearly shows that rock is the dominant strategy.

Now this would have been obvious without a matrix, but most games are more complicated.  Below is a decision matrix for a very specific situation that can come up in Championship Formula Racing.

Image two cars in a racing game sprinting for the checkered flag. The trailing car could end up gaining spaces from slipping the lead car in certain situations.  Without going into all the rules and reasons why, here are the cars' choices and results from the perspective of the lead car.  Also note that a result of 0 will likely mean that the lead car wins.

Dominated Strategies: For the trailing car, going 160 is dominated... it never results in the trailing car winning.

Dominating Strategies: There are no strategies for either car that always wins.  200 is closest for both cars, but if they both play 200, the trail car will win.

Nash Equilibrium: There is no Nash Equilibrium either.  No matter what speed one car picks, they might have a better play depending on what speed the other car picks... basically this scenario turns into a guessing game.

Below is a matrix for the same situation but with different choices.

Dominated Strategies: If the trailing car goes either 140 or 160, they can't win (remember 0s mean they will lose).

Dominated Strategies: Meanwhile the lead car can not lose if they go 160.

So this situation is clearly solved.  If this where the whole game, this would be a problem I would need to fix.

CFR Track Ratings Revised

The list of tracks I have build for Championship Formula Racing attempts to organize tracks based on how well they cater to one extreme strategy or the other.  Red tracks appear most favorable for racing from the front while purple tracks seemed most favorable for racing from behind.

Initially I organized these by gut, but pretty quickly applied some track profile metrics to determining what would end up being better for each strategy.  However, the ideal would be to use actual results from actual races.  I've now got data from 36 races on these tracks that helps me to do that and so I've redone some calculations and reorganized the tracks.

Performance Metrics

Because I do not actually know what strategy a car was using or attempting, I use a couple of proxies.  One is to look at where the car qualified.  A car that qualifies in the first 2 rows I consider to be running a front strategy.  A car that qualifies in the last 2 rows I consider to be running a back strategy.  My other proxy is start speed.  I consider any car running a 100 or 120 start speed to be running from the front and a car running a 20 start speed to be running from the back.  Obviously these are not perfect proxies, but they will have to do for now.

I then figured out how many points each position on the starting grid produced per race.  I also figured out how many points each start speed group produced per car.  I wasn't ignoring the middle groups and I think that is a viable 3rd strategic group but I did not want a 3-way variable... maybe next time.  But I did subtract the points scored by middle groups from the other numbers I calculated to provide some relationship to those middle strategies.  I use the point system from Organized Play.

Looking at the scores for Monte Carlo we can see that both the Front and Back groups are negative.  This means that the middle 2 rows actually did best.  But the front two rows did better than the back two rows.  Interestingly, the next two numbers show that 60 start speeds did worst.  20 start speeds (slow) having done a little better than 100+ start speeds (fast).

Finally, I show how many races I had at least some data I could use for these performance numbers.  Note that for many in-person races I might have only final results and so no data was helpful.  More often I would have only grid position and not start speeds.  For instance, the two races I have for Sao Paulo did not include start speeds which is why both Fast and Slow are 0s.

How Are Tracks Grouped

First I would look to see how many races I had in my sample for performance data.  With 10 or more I relied exclusively on the performance data.  With less than 4, I would rely exclusively on the track profile data.  In between and I look at both sets of data.

In that big table on the right, I show the scored produced by formulas I apply to different data.  For the in-between tracks I blend the track score and results scores together based on how close to 10 races my sample is.

To create the groups I look at the scores.  If a score is a standard deviation or more above or below the mean it ends up in the Red or Purple groups.  Yellow tracks tend to be meaningfully pro running from the front.  Green tracks should be pretty even but the reality is that are often still a little pro running from the front.  Blue tracks tend to actually be more balanced looking.

Race from the Front Bias

It has long been debated that CFR has a race from the front bias.  The data I've collected here does nothing to disprove that.  It is a game balance point that has long been on the radar.  The average results score (not shown below) of all tracks for which I have data is -1.73.  Roughly that means that some combination of starting in the front 2 rows and/or having a 100 start speed should be worth almost 2 points in any given race.

Tracks that Changed Groups

Now I'm going to look at some specific tracks that changed groups from my last groupings.

Francorchamps

Lets start with a doozey.  Francorchamps looks like a race from the back, is still the longest track I've built, and was grouped as a blue last time around.  But I have 10 races I can pull data from for this track and the results say different.

The chart to the right shows a starting grid and the average points that each spot has generated over those 10 races.  Note that due to field size not all grid spots have 10 samples in them.

