Today, I want to tell you a bit more about who you will be facing on the court in Hardcourt Balls. See, the AI opponents you'll play against are not just some generic random dice rollers. Each one of them is in fact hand-crafted to mimic the challenge of playing against some of the best players on tour today!
But before we dive in, two things real quick:
A) you may be wondering about the demo. Yes, it's coming along nicely. I will show more in the next update, but for now, just know that it will be called Hardcourt Balls - Qualifiers and arrive with its own Steam page. No date yet, but - soon-ish!
B) Don't forget to wish list Hardcourt Balls and tell your friends about it! I can't emphasize enough what a difference this makes for a niche indie game!
The AI opponents you will be facing in Hardcourt Balls are NOT randomly generated! Instead, they are hand-crafted to behave like real players. Do they like passing shots? Do they prefer dropshots? Are they baseline huggers? Do they prefer cross play? Do they like body serves?
I've actually spent months researching the play patterns of hundreds of actual ATP players using amazing websites like Tennis Stats and Tenis Abstract (you really ought to check them out, incredible fan work! You can participate, too!) and created unique player profiles for Hardcourt Balls that mirror some of the distinct play styles. I am not just talking here about assigning skill bonuses to Forehand, Backhand, Serve etc., either; these sites go much deeper, tracking statistics for shot selection, shot types, shot direction, and more. Here is the page for Nole, for example: Match Charting Project Player Data: Novak Djokovic Detailed Stats | Tennis Abstract Click on Shot Types or Shot Selection to see examples of what I am talking about.
To be clear: you will NOT find Nole or any other ATP player in the game. I am not allowed to do that, since the game is not affiliated with, nor endorsed by, nor licensed from, the various tennis organizations (not for lack of trying. I've reached out multiple times but never received a response). But you will find randomized players whose profiles may be similar to or inspired by real tennis pros from past and present.
I distilled these statistics to a unique matrix of probabilities defining which tiles on the court the player likes to target depending on his own position! Here is an example (for a pretty famous right-handed player):
I hope the graphic is pretty self-explanatory. But here are a couple of examples of how to read it.
When serving into the deuce (right) court, there is a 39% chance that the player will target wide (right hand corner).
When playing forehand, there is a 38% chance that the player will play down the line (right hand side of the court).
When playing backhand, there is a 57% chance for a backhand cross (to the right side of the field).
The end result - between the different traits and strengths, left and right-handed players, and all the unique styles - is that every match feels different and poses unique challenges. Just like in real life tennis, you will need to adapt your tactics for every match in order to win. Find ways to maximize your strengths while minimizing the opponent's. Learn to anticipate your opponent's moves and decide if you want to risk it all for a winner or play it safe and keep increasing the pressure.
And don't forget to wishlist if you haven't done so already! You don't want to miss the next updates: I will reveal more details about the upcoming demo, tutorials, and peel back another layer of the onion into some of the deeper tactics hidden in the deceivingly simple dice mechanics.