Thursday, July 9, 2020

Swamp Table Project: Objective Markers

The miniature game I play most by far is Infinity.  In most Infinity missions, there are objectives scattered around the table that you have to interact with to score points.  The objective could be a computer console or satellite dish or supply crate or small-arms-vending machine (seriously).  You can just use cardboard tokens to represent these things, but that was going to look out of place given the work I'm putting into the rest of the terrain, so I decided to make some objectives.

I went with a concept that I thought could viably represent any type of Infinity objective.

Here we have the constructed and freshly primed pieces. 

I used clay poker chips as the bases to provide some weight and a solid round base.  The sides of the body is a cardboard tube that I cut up to suit.  This cut was not as clean as I wanted so I used masking take to smooth off the edges.  This wasn't the best plan as the tape was still visible after priming and painting.

I then cut a piece of foamcore to cap the tube.  Both the flat top part and the angled flat part are 1 piece of foamcore that I cut half through and then folded.  I placed pieces of metal hangers in those gaps. 

On top are plastic tubes from dog-poop bag rolls that I cut on an angle and then glued lego satellite dishes to.

Here are a couple pieces after painting with a model for scale.  I left most of each piece the metalic color I primed with although I tried to add a hint of blue to the main bodies. 

Each of the 6 objectives got a different computer readout on the angled flat part.  These were modified from some images that Infinity publishes as the official computer screens for the main factions in the game.  I then highlighted each piece with a different color so I can tell them apart more easily.

Next I wanted a nice way to keep these and (someday) travel with them. 

So I cannibalized a box from a recent purchase of Infinity miniatures.  I cut off the box lid and cut circles in the foam insert that kept the minis sage during shipping.  Next I glued the foam into the box. 

The wholes are slightly smaller than the bases of my new objectives so they fit snugly.

Finally, I wanted a way to track information about objectives during the game.  Some missions care who touched an objective last or who touched it any time during a missions and some missions use more than one kind of objective.

The bottom piece of chipboard has a space for each objective identified both by color and with the same computer screen image.  I also have some arrow markers that can show possession or something else like that.  Finally I have a handful of markers that represent the various types of objectives that I can place near the bottom part to show what it what on the table.

The rest of the set.

Higher resolution images here.

After this side project I built trees.

Friday, June 26, 2020

Swamp Table Project: Shed

To go along with the farm house, I wanted a smaller building.  This time a shed.  My reference material were google searches for sheds in swamps / bayou. 

I used mostly craft sticks for this build.  With some balsa for the corners and door frames.  The base is foamcore and more foamcore for the walls under the eaves in the front and back. 

The roof is decorative paper that is corrugated on one side.

The roof just fits on top and can be removed for easier inside access.

More pictures.

Higher resolution images here.

Trees are the next big thing I tackled.  And I'm super proud of them but before I finished them I had a side quest to build some objectives.  So I did that next.

Thursday, June 11, 2020

Swamp Table Project: Ruined Farm House

A couple weeks ago I introduced the work I've been doing on a Swamp Table for my miniature gaming (mostly Infinity).  That was about some alien looking bushes.  This time I want to show off what is one of the main pieces for the table: a ruined farm house.

Sure, farm houses are not very futuristic but I wanted my table to be versatile and maybe this alien world was colonized by people who liked farm houses.  I wanted something reminiscent of a early 1800s southern farm house.  Not a large plantation home, more of a smaller structure.  I ended up finding some good source material online for inspiration and this is what I ended up with.

It is mostly a foam core construction on a foam core base.  This corner is the most intact part of the building.

The small balcony is actually pinned through the front wall and into the second story floor with a couple of toothpicks.  The railing uses balsa for the main support and thin wire for the smaller details.  The floor of the balcony is edged in craft/popsicle  sticks.

The front porch uses larger craft sticks supported by more of the smaller sticks.  Additional craft sticks became shudders and window sills.