The pole position is highlighted because a value of 11 or more means that the average result from this spot is a podium finish.

Why are the results different than expected?  My guess would be corner 1.  It really spreads out the field early and gives the cars that get through it on turn 2 a turn or so lead on the back half of the field.

Spielberg

Funny track.  When I built it I was convinced that this would be a deceptive red -- a track that looked like a play from the back but had too many choke points.  Twelve races later it turns out you can run it from behind sometimes.  But the front is still better on average.  So it moved from Red to Yellow.

The grey, na fields indicate that the 10th and 11th spots on the grid were never filed.  All of the data here was from my PBeM that caps at 10 cars.

Sakhir and Suzuka

Both of these tracks look more balanced on paper but so far they have both performed more front-leaning.  With only 4 or 5 races in the books on each with the data I need, they have moved from Green to Yellow although Sakhir could end up in red if trend continue.  Suzuka might end up in yellow.  Suzuka is very narrow and this result jives with my experiences on that track.  Sakhir surprises me.

Sakhir

Suzuka

Hockheim and Istanbul

Both look like race from the back tracks.  However, I have had thoughts that neither really were before.  And my track profile metrics peg them as greenish.  Honestly, I think I may have let perception blind me a bit when I made Hockenheim purple and Istanbul yellow last time around.

Interestingly, while both look moderately front-leaning from a grid perspective.  Both have odd metrics relating to start speed.  At Hockenheim, that 100 start speed seems crucial but the 20 start speed is apparently significantly better than the 60.  At Istanbul, the 100 start speed is terrible.

Istanbul

Hockenheim

The 2nd column in those tables is the average points with different start speeds (100 or 120 = fast, 20 = slow).  The 3rd column is my sample size.  So some of Istanbul's weirdness could be sample size related.

Austin and Valencia
I am convinced that Valencia is a run from the back track.  But the results so far suggest that it is more balanced than that.  Austin has been pegged by some as a run from the back as well but results are also suggesting better balance.  So they moved from Purple to Blue.  Austin could end up Green eventually.

Austin

Valencia

Oyama and Sochi
I don't have data (yet) for either but they both moved because I had placed both where I thought they were going to end up after racing despite what the track metrics may say.

Oyama looks so fast but it is also very short so it scores lower on the track profile scoring and moves from Purple to Blue.  Sochi has some choke points on it that I am not sure that the track metrics pick up on, however I've moved it from Blue to Purple for now until I can get more data on it.

Even Historical Driver Strategies for Championship Formula Racing

Back in June I talked about the three basic Historical Driver strategies for Championship Formula Racing: Front A, Even, and Back S.  A couple weeks ago we discussed variations on the Front strategy.  This time out, lets compare the three Even-ish Strategies and see how they riff on the theme of spending resources evenly.

My intent with the Mathy strategy was to have a car that took advantage of starred moves as much as possible.  The idea behind the Stalking strategy was to stay within striking distance for a move a little later in the race.

Same note as last time that these are not exactly the same as the versions of these strategies published in the game.  Reasons and links at the bottom of the article.

Now lets look at each Phase by Phase.  Same analysis process as last time... basically I'm measuring how much faster this strategy wants to go than a safe 0-wear plot.  More words at the bottom.

Phase 1

Not Starred:
Mathy: net +0 mph (100% +0)
Even: net +6 mph (72.2% +0, 27.8% +20)
Stalking: net +24 mph (11% +0, 58.4% +20, 30.6% +40)

Starred:
Mathy: net +37 mph (44.5% +20, 27.8% +40, 27.8% +60)
Even: net +28 mph (58.4% +20, 41.7% +40)
Stalking: net +34 mph (30.6% +20, 69.5% +60)

In the first phase we can also look to see how likely the car is to push it's start speed:
Mathy: 56%
Even: 33%
Stalking: 72%

Starred vs. non-starred is going to be a real theme for this group of strategies.  You can see here that only Stalking is willing to spend some wear into the first corner unless it is an efficient play.

Phase 2: 

 All three of these strategies include conditionals if they have more wear than c.  So lets look at both parts of that equation separately.

For most races and drivers their wear will be lower than c initially but if no wear gets spent in the first couple of corners that can change on shorter tracks.

