KDABET - A Store of Value Sports Betting Protocol Built on Kadena -

Please enable JavaScript to view the full PDF

KDABET - A Store of Value Betting Protocol Built on Kadena. Stephen Rothwell [email protected] www.kdabet.com Abstract: The Kadena blockchain scales up proof of work to hundreds of thousands of transactions per second and significantly minimizes gas fees. Sports betting exchanges and bookmakers can often see thousands of bets per minute in popular markets. Kadena is a natural fit for a sports betting protocol due to competitor chains, like Ethereum, that struggle with high transaction costs and limited throughput. However, to truly scale up a decentralized betting network to a global capacity, a token needs to also appreciate in value proportional to the amount of efficient data that builds up on the protocol. Current efforts in decentralized sports betting try to incentivize liquidity to enter markets via inflationary emissions. This approach fails to store value in the token because it doesn’t compensate the user for immutably writing efficient data to the ledger, and so, there is no incentive for skilled bettors to use the protocol over a centralized bookmaker. To store value, the protocol must instead emit tokens to those players which beat the final consensus of the global market itself, incentivizing skilled bettors to capitalize markets when they are maximally inefficient. Furthermore by engineering the token to be deflationary over time, much like Bitcoin, a scarcity effect is introduced which spurs the network to hold its tokens until supply is exhausted and network saturation is achieved. As the network saturates, the difficulty in generating price efficiency rises dramatically because there are more competitors trying to mine emissions via early betting. This causes a virtuous effect on token price due to increasing competition to mine. Bettors on KDAbet are incentivized to play a competitive game, betting often and early. This store of value approach to a digital betting token is called “proof of efficiency” and rewards those bettors whose data generates the very odds that drive the betting industry instead of those bettors who happen to be rich. 1. Introduction In fiat sports betting, bookmakers trade the ability to bet some minimum amount of money for the data that sports bettors provide. The data is the volume bet at a certain price and time. (figure 1). The bookmakers take that data and profile it to learn which bettors are skilled and then turn the efficient data around on their customers by moving the price off of those skilled bettors and diminishing the ability for a less skilled bettor to exploit an edge. Figure 1: A typical betting ledger Time Amount Odds User Type mID Backed Limit 2022-04-06H12:34:01 $135.13 1.923 321 MoneyLine 32 Dodgers $500 2022-04-06H12:36:35 $398.00 1.931 715 MoneyLine 32 Dodgers $500 This makes it very hard for skilled bettors to profit, due to the fact that the operators can share data with each other via price aggregation services, effectively charging a blanket economic rent for an insignificant level of exposure for the player, usually no more than $500 per bet. At most, a bettor can deploy a few thousand dollars in centralized markets before their information is factored into the price and the skilled bettor can no longer justify the cost of originating prices because the volume is too constrained. This phenomenon is called “slippage” because your edge is slipping downwards towards 0 as you feed the bookmakers more information in the form of repeated maximum bets. A decentralized exchange built on the Kadena blockchain has no such limitations. If there is unmatched liquidity sitting on a software, then that liquidity can be matched and held in an escrow inside a PACT smart contract, without artificial limits on the bet amount. Furthermore, wallets cannot be banned nor can the ledger data be singularly used against other unskilled bettors by a sole source. The betting data is on-chain and open to all. This argument for an open web3 protocol has been put forth by many proposed DEX’s like: LunaFI, BetDEXLabs and SX. However none of these communities have tried to solve the fundamental issue with starting a betting exchange: storing the value of skilled bettors' data processes into a token. To attract liquidity and keep it on a sports betting exchange by storing value, a decentralized community requires three attributes: 1. Deflationary token. An artificial monotonically decreasing scarcity must be embedded in the token’s mining dynamic. Otherwise, the price action stagnates and the community abandons the network because the token price degenerates into an unstable oscillatory function with respect to arbitrary demand for betting capital. 