Tomida, Yuta
Kwon, Soon Woo
Predictions:
| Market | Prediction | Odd | Result |
|---|---|---|---|
| Under 1st Set Games | 75.00% | ||
| Tie Break in 1st Set (No) | 96.70% | ||
| Over 1st Set Games | 68.60% | ||
| Tie Break in Match (No) | 87.00% | ||
| Under 2.5 Sets | 76.30% | ||
| Total Games 3-Way (Under 22) | 70.30% | ||
| Total Games 2-Way (Under 22.5) | 69.70% |
Overview of the Tennis Match: Tomida, Yuta vs. Kwon, Soon Woo
%%% This match between Tomida, Yuta and Kwon, Soon Woo promises to be a thrilling encounter in the tennis world. Both players bring unique strengths to the court, creating an exciting dynamic for fans and bettors alike. Tomida, known for his powerful serve and agility, will face off against Kwon, who is celebrated for his strategic play and resilience under pressure. As we approach the match scheduled for July 22, 2025, let’s delve into the betting aspects and predictions for this highly anticipated event. %%%
Betting Predictions
Head-to-Head Odds: Given Tomida’s recent form and his ability to dominate with his serve, he might be favored in head-to-head betting odds. However, Kwon’s solid track record and tactical prowess should not be underestimated, making this a potentially close contest.
Head-to-Head Betting Tip: Consider backing Tomida, but keep an eye on Kwon’s performance, especially if he capitalizes on break points.
Set Betting Analysis
Set 1 Prediction: Tomida is likely to leverage his powerful serve to close out the first set quickly. Bettors might find value in a bet for a swift set victory, possibly under 6 games.
Set 1 Betting Tip: Bet on Tomida to win Set 1 in straight sets.
Total Games in Match
Total Games Bettor’s Decision: Considering both players’ endurance and past performances in longer matches, the total games bet could lean towards the higher end. The clash of styles might extend the match beyond three sets.
Total Games Betting Tip: Consider placing a bet on an over if you’re looking for a longer match with more games played.
Player Performance Metrics
Tomida’s Serve Efficiency: Track Tomida’s first serve percentage and ace count. A strong serve could dictate the pace and outcome of the match, making initial games critical for betting insights.
Performance Tip: Monitor Tomida’s service games closely as they could be crucial in tight-set situations.
Kwon’s Break Point Conversion: Kwon’s ability to convert break points will be key. Analyzing his performance during crucial tie-breaks or deuce points could influence betting strategies.
Performance Tip: Betting on Kwon’s break point success could be insightful if he starts to show aggressive play.
Tournament Context
The stakes are high as both players aim to bolster their rankings leading into the latter part of the season. Their previous encounters have typically showcased tight rallies and strategic defenses, making each point count.
Tournament Insight: Consider how recent tournament performances may affect player mindset and endurance before placing bets.