W < C
Not Starred:
Mathy: net +0 mph (100% +0)
Even: net +6 mph (72.2% +0, 27.8% +20)
Stalking: net +8 mph (58.3% +0, 41.7% +20)

Starred:
Mathy: net +43 mph (41.7% +20, 58.4% +60)
Even: net +14 mph (27.7% +0, 72.3% +20)
Stalking: net +28 mph (58.4% +20, 41.7% +40)

W >= C
Not Starred:
Mathy: net +12 mph (41.6% +0, 58.4% +20)
Even: net +20 mph (27.7% +0, 44.5% +20, 27.8% +40)
Stalking: net +25 mph (16.6% +0, 41.7% +20, 41.7% +40)

Starred:
Mathy: net +43 mph (41.7% +20, 58.4% +60)
Even: net +31 mph (44.5% +20, 55.6% +40)
Stalking: net +28 mph (58.4% +20, 41.7% +40)

So mostly, none of these strategies want to spend much in this phase... But Even will spend if it has w >= c; Stalking will spend more than Even if the move is starred or they have w >= c; and Mathy will spend more than either if its a starred move.

Phase 3

Not Starred:
Mathy: net +0 mph (100% +0)
Even: net +34 mph (27.8% +20, 72.3% +40)
Stalking: net +0 mph (100% +0)
Stalking (w >= 2c): net +8 mph (58.3% +0, 41.7% +20)

Starred:
Mathy: net +37 mph (58.4% +20, 41.7% +60)
Even: net +34 mph (30.6% +20, 69.5% +40)
Stalking: net +20 mph (100% +20)

After last phase's variables, Phase 3 sees the Mathy and Stalking strategies revert to being mostly concerned with stars.  Even picks this middle phase of the race to be consistently prepared to spend some wear.

Phase 4

As usual, phase 4 has a lot of conditionals and cars will generally spend based on how much wear they have left at this point.  But one thing to note is that all three strategies can transition to this phase differently.

Mathy can get pushed here if they did not spend much wear earlier in the race and eventually gain w >= 2c.  Phase 4 for Mathy is much more willing to spend wear without there being a star than it's previous phases.

Even will only move to this phase if the car has entered the last 3rd of the race -- which is unusual.  And phase 4 for Even is very clearly defined by the wear remaining on the car -- have little wear: spend 1; have lots spend 2; in between spend 1 or 2.

Stalking has a more common transition to Phase 4 that includes moving here if w <= laps *2.  Which is really just a way to get them to Phase 5 quicker because Phase 4 for Stalking is actually its fastest phase.

Strategy Trends

Over the course of a race, HDs will spend most of their time in phases 2-4.  So let's quick see each strategy's progression over time:

(Not Starred/Starred) phase 2 >> phase 3 >> phase 4
Mathy net +0/43 >> +0/37 >> +5/48
Even net +6/14 >> +34/34 >> +20/20
Stalking net +8/28 >> +0/20 >> +23/42

I had to provide two numbers for each phase for these strategies because so much changes with stars.

Mathy basically only spends wear if there is a star for the whole race.

Even doesn't actually care much about stars and spends more middle and late than early.  Although that can vary if Even has a lot of wear left early in the race.

Stalking does care about stars but also defaults to spending wear late if it has it.

Next up I'll discuss the variations on the Back strategies.  Remember, links to the above 3 strategies below.

What is the Analysis Here?
The main way to measure a phase's intent is to look at the first starred and non-stared symbols in each tactic.  This gives you a sense of how much faster the car will likely try to go.  Think about it this way -- a car that wants to spend 1 wear in the upcoming corner will try to go 20 mph faster than a car that does not want to spend any wear, all other factors being equal.

If you then multiply each of those possible results by the odds of them being first choice, I get a net result of how much faster this car wants to go.  It might not be able to go that fast, but that's on the driver not the strategy.  I'm going to call this "net" in tables below.

Note that anything with 3 circles of any kind, should be considered starred because that is how the tracks are designed.  Also note, that if a tactic does not lead with a starred option, I'll count the first un-starred option for that tactics starred value since its more likely to be used.

How Are the Strategies Different?
Three minor editorial choices I've made since publication: 1) HDs can push start using only 1 green skill (the start speed test table changed a bit right before publication...); 2) I decided that the red skill chip could be used more places in relation to HD die rolls; 3) there were a few tactics that had 6 symbols on them and my BYO tool only allows for 5...  Links to these version in my BYO tool are at the end of this article.

Stalking (version 1.1)
Even (version 1.1)
Mathy (version 1.1)

Solo Race #7, 2 Laps at Silverstone

My 10 car field of historical drivers and I took the short ride over from Belgium to England in preparation for race 7 out of 10 in my 2017 solo championship.

I'm excited to be leading the series if only by a point after I drove through the carnage at Francorchamps for my 2nd win.

My plan at Silverstone is to ignore the desire for a high top speed.  I want to bid low, start fast with my 100 start speed, then use my 60-60 car to save some wear for when I really need it.  I'm hoping that the 140 top speed doesn't bit me.  I will be wrong.