A good look at the second floor from the back side.  The stairs and some other bits of that middle section are what I could have done better.  The whole area could have been planned better but I think it came out well enough -- especially for my first serious building construction.

More views of the interior via the backside of the building.  Lets focus more on the chimneys... which are my favorite part of this piece.

I used the technique of striping on side of the foam core off and then carving into the foam innards for the brick work and was really happy with how it came out.  Some of it was a little uneven, but I like it.  The actual flues at the top are my favorite plastic tubes from inside a roll a dog poop bags.

 Higher resolution images here.

The next piece I finished for this table was a small swamp shack.  Pictures of that in a couple of weeks.

Wednesday, May 27, 2020

Swamp Table Project: Lantern Bushes

Since Michael and I got into Infinity I've been tinkering around creating paper-craft terrain.  Mostly this was printing out patterns I found on the internet and gluing them to boxes.  It was a fun way to get my feet wet, but the quality was hit or miss and the durability was not great.  So I went down the serious terrain making rabbit hole (the Terrain Tutor to be specific). 

When I came up for air I decided that I was going to put together a scratch-built swamp table suitable for Infinity and maybe other things as well.  I've now made a lot of progress and wanted to share some pictures.

First up are what I like to call Lantern Bushes.  These were the first really interesting piece of terrain I scratch built and were very much inspired by a piece of what would normally have been trash.  I didn't have the swamp table idea yet but these pieces ended up fitting the theme.

Michael had a couple strings of lights under his old loft bed with these really nice paper coverings.  I decided that they would make great alien trees or bushes.  No need for paint.

I used chipboard as a basing material.  Painted it a bluish green and used some blue aquarium stones to give it an alien feel.

Roughly every other lantern was elevated on a plastic tube from the inside of a roll of doggie-poop bags.  I used modeling clay to form the root structures.  Some painting later and I had 4 pieces of larger scatter: Two pieces have two bushes and the other two pieces have 3 bushes.

The chipboard was not my best call.  As you can see in a couple of these pictures, the corners warped up a bit.  I did go back and try to warp it back the other way but couldn't correct it fully.

Below are pictures of the pieces with 3 bushes.  Higher resolution images here.

The next thing I tackled was one of the larger pieces destined for this table -- a ruined farm house.

Wednesday, May 6, 2020

WBC 2020 Tracks... assuming that is a thing this year

Indianapolis corner 1 at the end of a 4-wide straight.

Editorial Note: since this posting, WBC 2020 was cancelled.

When I checked BPA's web site last night, they had not yet made a decision about WBC 2020.  Just in case, intrepid steward Chris Long has picked some tracks.

In no particular order, the qualifying tracks will be:

Group 1:
This would be the first time that Indy has appeared at WBC.  Also, 4-wide straight.

Wednesday, September 25, 2019

Judging Track Styles

For a while now, I've been organizing tracks on my web site by the play style those tracks tend to favor.  In this case I'm judging tracks along the race-from-the-front and race-from-the-back axis of broad strategic choices.  All other things being equal, some tracks are just easier to hold a lead on than others.

Besides being interesting information, I like to use this data when picking tracks to use in a series.  Picking different kinds of tracks keeps the racing interesting from race to race.  I've also noticed that some drivers are just better at different strategic styles so a variety of tracks helps to keep the competition fair for everyone.

I've updated the table and some of the calculations that go into some of the scores.

How to Read the New Table
There is a lot of information below and in the key at the bottom of the track listing, but the top line are Raw Score and Adjusted Score.

Raw Score is my best guess based on results and Track Score of how a track favors play from the front (negative numbers) and play from the back (positive numbers).  A score over 1 or under -1 are suggestive of a strong lean.  Scores closer to zero are pretty balanced (or could favor middle strategies).

Adjusted Score is basically the same thing but relative to all the other tracks,  So where raw score tries to objectively describe a track, Adjusted Score is comparing that track to all the others.  Interestingly, there is less variation in those two things after using my new Layout Score than there used to be.