b1naryth4i5/soccer_hw/src/ODF.cpp
#include «ODF.hpp»
#include
#include «particles.hpp»
class DoubleGaussian2D {
private:
double x;
double y;
double c1;
double s1;
double c2;
double s2;
public:
DoubleGaussian2D(double x_, double y_, double c1_, double s1_, double c2_, double s2_) :
x{x_}, y{y_}, c1{c1_}, s1{s1_}, c2{c2_}, s2{s2_} {}
double value(double x_, double y_) const {
double dx = x – x_;
double dy = y – y_;
return exp(-(dx * dx + dy * dy) / (2 * s1 * s1)) / (sqrt(2 * M_PI) * s1)
+ exp(-(dx * dx + dy * dy) / (2 * s2 * s2)) / (sqrt(2 * M_PI) * s2);
}
};
double calcDistance(const Point & p1, const Point & p2) {
double dx = p1.getX() – p2.getX();
double dy = p1.getY() – p2.getY();
return sqrt(dx * dx + dy * dy);
}
double calcAttraction(const Particle & p, const Field & field) {
const SoccerParam::TeamParam & teamParam = p.getVisibility() ? field.getRedTeamParam() : field.getBlueTeamParam();
const WorldModel & world = field.getWorldModel(p.getVisibility());
const PlayerData & pd = field.getPlayerData(world.getPlayerID(p.getVisibility()));
double t = listAttraction().back().first;
int numPlayers = 0;
double totalDistance = 0.0;
for (const PlayerData & op : world.getOpponentTeam()) {
if (!op.isGhost() && !op.isPenaltyKicker()) {
totalDistance += calcDistance(pd.getPosition(), op.getPosition());
numPlayers += 1;
}
}
if (numPlayers == 0) {
numPlayers = 1;
totalDistance = teamParam.sightRadius;
}
totalDistance /= numPlayers;
return listAttraction().back().second + t * totalDistance;
}
double ODF::calcGoalAssistPotential(const Field & field, const Particle & p, double dist) const {
const WorldModel & mod = field.getWorldModel(p.getVisibility());
const PlayerData & pd = field.getPlayerData(mod.getPlayerID(p.getVisibility()));
const SoccerParam::FieldParam & param = field.getPhysicalParam().fieldParam;
if (param.goalArea.p.x > 0 && param.goalArea.p.y > 0) {
dist = util::distToSegment({param.goalArea.p.x, param.goalArea.p.y},
{param.goalArea.q.x, param.goalArea.q.y},
{pd.getPosition().x, pd.getPosition().y});
} else {
dist = calcDistance(pd.getPosition(),
{field.getGoalPosition(p.getVisibility()).x – param.goalPenaltyArea.p.x,
field.getGoalPosition(p.getVisibility()).y – param.goalPenaltyArea.p.y});
}
if (dist > param.goalWidth) {
return -10000;
}
double crossRatio = std::fabs(dist) / param.goalWidth;
return listGoalAssistPotential().back().second
+ listGoalAssistPotential().back().first * crossRatio;
}
double ODF::calcPotential(const Field & field, const Particle & p) const {
const SoccerParam::FieldParam & param = field.getPhysicalParam().fieldParam;
const SoccerParam::TeamParam & teamParam = p.getVisibility() ? field.getRedTeamParam() : field.getBlueTeamParam();
const WorldModel & mod = field.getWorldModel(p.getVisibility());
const PlayerData & pd = field.getPlayerData(mod.getPlayerID(p.getVisibility()));
int modPlayerCnt = (int) mod.getAllyTeam().size();
if (modPlayerCnt == 0) {
return listPotential().back().second + listPotential().back().first * param.ballRadius + dec(ballRadiusInfluence);
} else {
return listPotential().back().second + listPotential().back().first * param.ballRadius / modPlayerCnt + dec(ballRadiusInfluence);
}
//if (p.isHostile()) {
// return listPotential().back().second + listPotential().back().first * param.ballRadius + dec(ballRadiusInfluence);
//}
//double myDist = ((double) modPlayerCnt) * field.distToNearestTeammate(p.getPosition(), {param.playableAreaWidth, param.playableAreaDepth}) / (param.playableAreaDepth – param.goalDepth);
//return listPotential().back().second + listPotential().back().first * myDist + dec(ballRadiusInfluence);
}
std::pair ODF::calcGoalPotential(const Field & field, const Particle & p) const {