2. Network effect: To create a network effect in sports betting, the token must reward originators who are efficient price makers and not just players with lots of betting capital. Otherwise, as we see in volume based bet-mining approaches, the price stagnates and there is no store of value. (figure 2) Emitting tokens from a fixed supply to skilled market makers/takers allows for capital to build up in the hands of the people who drive market prices and incentivizes them to hold on to their tokens to increase token demand. As skilled originators adopt the platform and the network grows, the betting markets get even more efficient due to more players competing to mine the token, putting additional demand pressure on the token. 3. High composability and low fees: Smart contracts need to be price efficient and that means the underlying smart contract SDK has to be highly composable and feature cheap compute. This is not possible on Polygon or Ethereum because solidity has poor composability and unfeasible gas fees. Kadena solves this problem with its simple and compact PACT language. Pact is a highly composable LISP and provides cheaply upgradeable smart contracts that developers can quickly adapt to changing transaction logic. This means a single, compact, smart contract deployment can encompass and resolve many market logics at once and due to Kadena’s low gas DEX infrastructure, there is a much lower fee burden that prices out poor people on other blockchains from trying to mine tokens on the network. Kadena’s unique attributes foster an environment which encourages a high rate of adoption. This approach to a store of value token is superior for adopters because it focuses on the growing of the network at the fastest possible speed and encourages the core market making community to hold their tokens instead of treating tokens like working capital. Miners anticipate the token storing the value of efficient data as adoption grows and rewards dissipate. This system for rewarding stakeholders who engage in the price making game of sports betting markets is called a “Proof of Efficiency” protocol. Figure 2: The SportX (SX) token has not stored the value of +EV data over time. Notice how the token has failed to accrue any value since inception. This is because their mining mechanism is based on volume only which means only the capitalized can mine the token. This implies their approach does *NOT* generate a network effect. 2. Why Kadena? Kadena is a Proof of Work Style blockchain that can scale to high transaction rates. Bitcoin works by maintaining a single chain of linked hashes which has to be confirmed by working backwards to the origin block and confirming the data is sound and untampered with. Kadena braids together separate proof of work chains via a mechanism called “braiding” . The graph structure of the linked hash blocks are optimized to reduce the number of jumps needed to be made to get to the genesis block and verify a transaction. This means Kadena is highly scalable with minimized gas fees as the compute burden is much lower than standard PoW. This is a key concern of sports bettors who want to maintain their bankrolls or might desire to bet a high frequency of in-play bets. Kadena features a unique smart contract language called “PACT”. PACT is a LISP expression style software for building secure smart contracts . PACT is extremely composable due to its underlying functional programming structure written in HASKELL. The Lisp syntax neatly allows the software to apply functions to data and configures an output object based on the data that interacts with a program’s Abstract Syntax Tree (AST). (figure. 3). This composability first approach to a smart contract language allows for all of the types of matchups in a sports betting exchange to be neatly handled by a small software and unlike solidity, you don’t need to deploy a lot of smart contracts nor suffer any interoperability or upgradability concerns like ETH smart contracts do. Kadena promotes efficient code deployment that can react elegantly and inexpensively to a lot of different types of transactional data structures that occur in sports betting. Figure. 