Lap 1

Below are the results after the pole bid.  Fangio and Vettl bid the most again.  Fangio got pole after a tie-breaker roll.  Kimi Räikkönen is actually inside of me in the 4th row -- much higher than he normally starts.  Stewart's orange car sits outside row 2.

The First turn was important to me.  I wanted to pass some people here.  Below you can see that I did pass Hunt (white car) and Mansell (black car) but Alonso did his usual and ended up inside me.  Partly that's because I chose to end up behind Rindt for a possible slip next turn.

So, I only gain 1 spot on turn 1.

A couple sectors later and we are half-way through lap 1 and I've fallen back two more spots.  First Hunt dove inside me while I was on the line in front of Becketts.  Hunt spends more wear than I to stay inside through the corner then uses his better top speed to pull ahead.

Then at the end of the Hanger straight, Mansell spends more wear in the corner and ends up inside me after I got the slip to stay even.  Not much changes as lap 1 turns into lap 2.

Vettel leads in the white-trimmed Ferrari but he had only 2 wear left at the half-way mark.
Fangio sits second and looks good with 8 wear.  Stewart has 4 wear in 3rd but broke his top speed trying to go 180 through Copse the turn before the image above.  Rindt has 3 wear in 4th.

Alonso sits in 5th -- half-way between the lead pacl and the rest of us -- with 7 wear.

Mansell leads the rest of us and has 12 wear left.  Hunt has 7.  I have 11.  Fittipaldi has 5 wear.

Raikkonan is way back there but has 14 left still.

Lap 2

This is the crucial turn.  We start with the groups pretty much as they were above to start lap 2.  Alonso has fallen back to the pack.  Raikkonan went 200 last turn to close up some.

In the picture above, note a couple crucial details: 1) Fangio is right behind Vettel, 2) I'm no in a slip position.  In the picture below, there were two big things happening.

Most importantly for the race, this is where Fangio makes his move.  He pushes his top with dice, makes it, spends 2 wear in the corner, and passes Vettel cleanly.  As we'll see later, this is the end of the race.

Most importantly for me, I went from 3 spaces behind Alonso to 5.  Alonso pushes to 180, Mansell got two slips, Hunt also pushed to 180, I only went my 140 top.  Thankfully, Fittipaldi broke his top speed trying to pass me or this would have been even worse.

Below we have two forced passes.  First (on the left), Alonso goes 180 and squeezes past Rindt into 2nd.

 

Two turns later (on the right), I pass Stewart into 6th.  Raikkonen broke his brakes trying to slow for Abbey and is the first retirement on the day.

The next turn is below.  Fangio waves to his pit crew.  Alonso enters Luffield, but not quickly.  Vettel takes a chance and crashes.

A turn later, Mansell is next to Alonso having run through Luffield faster.  Rindt it right on his tail and I'm behind Rindt.

The end result of this is that Mansell was able to pass Alonso for a second place.  Rindt was also able to get slips to pull into 3rd.  Alonso ended up 4th and I was unable to improve on 5th.

I built another Google Photo Album for this race.  Every turn is recorded there.  I made some notes as well.  My advice is to click on the first image, click on the circled i symbol to reveal my notes, then page through that way.

Wrap-Up

I stayed ahead of Stewart in the season rankings who finished 6th.

And a big win for Fangio -- his 3rd this year -- to put him right back in the conversation for the title with 3 races left.

A disappointing result for Vettel who retired from his second race in a row to really fall behind the 3 season leaders.  Also disappointing for Alonso who dropped from 2nd to 4th across the finish line.

On the other hand, this was the best results on the season for both Nigel Mansell and Jochen Rindt who finished 2nd and 3rd.

Raikkonen's first DNF of the season means that there are now only 3 drivers who have finished every race: Me, Stewart, and (ironically) James Hunt.

2018 Organized Play Season Will Be Huge!

Well, it certainly shapes up that the second season of Championship Formula Racing will be bigger than the first.

I've updated the calendar and there are already 4 in-person seasons or tournaments planned plus 3 more single race live events and the 2 Play-by-email seasons that are already underway but will count towards the 2018 season as they are still in progress.

Congress of Gamers -- Summer

The first race of the 2018 season will be held August 26th starting at 10:30 am at the Congress of Gamers in Tysons Corner, VA.  If you've been to the event in Rockville by the same name, expect the same event in a different setting.  Sadly, I will not be able to make that race but Michael Polcen will ably steward.

For more information about the Congress of Gamers see their web page.