const SoccerParam::TeamParam & teamParam = p.getVisibility() ? field.getRedTeamParam() : field.getBlueTeamParam();
const WorldModel & world = field.getWorldModel(p.getVisibility());
return { -10.0 – (double) listGoalPotential().size() + dec(goalPartWithPotential),
(double) listGoalPotential().size() * (teamParam.sightRadius – calcDistance(field.getGoalPosition(p.getVisibility()),
world.getPosition())) };
}
std::shared_ptr ODF::createDoubleGaussian(const Point & pos_, double sigma1_, double sigma2_) const {
Point pos{pos_.x, pos_.y};
auto sigma1 = sigma1_;
auto sigma2 = sigma2_;
if ((pos_.x != kOrigin.x || pos_.y != kOrigin.y) && !util::isInsideField(pos_.x, pos_.y)) {
pos.x += kStandardBoundary.x;
pos.y += kStandardBoundary.y;
sigma1 += kStandardBoundary.x + kStandardBoundary.y;
sigma2 += kStandardBoundary.x + kStandardBoundary.y;
}
return std::make_shared(pos.x, pos.y,
sigma1, sigma1 / sqrt(-log(0.001)),
sigma2, sigma2 / sqrt(-log(0.001)));
}
double ODF::calcPathWidth(const Field & field, const Particle & p) const {
const SoccerParam::FieldParam & param = field.getPhysicalParam().fieldParam;
const WorldModel & world = field.getWorldModel(p.getVisibility());
int modPlayerCnt = (int) world.getPlayerList().size();
// standard path Widtch
double pathWidth = pathAttract() * std::min(param.goalWidth, param.playableAreaWidth / modPlayerCnt);
// avoid opponent
if (world.opponentCount() > 0) {
std::pair cMeanStd =
field.calcOpponentMeanStd({world.getPosition(),
world.kickableArea}, world.getOpponentTeam());
pathWidth = std::max(pathWidth, cMeanStd.first + pathAttract() * cMeanStd.second);
}
return pathWidth;
}
std::pair<std::vector, std::vector<std::shared_ptr>> ODF::getBarrierRegion(const Field& field, double pathWidth) const {
// if the number of player is one, use thin ballRadiusWhenAlone
const WorldModel & world = field.getWorldModel(field.countHostileParticle() == 8 ? false : true);
int modPlayerCnt = (int) world.getPlayerList().size();
if (modPlayerCnt == 0 || !world.amAlive()) {
pathWidth += ballRadiusWhenAlone;
// ghost player
if (modPlayerCnt == 0) {
pathWidth += trailInfluence * std::sqrt(field.countHostileParticle() – modPlayerCnt);
}
} else {
pathWidth += ballRadiusInPresenceOfOthers;
// ghost team
if (!world.amAlive()) {
pathWidth += trailInfluence * (field.countHostileParticle() – modPlayerCnt);
}
}
const SoccerParam::FieldParam & param = field.getPhysicalParam().fieldParam;
std::vector barrierRegion;
Region region{listBarrierRegion().back().first};
double factor = std::min(listBarrierRegion().back().second,
pathWidth / param.playableAreaDepth);
barrierRegion.push_back(region * Factor{factor,
factor,
factor});
std::vector<std::shared_ptr> potentialList;
// the mean of opponent position
std::pair cMeanStd;
if (!world.opponentCountEmpty()) {
std::pair cMeanStd =
field.calcOpponentMeanStd({world.getPosition(),
world.kickableArea}, world.getOpponentTeam());
barrierRegion.emplace_back({cMeanStd.first – pathWidth / param.playableAreaDepth / kBoundaryDilation,
cMeanStd.first + pathWidth / param.playableAreaDepth / kBoundaryDilation},
{-std::abs(cMeanStd.first – param.ballRadius – cMeanStd.second),
std::abs(cMeanStd.first + param.ballRadius + cMeanStd.second)}, Factor{1.0, pathWidth, param.playableAreaDepth},
calcBarrierPotential(field.worldModel(), field.playerData(world.playerID()).getPosition(), cMeanStd));
potentialList.push_back(createDoubleGaussian({cMeanStd.first – pathWidth / param.playableAreaDepth,
cMeanStd.second},
cMeanStd.second / trajectoryLength,
cMeanStd.second));
// barrierRegion.emplace_back({cMeanStd.first – pathWidth / param.playableAreaDepth,
// cMeanStd.first + pathWidth / param.playableAreaDepth},