3: An AST diagram consisting of an arithmetic addition operation and its component parts. If we consider a smart contract as an AST that operates on transaction and oracle data, we can operate on the data and decompose it into a component tree which can mutably cover all types of betting markets, in a family of similar markets, via a single binary deployment. Kadena’s PACT language is a nice LISP style syntax and therefore is efficient for sports handling betting transactions which require many thousands of market types with different resolution structures to be covered. Perhaps the most important aspect of Kadena is its scalability. At scale, Kadena will handle hundreds of thousands of transactions, dwarfing competitors like Solana and Polygon, but at the same time will maintain the bulletproof and battle-tested security of Proof of Work protocols. Kadena is also highly secure because it is Turing Incomplete and guards against dangerous bugs like infinite loops and recursions which open up exploits. Safety of user funds is critical in sports betting applications. Even a single loss of betting capital can cause a cascade of negative press which causes thousands of players to exit the protocol. Kadena’s focus on safety first for large scale financial transactionality is absolutely essential for trust and regulatory compliance in a stringently policed industry like sports betting. Kadena is a fit for the three primary concerns of a Web3 sports betting protocol: 1. The ability to scale and handle In-Play which comprises millions of daily transactions. 2. Composable, efficient smart contracts that are easy to develop and safe. 3. Little to no gas fees which pleases bettors. 3. Proof of Efficiency Protocol (PoE) Origination is a word which describes the effort of mathematically setting a probability for a team winning a sports matchup. The inverse of the probability, is exactly the odds needed to breakeven without any fee tacked on to it. 𝑂𝑑𝑑𝑠 = 1/𝑤𝑝 => 𝑜𝑑𝑑𝑠 = 2. 00 , 𝑤𝑖𝑛 𝑝𝑟𝑜𝑏. = 1/2. 00 = 50% (1) Originators try to outsmart the bookmaker by computing the chance to win and comparing that to the implied probability of the bookmaker's odds. If there is a discrepancy in the odds, perhaps due to the bookmaker's incorrect calculation, the originator will bet that matchup with increasingly more money as that discrepancy gets larger in their computation’s favor. The bookmaker’s odds are the least efficient at the moment they first offer them and the most efficient at the moment of a games tipoff time when game information is maximal. This is because the bookmaker uses the data they receive, in the form of profiled bets, to inform their odds making effort. As more data comes in, the aggregated opinion dominates and finally determines the best price at the point of a sporting matchups start, known as the closing line. Operators often allow very small bets in the first few hours of a market and very large betting limits when the market is mature. They take on more risk as they become more certain of what the wisdom of the crowd thinks the line ought to be. If the originator has a better price than the closing line, the difference between the two prices is called closing line value (CLV). In essence, the bettor has outsmarted the market and has a positive expected value on making money off this bet. It is widely thought that CLV determines which bettors are efficient price makers. Furthermore, origination is a process that gets harder over time because the efforts to outsmart the bookmaker are becoming more sophisticated as computer technology, better public data, machine learning and automation have all proliferated through the markets since the early 2010s. The ability to originate and beat the bookmaker has a natural deflationary aspect to it. Therefore, it makes sense to mine a token by asking bettors to prove that their origination has positive expected value. They do this by simply betting. If the originator on the exchange can consistently prove they beat the closing line, they will earn tokens on the KDAbet protocol, semi-proportionally to the matched volume while at the same time making the line more efficient and storing their data on the blockchain. This highly incentives bettors to bet early and often, effectively capitalizing markets early and with significant volume. Naturally as competition in markets increases, so must individual bettor volume in order to claim more mining share. On-chain data can also be aggregated and reverse engineered with some effort which effectively supports the store the value of origination in the token as players can more quickly figure out what another player is doing. As the ability to produce a unique, sustained edge dissipates, it becomes more probable that the KDAbet token stores the value of players +EV data due to token mining getting more difficult over time. 4. Implementation of PoE A pool