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Battle Arena Drones is heavily inspired by the nostalgia of Descent II multiplayer.
The combat is too much to go into on this page. Follow the link for more information.
The game's distinct design style is derived from the Retrofuturistic, science fiction and popular culture aesthetics and concepts of the 1950s, as implied by, for example, the design of the drones themselves, which resemble muscle car automobiles that peaked in popularity in the 1950s.
This aesthetic is further suggested by the drones' distinctly curved and overly shinny surfaces, with hard and high-tech machinery under the hoods. The curvature of the surfaces of the drones also interact with the various lighting effects and sources in the game, resulting in an array of reflections and illuminations, which give the drones a dynamic and life-like look and feel. This subsequently resulted in a reduction of the art production costs of intricate texturing, as this effect allowed for a more desirable and well-rounded look that works across scale well.
Effects and aesthetics oscillate between arcade- and realistic-looking, leaning more frequently towards arcade-looking.
The stars of the BAD sport's arenas are always the drones. The history of the drones in the BAD universe is diverse- built for everything from industrial work to urban pacification, the drones were designed to penetrate any building designed for human use. This makes them able to move wherever we would and do the jobs we might have done, or hunt down a reclusive criminal. The drone types used in the combat sport of BAD have been refitted to operate within the arena rules, and of course are as glossy and shiny as possible. In some ways they reflect the obsession some have with muscle cars: glossy paneling, and under the hood there’s just hard machinery. BAD features several manufacturers that each brings their own style to the drones. Each drone is designed to look distinct and recognizable in shape, while still holding true to the primary design of all drones in the game.
New game modes will be built over time for now these are the identified and planned modes.
This is a death match where first player to reach a number of kills wins.
Team Death-match where the first team to a number of kills wins.
This name probably will change. A racing variant where killing drones scores you some of the points they have but finishing the track gives you far more points. The teams have to decide how to allocate players to race, defend or attack.
This is based a little on cricket. At the start of the round each player in each team selects 5 drones. These drones once destroyed may not re-spawn. Each death the player must chose which drone they want to use next until they are eliminated or the whole of the other team is eliminated.
The meta game revolves around making in game currently levels in each drone, badges and prizes (digital and real world). We have identified several different players we need to cater for.
In each case a set of short, medium and long terms goals need to be ascertained for each of the types of players. In both free to play and commercial models. This is 6 meta game models we need to mold.
Each player starts of at level 1 and they are also level 1 in each drone. A player's profile level is the sum of their drone levels. For every number of levels we issue them with a prize delivered in the email system. Each drones level is geometrically higher and harder to reach. This means playing with lover level drones are the easiest way to make levels fast.
Currently we need to decide if there is a cap per drone
The first 5 levels of a drone award access to that drones customization tiers (see individual drone pages) Tier 1 is unlocked automatically and grant access to choosing a secondary weapon to spawn with. Tier 2 to 4 are stat trade offs. Tier 5 is a choice between 3 passives that change playstyle in that drone dramatically.
Each AI in the game has a personality and a play style. Some are specific to certain drones others can fly various drones. All are named after fictional artificial intelligences. The AI's have player profiles and there scores are kept globally, this the in turn becomes a yard stick for measuring a players ability to defeat certain AI skills.
Scoring in tournaments can be presented for social groupings as well as comparing social groupings against each other in a leader board. For example, if two secondary schools are playing in the same inter-school tournament (only available to players in social groups of educational/secondary), each school can evaluate how there players compare to each other as well as how they are doing compared to the other schools overall.
To make this fair, scoring is done on the top 10 (or n) players and each players tournament score is their top 10 (or n) games scored. So attrition does help but skill is a far more significant measurement.
Global ranking is only adjusted when playing ranked tournaments (any kind in any circumstance). Ranking is based on a score differential where each player starts the season (every three months) with a specific score. Players with a higher value will not easily take from those with lower. Also players are typically placed in games with similarly ranked players (this depends on the match making model for the tournament).
Free-to-play players are the life-blood of the game. In effect they are as much a part of the game as each part we build. When we motivate their play style we need to consider how it will play out versus our paying customers and create a symbiotic relationship between the two modes of play. Big goals here but currently no plan exactly how this can be achieved.