Measuring Tracks Based on Results
Ideally I score tracks based on actual race results from organized play.  In a perfect world I would ask each driver before the race how they were approaching the race strategically... instead I find proxies.  The two proxies I work with are qualifying position and start speed.

Qualifying position is an obvious stand-in for strategy.  Race from the front strategies like to start out front.  However, its not perfect.  There are times you make a pole bid hoping to end up one place only to end up somewhere completely different.

Start speed is another decent proxy in my view.  Race from the front people tend to like a 100 start speed.  Again, not always a perfect approach.  I've seen people take the 100 start speed not because they wanted to start with the lead but because they wanted to bid nothing and work up to the mid-field in a couple turns.  Some tracks are also laid out in such a way that 100 start speed may be of minimal value or hugely valuable regardless of overall strategy.

Certainly these two measures can produce mixed signals.  I've seen cars on the front row of a starting grid with a 20 start speed and cars near the back with 100 start speeds.  That said, I think these are decent tools to work with.

Basically I find the average number of points scored by people who started the race in the front 2 rows ("the front"), middle 2 rows ("middle"), and back 2 rows ("back").  [See the bottom of this page for how I score results.] I do the same for start speeds with "fast" being 100 or 120, "medium" being 60, and "slow" being 20 start speed.

I then figure out how much better front did than middle and how much better back did than middle.  Then I add those two numbers together.  A result of 0 means that middle was best or that neither front nor back seemed to hold an advantage, a negative result means that results favored cars starting in the front 2 rows, a positive result shows that results favored the back 2 rows.  Then I do the same for start speeds... negative results showing the high start speeds did better and positive results showing that the 20 start speeds did better.
( (Qbd-Qfd)*Q + (Ssd-Sfd)*S ) / (Q+S)
Q = the number races where I have data for qualifying
Qbd = Qb - Qm
Qfd = Qf - Qm
Qb = the average points scored by someone starting in the first two rows on this track
Qm = the average points scored by someone starting in the middle two rows on this track
Qb = the average points scored by someone starting in the last two rows on this track
S = the number races where I have data for start speed
Ssd = Ss - Sm
Sfd = Sf - Sm
Sf = the average points scored by someone with a 100 or 120 start speed on this track
Sm = the average points scored by someone with a 60 start speed on this track
Ss = the average points scored by someone with a 20 start speed on this track
In the end this is a track's score if I have enough data to feel good about that.  I'm not sure how many results makes me feel really good about this method, but for now I pretend to feel good at 10 races.

Before I get to 10 races, I also look at some elements of the track layout.  I weight the results score more and more as I get more and more result data.

Measuring Tracks Based on Layout
Finding objective attributes of a track that predict how it will play has proven difficult.  I started with 5 attributes based mostly on gut.  But recently I've reassessed how well those attributes predict actual results and that led me to find new attributes.

Originally I used 1) Long Straights, 2) Corner Density, 3) Width, 4) Longest Straight, and 5) Track Length to concoct a layout score.

Long straights was a weighted count of straights longer than 7 spaces.  Corner Density was the length of the track in spaces divided by the number of corners on the track.  Those two measures were meant to explore how tight and twisty a track is.  Are there a lot of short straights between tightly packed corners?  If so, this could contribute to a race from the front strategy.

For width I measured the percentage of 3-wide track against the total length of the track.  This is all about passing.  Two wide track gets bottled up and blocked a lot easier than 3-wide track.  So a higher percentage of 3-wide should be better for running from behind.

Longest straight and track length are exactly what they say they are.  Race from the front cars tend to buy wear and start speed at the expense of acceleration, deceleration, and top speed.  So long straights can hurt those kinds of cars -- and by extension, racing from the front.  Finally, the shorter the track the easier it should be to hold on to that lead.