of tokens is set aside for users to mine. Each market on the smart contract is afforded a reward for emission after the market is completed. The Reward is deflationary: −λ𝑥 + 𝐵𝑙𝑜𝑐𝑘 𝑅𝑒𝑤𝑎𝑟𝑑 = 𝐵(λ, 𝑥) = λ𝑒 , 𝑥ϵℵ (2) Where 𝑥 is an integer expressing the nth market block created to bet into and λ is a parameter controlling the decay rate of the block emission. A “block” is a set of markets in a market family of which the reward is equally distributed over, for example: baseball -> moneyline -> 15 games -> 2022-05-12. Bettors in the network buy tokens to match up bets in a software and push the matched amounts in the smart contract’s blocks in the form of a simple ledger. The ledger write dictates an escrow in the smart contract holds two users match funds while the sporting matchup is played. After the game is over, the Oracle (Sport Radar) provides resolution data and the bets in the ledger for that game are rolled up. Each bet in the block is enumerated through and the odds taken is compared to the closing line odds. An Emission is paid out according to a bettor's efficiency and matched volume. There are 4 scenarios that can play out for each individual who bets in the market. 1. The bettor won and had CLV. In this case the CLV is used to pay out tokens proportional to how efficient that bet was in the block segment 2. The bettor won but had negative CLV. The bettor essentially got lucky. 3. The bettor lost and had positive CLV. Although the bettor made the line more efficient, they simply got unlucky and lost. 4. The bettor lost and had negative CLV. The bet was simply a bad bet. The question is, if we have 𝑥 tokens as an emission, how do we emit these tokens to the users in a manner that rewards volume and CLV at the same time? We propose the following payoff matrix where V is the matched volume bet, α is a sensitivity parameter which controls how lopsided rewards are for efficient data, and δ is a suppressing fraction between 0 and 1 which punishes partial efficiency: Result CLV? Shares Won Yes V/(1+exp(-α*clv)) Won No δV/(1+exp(-α*clv)) Lost Yes δV(1+exp(-α*clv)) Lost No 0 The logistic function naturally emits rewards for the case of the winning bettor in a symmetric fashion around 0 CLV. The rewards are exponentially proportional with respect to increasing efficiency and winning. However, we still want to reward a losing bettor with a fractional emission who provides CLV and pay nothing to a losing bettor who exhibits no value in their on-chain data. In this way we say thank you to the sports bettor who gets unlucky but served up his information to help shape the line. The proportion of emitted tokens paid out to the bettors is the ratio of shares the bettor earned with the formula in the fee matrix over the sum of total shares of all market participants. Those who bet more, earn more, but those that bet efficiently and at scale earn the most by far. 5. Storage Of Value The dollar value of the $KDAb token is determined by the demand of the network on the token which is determined by the number of players and their demand for the betting token. The price is offset by the increasing supply of circulating tokens. Naturally, the emissions are constantly decreasing as each market resolves and subsequent attached rewards decrease over time as per (1). Assumptions ● The proposed token supply will be 100 million $KDAb. ● An initial cohort of 3000 bettors in line with LunaFi and SX launch values. ● We mint 13 million tokens to 3000 initial users at an arbitrary price of $0.50 ● We assume a growth rate k. ● We assume a Customer lifetime value of V. ● We assume a player capacity value, C. At the start of the network’s genesis block, a simple differential equation describes the growth rate. 𝑛'(𝑡) = 𝑘𝑛(t) (3) Where t is time. This first order differential equation has a simple solution: 𝑘𝑡 𝑛'(𝑡) = 𝑛(0) * 𝑒 (4) We assume that we will grow exponentially at the beginning as CLV rewards are very high and initial users can mine tokens with little competition in the various markets. As more and more miners enter the system trying to mine the market blocks the differential equation will become logistic. 