Also note that I plan to run races at the Congress of Gamers in Rockville to be held October 7-8 and the related Winter Games Fest in January.

Detroit CFR Season

The big newcomers to this calendar are the biggest seasons planned for 2018 -- one in Detroit and one in San Marino.

The Detroit series will feature 8 races and starts September 8th.  This is a great group of veteran drivers that are more than happy to bring in new-comers.  Check out their web site for more details.

Flag of San Marino -- home of CFR's newest tournament

San Marino Season

The San Marino season is planned for 9 races starting September 26th.  This will be the first CFR event to take place in Europe.  Given the large number of Italian fans of CFR, the interest from San Marino makes sense.  Check out the web site for the San Marino gaming association that is running the season for more information... if you can read Italian.

Tournaments for PrezCon and WBC are planned as usual.

Play By Email

There are two email based seasons going on right now.  Mine and the Redscape series.  Both run 3-race seasons with multiple races to accommodate all of the participants.  Both use a ladder system to advance drivers between the heats.

For more information about my series, see that page on my site.

For more information about the Redscape series, email me and I will pass you on to Mr. Polcen.

Long time driver, Robert Rund is also thinking about putting together a email race using the pitting rules.  If you are interested, email him.

2017 CFR Organized Play Champion and Other Awards

The inaugural Championship Formula Racing Organized Play season has concluded.  Before we get to the awards, some data on the season.

Race Opportunities	21
Total Races	47
Tournaments	5
Drivers Ranked	100
Driver Races	477
Avg Field Size	9.5

It is hard to compare these numbers to past recordings since those would be pre-OP numbers but these numbers are all larger than I have seen in the last 5 years that I've been meaningfully ranking drivers.  Last year I tracked 31 races and ranked 89 drivers for a total of 316 Driver Races.  In 2013 and 2014 there were 4 tournaments... the most before this year.  Last year and in 2013 there were 14 race opportunities.

Interestingly, the average field size has been shrinking.  It was 11.8 in 2013 and has slowly dropped year after year.

Obviously 47 races and 5 tournaments means a lot of drivers and a lot of stewards.  Thanks to everyone who raced and especially to every steward and tournament organizer.

But without further ado... awards:

OP Champion

Don Tatum came close and Kevin Keller made a run at WBC from way behind, but in the end I (Doug Schulz) held onto my lead to win the first CFR OP Championship.  On the right is this year's top 20 showing their change in ranking from last year.

I'll write a longer summary of this season in a later post so I can give it more time.

Complete rankings can be seen here. 

Rookie of the Year

By which I mean, rookie to CFR rankings... Renaud Verlaque showed up at WBC this summer, ran in 3 qualifiers, winning his last qualifier to make the finals table.  That was good enough for 27th on the season even after retiring in the WBC finals.

Honorable mention to Phillip Walling who scored points in all 3 races he entered this year and ended up ranked 51st.  In total 29 different drivers raced this year for the first time since at least 2013.

Comeback Driver of the Year

For the best showing from a driver we have not seen in a while... Chris Brandt has been running the event at PrezCon Winter for a while now but last appeared in these rankings in 2013.  This year Chris wrote up his results and even participated in other OP events -- 9 races in total -- on his way to being ranked 16th on the year.

Honorable mentions for Dan Mallison II and Dave Ingraham who ranked 26th and 41st after spending a year away from these rankings.

Most Improved Driver of the Year

For the largest jump in ranking from last season (minimum 2+ races the season prior)... Jim Fleckenstein ran 3 races last year, a 3rd, 5th, and DNF -- not making the finals at his only event that year and ranked 46th.  This year, raced 8 times, picked up a win, and scored points in both tournaments his entered for a rank of 15th this year.

Very Honorable mention to Bruce Lavoie who jumped from 62nd to 31st this year.  His three races this year included a win and a third.  His 3 races last year included 2 DNFs and a 5th.

Steward of the Year

This was the hardest award to give out.  Without every steward, the races would not happen and this post would not exist, but... Michael Polcen did much this season to over come car-gate.  Not only does Michael run the 2nd largest online CFR tournament, he also ran a demo event at his friendly local game store.

Very Honorable mentions for Chris Brandt who stewarded 5 races this season at PrezCon Winter, Chris Hancock who stewarded 4 races in two different online tournaments, Chris Long who ran 4 races at the hugely successful WBC, Jim Orlando whose name is not Chris and yet still ran 4 races this year, and Don Tatum who ran his first tournament this year at PrezCon Summer.

Great season, thanks, and keep eyes out for early news from the 2018 season of CFR Organized Play.