However, after updating my data recently I ran some regressions to see how good I my layout scores were at predicting results.  Turns out... not so well.

Y-axis is number of long straights.  X-axis is results score (lower favors play from the front).
Y-axis is corner density.  X-axis is results score (lower favors play from the front).

Y-axis is the length of the longest straight.  X-axis is results score (lower favors play from the front).

Y-axis is the track length in spaces.  X-axis is results score (lower favors play from the front).
Turns out track length, longest straight, corner density and number of long straights really aren't very predictive of how these tracks seem to be playing out.

Y-axis is the % of the track that is 3-wide.  X-axis is results score (lower favors play from the front).
3-wide is better... although the internet tells me that 0.3 is considered a weak correlation so this still isn't terribly predictive.

So I took a bunch of other measures and made up some new ones to try and find more predictive track attributes.  Literally the only thing I could find that hit the 0.3 mark is the number of corners that are 3-wide (for corners that change width I count it as 3-wide if it ends 3-wide).

Y-axis is the number of 3-wide corners.  X-axis is results score (lower favors play from the front).
This makes sense.  Corners are bottlenecks and good opportunities to pass so having more room in the corner, especially the all important exit row, makes sense as something that would assist running from behind.  Interestingly, the raw number of 3-wide corners was more predictive than the percentage of corners that are 3-wide.  This also makes sense... more raw opportunities per lap is better.

I tried creating a new layout score just based on this metric as it had the best fit, but the result included obvious blind spots.  I added back in the percentage of the overall track that was 3-wide and that helped a little but it felt like I needed more attributes to round out this track-based score.  So I went searching for modestly predictive things.

Turns out the number of "medium" straights is more predictive than a lot of other things I can measure.  In this case medium straights means straights that are longer than 3 spaces and shorter than 10 spaces long.  Why?  Because that data ended up being the most predictive.  Why?  No idea.

Y-axis is the number of medium straights.  X-axis is results score (lower favors play from the front).
Finally, I tweaked corner density to make it more predictive by only counting the number of corners that have a speed under 120.  (When I assign a single speed to a corner this way, I use the fastest speed through the corner that is not obviously less efficient than other options.)

Y-axis is track length divided by slow corners.  X-axis is results score (lower favors play from the front).
So I created a new Layout Score based on these 4 things, but I weighed the score so that the first two things counted more than the last 2.

Thursday, August 1, 2019

CFR Organized Play 2019 Final Rankings

Don Tatum is the only driver to have finished Organized Play in the top 5 all three seasons.  He finished 2nd in 2017 and 4th in 2018.  This year he breaks through to become the 3rd CFR Organized Play Champion.

This was a season Don really ran away with.  Early in the season, it seemed that Tim Baker might give him a run (Tim ended the season 3rd) but by the time we got to WBC, really no one was in striking distance.

Don won 8 races this season (last season's champion Michael Polcen was 2nd with 5).  Don was also the only driver to win 2 events this season.  In the end he finished 50 points clear of runner-up Bruce Rae.  The 2018 season was decided by 6 points.  2017 was decided by 21 points.

Huge congratulations to Don.
2019 OP Top 20
Rookie of the Year
Bill Worrell raced for the first time in CFR Organized Play this season and won the Detroit Season including 1 race win and several more podiums.  He finished the season 5th.  

There were 42 rookies to Organized Play this season out of the 151 total drivers ranked.  Only two others finished in the top 50: Scott Cornett who ranked 22nd this season and Phillip White who ranked 41st.

Most Improved Driver of the Year
Stephen Peeples participated in a single Organized Play race last season and ranked 125th.  He participated in 6 this season, including 2 wins to rank 40th -- a jump of 85 spots.

Steward of the Year
For the last two yeas, Chris Brandt has run two different events -- the in-person PresCon tournament as well as the local DC-Maryland-Virginia season.  He is the only person to run two events a year and both grew this year.  Thanks Chris!