𝑛(𝑡) 𝑛'(𝑡) = 𝑘(1 − 𝐶 )𝑛(𝑡) (5) Now we see we have a capacity value C, which constrains the amount of growth because as more and more market makers compete to match up high CLV bets in popular markets, the share reward drops dramatically, restricting the growth rate. The solution to (4) is: 𝑘𝑡 𝐶𝑛(0)𝑒 𝑛(𝑡) = 𝑘𝑡 (6) 𝑛(0)𝑒 + 𝐶 − 𝑛(0) By now anyone versed in math will notice the solution is the same as the famous population growth problem with a maximum capacity. But how does this relate to the price? As we mentioned the value of the token is related to the number of players and their expected Customer Lifetime Value expressed as total added liquidity, V, denoted in USD. However we have to account for the dropout rate, D, as players leave the system or run out of capital to keep betting. 𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝐿𝑖𝑞𝑢𝑖𝑑𝑖𝑡𝑦 = 𝑛(𝑡, 𝐶, 𝑘) 𝑉(1 − 𝐷) (7) And so we can estimate the token value as the expected as: 𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝐿𝑖𝑞𝑢𝑖𝑑𝑖𝑡𝑦 𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑇𝑜𝑘𝑒𝑛 𝑉𝑎𝑙𝑢𝑒 = 𝑇𝑜𝑘𝑒𝑛𝑠*(1−𝐵(λ, 𝑥)) (8) 6. Possible Ranges of the Storage Of Value The equation in (8) models the growth of the tokens value and so we want to ask some questions about the minimum viable network parameters required to build a network effect that matures into a global sports betting exchange. We know from DraftKings extensive public research that the average customer lifetime value in terms of deposits made by a random player at scale is $2,500 and they suggest (although not confirmed) a drop out rate of 5% and an acquisition cost of $375. An exchange takes a lot more market makers, capitalized players and arbitrageurs and so the expected per-player volume is higher. A conservative estimate of $5,000 Lifetime value per player is reasonable with the high end players populating the long tail of depositors. The updated token value function becomes: 𝑛(𝑡,𝐶,𝑘) 𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑇𝑜𝑘𝑒𝑛 𝑉𝑎𝑙𝑢𝑒 = 4500 * 8 (9) 10 *(1−𝐵(λ, 𝑥)) The KDAbet protocol expects to start with about 3,000 players via our established brokerage and player network, which currently serves many thousands of bettors for the last 20 years. And so with n(0) set, we only need to set a rational value for the capacity, C, and growth rate, k. Growth is nearly impossible to predict, so instead, we suppose a range of possible growth and measure the band structure of possible trajectories of the token within possible 10% to 100% growth YoY. However, we can reasonably set a capacity value: 𝐶 = 𝑉𝑖𝑎𝑏𝑙𝑒 𝑆𝑝𝑜𝑟𝑡𝑠 * 𝑀𝑎𝑟𝑘𝑒𝑡 𝑇𝑦𝑝𝑒𝑠 * 𝑈𝑛𝑖𝑞𝑢𝑒𝑠 = 21 * 5 * 4000 = 420, 000 Noting that Pinnacle serves 21 major sporting leagues with 5 major bet types and large bookmakers at scale like DraftKings report upwards of 1.3 million unique players. The dominating bet types are: ● Moneyline ● Point Spread ● Props ● Totals ● Futures We suggest a saturation capacity in each major market of about 4000 unique matched players before the block reward starts to decay to insignificance. If we assume a growth rate parameter in the interval [0.1, 1], we can update our token value function: 9 [0.1, 1.0]𝑡 1.26*10 *𝑒 1 𝑇𝑜𝑘𝑒𝑛 𝑉𝑎𝑙𝑢𝑒 = 4500 * [0.1, 1.0]𝑡 * 8 (10) 3000𝑒 + 420000 − 3000 10 (1−𝐵(λ, 𝑥)) All that is left is to decide the decay rate of the block rewards and the number of markets we want to decay over. There are approximately 20,000 tradable markets a year across the entire range of sports/Esports, and so, we can set 𝑥, in 𝐵, to be 200,000 which suggests a token mining horizon of 10 years. Suppose we set lambda, which is the y intercept of the block reward function, to be 0.00005. Our block reward decay structure then is visualized in figure. 3. Figure. 3 The exponential decay of the token emission as a function of markets offered. After about 5 years, the vast majority of the tokens are mined by players and the market is essentially saturated to the point of maximal value. Plugging in the value for B, we can update our token value function at a 10 year horizon: 𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑇𝑜𝑘𝑒𝑛 𝑉𝑎𝑙𝑢𝑒 [𝑚𝑖𝑛, 𝑚𝑎𝑥] = [$0. 36, $18. 78] (11) This analysis leads to a minimum and maximum range of KDAb token prices of $0.36 and $18.78 respectively, representing a possible -30% to 3800% ROI on mint price. Multiplying by the token supply by the range interval we get a market cap range of: 𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑀𝑎𝑟𝑘𝑒𝑡 𝐶𝑎𝑝 [𝑚𝑖𝑛, 𝑚𝑎𝑥] = [$36𝑚, $1. 87𝑏] (12) And furthermore we can estimate a breakeven growth rate, k, of 20.5% YoY over 10 years on the arbitrary mint price of $0.5. 