// {-std::abs(cMeanStd.first – param.ballRadius – cMeanStd.second),
// std::abs(cMeanStd.first + param.ballRadius + cMeanStd.second)},
// Factor{1.0, pathWidth, param.playableAreaDepth},
// calcBarrierPotential(field.worldModel(), field.playerData(field.worldModel().getPlayerID()).getPosition(), cMeanStd));
// potentialList.push_back(createDoubleGaussian({cMeanStd.first,
// cMeanStd.second},
// cMeanStd.second / trajactoyLength,
// cMeanStd.second));
}
// barrier position
// for (const PlayerData & p : field.worldModel().getAllyTeam()) {
// if (!p.isGhost()) {
// barrierRegion.emplace_back({p.getPosition().x – pathWidth / param.playableAreaDepth / kBoundaryDilation,
// p.getPosition().x + pathWidth / param.playableAreaDepth / kBoundaryDilation},
// {p.getPosition().y – pathWidth / param.playableAreaWidth / kBoundaryDilation,
// p.getPosition().y + pathWidth / param.playableAreaWidth / kBoundaryDilation},
// Factor{1.0, pathWidth, param.playableAreaDepth},
// calcBarrierPotential(field.worldModel(), p.getPosition()));
//
// potentialList.push_back(createDoubleGaussian({p.getPosition().x,
// p.getPosition().y},
// pathWidth / trajectoryLength,
// pathWidth));
// }
// }
// if (field.worldModel().getAllyTeamSize() > 0) {
// std::pair teammatePosition =
// field.distToNearestTeammate(field.worldModel().getSelfPosition(),
// {param.playableAreaWidth, param.playableAreaDepth});
//
// region = {teammatePosition.first – pathWidth / param.playableAreaDepth / kBoundaryDilation,
// teammatePosition.first + pathWidth / param.playableAreaDepth / kBoundaryDilation,
// teammatePosition.second – pathWidth / param.playableAreaWidth / kBoundaryDilation,
// teammatePosition.second + pathWidth / param.playableAreaWidth / kBoundaryDilation};
//
// barrierRegion.push_back(region * Factor{factor,
// factor,
// factor});
//
// }
// // ball position
// PositionType ballX;
// PositionType ballY;
//
// if (field.worldModel().getSelfPosition().x == kOrigin.x &&
// field.worldModel().getSelfPosition().y == kOrigin.y) {
// ballX = field.worldModel().getBall().position.x + kStandardBoundary.x;
// ballY = field.worldModel().getBall().position.y + kStandardBoundary.y;
// } else {
// ballX = field.worldModel().getBall().position.x;
// ballY = field.worldModel().getBall().position.y;
// }
//
// barrierRegion.emplace_back({ballX – pathWidth / param.playableAreaDepth / kBoundaryDilation,
// ballX + pathWidth / param.playableAreaDepth / kBoundaryDilation},
// {ballY – pathWidth / param.playableAreaWidth / kBoundaryDilation,
// ballY + pathWidth / param.playableAreaWidth / kBoundaryDilation},
// Factor{1.0, pathWidth, param.playableAreaDepth},
// calcBarrierPotential(field.worldModel(), {ballX, ballY}, {0.0,0.0}));
// region = {ballX – pathWidth / param.playableAreaDepth / kBoundaryDilation,
// ballX + pathWidth / param.playableAreaDepth / kBoundaryDilation,
// ballY – pathWidth / param.playableAreaWidth / kBoundaryDilation,
// ballY + pathWidth / param.playableAreaWidth / kBoundaryDilation};
//
// barrierRegion.push_back(region * Factor{factor,
// factor,
// factor});
return {barrierRegion, potentialList};
}
std::pair<std::vector, std::vector<std::shared_ptr>> ODF::getBallOfFusionRegion(const Field& field) const {
const WorldModel & world = field.worldModel();
if (world.opponentCount() == 0 || !world.amAlive()) {
return {{}, {}};
}
std::pair oppMeanStd =
field.calcOpponentMeanStd({world.getPosition(),
world.kickableArea}, world.getOpponentTeam());
Region region{oppMeanStd.first – oppMeanStd.second,
oppMeanStd.first + oppMeanStd.second,
oppMeanStd.second – oppMeanStd.second,
oppMeanStd.second + oppMeanStd.second};
// use parameterized ball of fusion
//