7. Store of Value Table (YoY) The following chart expresses the end and midpoint token values and unique players at different realized average growth rates over the 10 year saturation timeline. We assume a maximum capacity of 420,000 players as mentioned in the previous section. Avg.Growth 5Yr Players 10Yr Players End Token Value End MktCap 10% 4,831 7,781 $0.36 $36.0m 20% 7,464 18,575 $0.953 $95.3m 30% 11,138 41,357 $2.386 $2.38B 40% 16,134 86,776 $5.33 $5.33B 50% 22,781 172,995 $9.75 $9.75B 60% 31,457 329,853 $14.05 $14.05B 70% 42,595 420,000 $16.77 $16.77B 80% 56,687 420,000 $18.05 $18.05B 90% 74282 420,000 $18.58 $18.58B 100% 96000 420,000 $18.78 $18.78B As growth starts to approach capacity we notice decreasing marginal benefit starts to blunt token value due to the predator-prey dynamic. As the token emission becomes far less valuable, growth must stymie and the network reaches its full saturation and therefore the goal of becoming a significant global web3 exchange. 8. Distribution of Rewards & Governance of Rewards The core goal of the protocol is to capture the critical data points that shape the line which means the parameters δ and α in the emission table must be chosen to optimize the retention of the core originators. If we distribute the reward too liberally, the best bettors will remove their liquidity and bet elsewhere. Furthermore this distribution needs to be able to change over time as network demographics grow and be governed by the community itself. Consider a mature betting market (for example baseball: moneyline) with 4000 active participants that are matching up bets daily. We can safely assume the following distribution of bettors in line with Betfair.com market statistics. ● 8 market makers providing 20% of total volume ● 200 sharp bettors providing 20% of the total volume ● 20 arbitrageurs providing about 10% of the volume ● 3772 retail players providing the final 50% of volume And in terms of realized CLV per dollar bet we can assume in a traditional bookmaker ● Market makers average 15% of relative CLV ● Sharps average 30% of the relative CLV ● Arbitrageurs average 15% of relative CLV ● Retail averages 40% of relative CLV With these assumptions we can make some pie charts expressing 3 different subjective payout regimes: Regime 1: broad distribution system α << 1 δ ≃ 1 In this regime, the slope of the logistic reward share of those bettors that mine rewards is more linear and the rewards are equally weighted so that the bulk of the tokens go to retail. Sharps still garnish a high rake with high volume. market makers losing out and arbers suffering the most. This regime is optimal when retail growth is the focus of the network. Regime 2: balanced distribution α ≃ 1 δ ≃ 0. 5 In this regime, the slope of the logistic reward share is close to the natural log. Market makers benefit the most because it excludes casual bettors, but doesn’t unfairly reward early sharps who dominate CLV. We use this regime when we want a steady flow of rewards to high volume bettors and to ensure that markets are well capitalized. Regime 3: skewed distribution α >> 1 δ << 0. 5 In this regime, unskilled bettors with low volume are punished and sharp bettors who shape the line are disproportionately rewarded, particularly when they provide significant volume. We use this regime when we are failing to attract sharp bettors into markets and arbitrageurs are bleeding the protocol of tokens too fast. The rewards are proposed as a dynamic system governed by the community itself where the tokens act as voting rights and the parameters can be tweaked toward optimality. The KDAbet protocol includes the ability to vote every month on the distribution so that the network is always dynamically stepping toward the fairest possible outcome in terms of rewards for the provision of +EV data. 9. Tokenomics The token distribution is designed to maximize network adoption. That means no venture capital or greedy team distributions to scare participants away. The distribution is as follows: ● 12% team tokens: We propose a team token allocation of 12%. ● 13% token sale: We distribute 13% of tokens to early community members and strategic investors with a focus on community members first. ● 5% liquidity pool: For early provision of market making capital when the network is brand new. ● 70% Mining. The bulk of the tokens goes to bet miners to incentivize participation. The token distribution suggests that the initial emission amount in the genesis block will be 3,500 KDAb tokens. After 1 year of emissions, the emission rate will be 1,400 tokens per market, rapidly decreasing as the network saturates. 10. Frontend/Backend/Licensing Platform Relationship KDABet enjoys a fruitful and friendly partnership and white label partnership with Lion Gaming Group who has agreed to be our backend, payment rail and frontend technology provider. Their platform specializes in robust solutions for exchange and bookmaker skins and completely takes care of the problem of building out a front end for the KDAb protocol. Furthermore, the company offers B2B and B2C license onboarding services ensuring that the markets that we expand into will be completely legal and respecting local jurisdiction with respect to onboarding players and dealing with web3 payment rails and regulatory concerns. . 11. Oracle Data Oracles are entities which provide data in order to resolve matched escrow in sports betting smart contracts. It is important to stress that Oracles in programmatically resolved sports betting contracts should NOT be decentralized at all. The Oracles should always come from official data, directly from the leagues at all times, as accuracy and legitimacy in bet resolution is paramount for players so that disputes are kept to a minimum. Only the leagues can provide this in a timely and organized manner, and SportRadar is the only firm that has official league data for all major markets. Our relationship with the Lion Gaming group gives us access to SportRadar, the premiere data service which works directly with the leagues to issue correct scoring data in all sports and Esports to bookmaking operations. 12. Concluding Remark The KDAbet protocol provides anmin effective method to store the value of sports betting data and create a two way market for originators to get paid for their contributions to a betting network. By ensuring that efficiency is compensated, we serve the betting community by forbidding any centralized entity from forming the ability to charge economic rent on their intellectual property. Appendix 1: Marketing Plan NFT’s/VR Lounge Increasing the lifetime value of the average customer is paramount toward generating a higher token price. In order to keep customers “sticky”, we will use the Marmalade NFT system to mint our own marketplace of unique sports betting NFT’s to generate a secondary market of mutable data assets that unlock special privileges and help keep a cohesive community together on social media. Marketing the protocol is accented with two plays. The first play is a mutable NFT market for users to show their community support and get sports betting bonuses. 1. Mutating NFT’s. We intend to allow people to mint NFT’s when their betting accounts reach certain milestones. We call this a progressive mint. For instance say you bet over $1 million in tokens. You can then mint an nft trait which gives you certain social benefits and free bets in large tournaments. You might win a huge March Madness tournament and that could get you access to a 1 on 1 meeting with SHAQ in vegas. Kadena is unique because of the Marmalade NFT market place which allows for storage of data on the NFT token itself. This means NFT’s can mutate as you unlock more milestones and your legend grows on the KDABet network. 2. Original Mint. For our early investors we will offer a limited mint of 3,000 elite NFT’s that display their dedication 3. Secondary Mint. For tag along players who join the protocol after launch, we will mint a further 3000 NFT’s after the floor price of the original mint and the mutable traits have built up enough to accrue value for those who dedicated time and money to the network when it was small. Examples of NFT traits are: ● Badges: Milestones and accomplishments in betting get tagged to the NFT art showing that the holder achieved social dominance in betting. ● Freerolls: If a bettor is efficient and mines a lot of tokens with significant volume, we will award the NFT holder a free bet from time to time. ● Exclusive Trips: We will buy NFT holders game tickets if they hold an NFT given out in a random raffle. ● Swag Packs: Exclusive KDAb swag and team swag to loyal NFT holders. ● Odds Boost: The user can boost their odds slightly on the house after a certain amount of volume has been bet. VR Lounge Thanks to our partnership with Lion Gaming Group, we will be creating a unique VR lounge for users to show off their NFT’s and hang out in a metaverse environment. The metaverse is an important marketing tool to capture mindshare and create unique new experiences for fans that transcend the banal marketing strategies of traditional fiat sportsbooks. The VR lounge will consist of a casino environment modeling after the “Cosmo” and feature a sitting area with large video players streaming sports and Esports. Members who venture into the VR lounge will enjoy benefits like: ● A progressive lottery that rewards a community member randomly with a large monetary reward from micro taxes charged to users who bet in the lounge. ● Casino games and fun slots that give rewards to people who are waiting around for games ● Large scale tweet screens that feature user engagement and airdrops tokens to users who promote the lounge and KDAbet brand. ● Daily bet gathering airdrops for people who come and watch the game in the lounge and participate with users. These are just a few examples of creative ways to keep the most valuable players active in the network. Appendix 2: Core Operating Team Duncan McIntyre. Partner ~ J.D Corporate Law. Duncan is an entrepreneurial tech executive with a proven track record of scaling companies, fundraising, & solving complex legal issues. Duncan currently serves as President and CEO of Lion Gaming Group Inc., a gaming software development company with a focus on bleeding-edge technologies. Previously, Duncan was a founder of FansUnite, serving as its COO and a Director through public listing. Duncan also played a pivotal role at Victory Square Technologies, with the number of portfolio companies growing from 2 to 21 and the market cap from approximately $20M to $220M while he was involved. Duncan has also been extensively involved in multiple global M&A transactions. Martin Bailey. ~ Partner, B.Eng Software Engineering Martin is an expert in the field of software architecture and scalable computing. He’s an experienced business executive in charge of our technology strategy. Martin is best known as the developer of high-performance software for Avigilon Inc’s world class camera surveillance system which led to an IPO, a billion dollar acquisition in 2018 and massive deployment of smart cameras in stadiums and casinos around the globe. He exited his 2nd startup Karma Insurance in 2020 and now advises strategic clients and operates sports analytics models at scale as a founder at Highwater Technologies Inc. Joey Fortuna ~ Partner B.Sc Kinesiology Joey is one of the most well known sports bettors on the earth and has grown the premiere brokerage in America, handling hundreds of millions of dollars of volume per year in over 12 sports. He has been featured on 4 major Television networks and every podcast in the sports betting space for his expertise in at-scale trading. He has every executive in every major sportsbook on his rolodex and acts as the liaison for Highwater in sales, business and accounts as well as functioning as our Head Trader and VP Risk. James Mcloughlin ~ Partner, B.Comm James is a highly experienced and respected marketing executive who spearheaded the content division at Betfair, the world's largest exchange for 4 years marketing to millions of global players from retail to the largest syndicates in the world. Previous to Betfair, James operated as a senior bookmaker at sportsbet, serving thousands of Australian customers and has a wealth of connections with respect to whale players in the industry. James is also an experienced web3 proponent and crypto trader and currently serves as director of marketing at BOOM sports, a highly successful startup in the white label space that completed its series B raise. Stephen Rothwell. ~ Partner, BSc, Math/Physics, M.Sc, Machine Learning Stephen is in charge of developing the automated market makers for KDAbet which extract liquidity from retail bettors and provide cross market liquidity to KDABet. He is a master of machine learning and statistics as well as an accomplished computer scientist. His accomplishments include two exits, one IPO with Fansunite, building the world's first quantum computer with a team of 26 at D-Wave. He developed brain scanning software with NMR magnets at the University of Lethbridge. He is a respected sports bettor in the USA with over 10 years of at scale betting experience in 4 different sports. Jesse Learmonth ~ Advisor, B.Comm Jesse is a highly experienced sports betting product leader and operator in the space. Jesse is best known for his time as the Director of Product Management at the world's largest bookmaker, Pinnacle Sports. Over a 6 year tenure working from the company’s global head office in Curacao, he led the teams that completely overhauled the sportsbook product experience into a modern UX that serves players in 100+ countries. Previous to that, he co-founded Bet Smart Media, which developed software and applications for over two dozen tier-1 sports betting brands. Bet Smart Media was acquired by Pinnacle in 2015. Having built many applications for the biggest brands in the space, Jesse has a deep industry network across the globe and will lend his expertise to help shape the product experience for KDAbet. Jesse currently hosts the popular sports betting podcast “Betting Startups Podcast”, which interviews founders of the most promising betting industry startups. All information included herein is copyright © KDABet Inc, 2022